refy/example_library.bib

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@UNPUBLISHED{Okazawa2021-qd,
  title    = "The geometry of the representation of decision variable and
              stimulus difficulty in the parietal cortex",
  author   = "Okazawa, Gouki and Hatch, Christina E and Mancoo, Allan and
              Machens, Christian K and Kiani, Roozbeh",
  abstract = "Lateral intraparietal (LIP) neurons represent formation of
              perceptual decisions involving eye movements. In circuit models
              for these decisions, neural ensembles that encode actions compete
              to form decisions. Consequently, decision variables (DVs) are
              represented as partially potentiated action plans, where
              ensembles increase their average responses for stronger evidence
              supporting their preferred actions. As another consequence, DV
              representation and readout are implemented similarly for
              decisions with identical competing actions, irrespective of input
              and task context differences. Here, we challenge those core
              principles using a novel face-discrimination task, where LIP
              firing rates decrease with supporting evidence, contrary to
              conventional motion-discrimination tasks. These opposite response
              patterns arise from similar mechanisms in which decisions form
              along curved population-response manifolds misaligned with action
              representations. These manifolds rotate in state space based on
              task context, necessitating distinct readouts. We show similar
              manifolds in lateral and medial prefrontal cortices, suggesting a
              ubiquitous representational geometry across decision-making
              circuits. \#\#\# Competing Interest Statement The authors have
              declared no competing interest.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2021.01.04.425244",
  month    =  jan,
  year     =  2021,
  keywords = "To Read",
  language = "en"
}

@ARTICLE{Murakami2014-lh,
  title     = "Neural antecedents of self-initiated actions in secondary motor
               cortex",
  author    = "Murakami, Masayoshi and Vicente, M In{\^e}s and Costa, Gil M and
               Mainen, Zachary F",
  abstract  = "The neural origins of spontaneous or self-initiated actions are
               not well understood and their interpretation is controversial.
               To address these issues, we used a task in which rats decide
               when to abort waiting for a delayed tone. We recorded neurons in
               the secondary motor cortex (M2) and interpreted our findings in
               light of an integration-to-bound decision model. A first
               population of M2 neurons ramped to a constant threshold at rates
               proportional to waiting time, strongly resembling integrator
               output. A second population, which we propose provide input to
               the integrator, fired in sequences and showed trial-to-trial
               rate fluctuations correlated with waiting times. An integration
               model fit to these data also quantitatively predicted the
               observed inter-neuronal correlations. Together, these results
               reinforce the generality of the integration-to-bound model of
               decision-making. These models identify the initial intention to
               act as the moment of threshold crossing while explaining how
               antecedent subthreshold neural activity can influence an action
               without implying a decision.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  17,
  number    =  11,
  pages     = "1574--1582",
  month     =  nov,
  year      =  2014,
  language  = "en"
}

@ARTICLE{Gremel2013-im,
  title     = "Premotor cortex is critical for goal-directed actions",
  author    = "Gremel, Christina M and Costa, Rui M",
  abstract  = "Shifting between motor plans is often necessary for adaptive
               behavior. When faced with changing consequences of one's
               actions, it is often imperative to switch from automatic actions
               to deliberative and controlled actions. The pre-supplementary
               motor area (pre-SMA) in primates, akin to the premotor cortex
               (M2) in mice, has been implicated in motor learning and
               planning, and action switching. We hypothesized that M2 would be
               differentially involved in goal-directed actions, which are
               controlled by their consequences vs. habits, which are more
               dependent on their past reinforcement history and less on their
               consequences. To investigate this, we performed M2 lesions in
               mice and then concurrently trained them to press the same lever
               for the same food reward using two different schedules of
               reinforcement that differentially bias towards the use of
               goal-directed versus habitual action strategies. We then probed
               whether actions were dependent on their expected consequence
               through outcome revaluation testing. We uncovered that M2
               lesions did not affect the acquisition of lever-pressing.
               However, in mice with M2 lesions, lever-pressing was insensitive
               to changes in expected outcome value following goal-directed
               training. However, habitual actions were intact. We confirmed a
               role for M2 in goal-directed but not habitual actions in
               separate groups of mice trained on the individual schedules
               biasing towards goal-directed versus habitual actions. These
               data indicate that M2 is critical for actions to be updated
               based on their consequences, and suggest that habitual action
               strategies may not require processing by M2 and the updating of
               motor plans.",
  journal   = "Front. Comput. Neurosci.",
  publisher = "frontiersin.org",
  volume    =  7,
  pages     = "110",
  month     =  aug,
  year      =  2013,
  keywords  = "action selection; goal-directed actions; habitual actions;
               premotor cortex; value-based decision making;To Read",
  language  = "en"
}

@ARTICLE{Erlich2011-rn,
  title     = "A cortical substrate for memory-guided orienting in the rat",
  author    = "Erlich, Jeffrey C and Bialek, Max and Brody, Carlos D",
  abstract  = "Anatomical, stimulation, and lesion data have suggested a
               homology between the rat frontal orienting fields (FOF)
               (centered at +2 AP, $\pm$1.3 ML mm from Bregma) and primate
               frontal cortices such as the frontal or supplementary eye
               fields. We investigated the functional role of the FOF using
               rats trained to perform a memory-guided orienting task, in which
               there was a delay period between the end of a sensory stimulus
               instructing orienting direction and the time of the allowed
               motor response. Unilateral inactivation of the FOF resulted in
               impaired contralateral responses. Extracellular recordings of
               single units revealed that 37\% of FOF neurons had delay period
               firing rates that predicted the direction of the rats' later
               orienting motion. Our data provide the first
               electrophysiological and pharmacological evidence supporting the
               existence in the rat, as in the primate, of a frontal cortical
               area involved in the preparation and/or planning of orienting
               responses.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  72,
  number    =  2,
  pages     = "330--343",
  month     =  oct,
  year      =  2011,
  keywords  = "To Read",
  language  = "en"
}

@ARTICLE{Jeong2016-dq,
  title    = "Comparative three-dimensional connectome map of motor cortical
              projections in the mouse brain",
  author   = "Jeong, Minju and Kim, Yongsoo and Kim, Jeongjin and Ferrante,
              Daniel D and Mitra, Partha P and Osten, Pavel and Kim, Daesoo",
  abstract = "The motor cortex orchestrates simple to complex motor behaviors
              through its output projections to target areas. The primary (MOp)
              and secondary (MOs) motor cortices are known to produce specific
              output projections that are targeted to both similar and
              different target areas. These projections are further divided
              into layer 5 and 6 neuronal outputs, thereby producing four
              cortical outputs that may target other areas in a combinatorial
              manner. However, the precise network structure that integrates
              these four projections remains poorly understood. Here, we
              constructed a whole-brain, three-dimensional (3D) map showing the
              tract pathways and targeting locations of these four motor
              cortical outputs in mice. Remarkably, these motor cortical
              projections showed unique and separate tract pathways despite
              targeting similar areas. Within target areas, various
              combinations of these four projections were defined based on
              specific 3D spatial patterns, reflecting anterior-posterior,
              dorsal-ventral, and core-capsular relationships. This 3D
              topographic map ultimately provides evidence for the relevance of
              comparative connectomics: motor cortical projections known to be
              convergent are actually segregated in many target areas with
              unique targeting patterns, a finding that has anatomical value
              for revealing functional subdomains that have not been classified
              by conventional methods.",
  journal  = "Sci. Rep.",
  volume   =  6,
  pages    = "20072",
  month    =  feb,
  year     =  2016,
  keywords = "To Read",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Gradinaru2007-qv,
  title     = "Targeting and readout strategies for fast optical neural control
               in vitro and in vivo",
  author    = "Gradinaru, Viviana and Thompson, Kimberly R and Zhang, Feng and
               Mogri, Murtaza and Kay, Kenneth and Schneider, M Bret and
               Deisseroth, Karl",
  abstract  = "Major obstacles faced by neuroscientists in attempting to
               unravel the complexity of brain function include both the
               heterogeneity of brain tissue (with a multitude of cell types
               present in vivo) and the high speed of brain information
               processing (with behaviorally relevant millisecondscale
               electrical activity patterns). To address different aspects of
               these technical constraints, genetically targetable neural
               modulation tools have been developed by a number of groups
               (Zemelman et al., 2002; Banghart et al., 2004; Karpova et al.,
               2005; Lima …",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  27,
  number    =  52,
  pages     = "14231--14238",
  month     =  dec,
  year      =  2007,
  keywords  = "Locomotion;To Read",
  language  = "en"
}

@ARTICLE{Magno2019-qz,
  title    = "Optogenetic Stimulation of the {M2} Cortex Reverts Motor
              Dysfunction in a Mouse Model of Parkinson's Disease",
  author   = "Magno, Luiz Alexandre Viana and Tenza-Ferrer, Helia and
              Collodetti, M{\'e}lcar and Aguiar, Matheus Felipe Guimar{\~a}es
              and Rodrigues, Ana Paula Carneiro and da Silva, Rodrigo Souza and
              Silva, Joice do Prado and Nicolau, Nycolle Ferreira and Rosa,
              Daniela Valad{\~a}o Freitas and Birbrair, Alexander and Miranda,
              D{\'e}bora Marques and Romano-Silva, Marco Aur{\'e}lio",
  abstract = "Neuromodulation of deep brain structures (deep brain stimulation)
              is the current surgical procedure for treatment of Parkinson's
              disease (PD). Less studied is the stimulation of cortical motor
              areas to treat PD symptoms, although also known to alleviate
              motor disturbances in PD. We were able to show that optogenetic
              activation of secondary (M2) motor cortex improves motor
              functions in dopamine-depleted male mice. The stimulated M2
              cortex harbors glutamatergic pyramidal neurons that project to
              subcortical structures, critically involved in motor control, and
              makes synaptic contacts with dopaminergic neurons. Strikingly,
              optogenetic activation of M2 neurons or axons into the
              dorsomedial striatum increases striatal levels of dopamine and
              evokes locomotor activity. We found that dopamine
              neurotransmission sensitizes the locomotor behavior elicited by
              activation of M2 neurons. Furthermore, combination of intranigral
              infusion of glutamatergic antagonists and circuit specific
              optogenetic stimulation revealed that behavioral response
              depended on the activity of M2 neurons projecting to SNc.
              Interestingly, repeated M2 stimulation combined with l-DOPA
              treatment produced an unanticipated improvement in working memory
              performance, which was absent in control mice under l-DOPA
              treatment only. Therefore, the M2-basal ganglia circuit is
              critical for the assembly of the motor and cognitive function,
              and this study demonstrates a therapeutic mechanism for cortical
              stimulation in PD that involves recruitment of long-range
              glutamatergic projection neurons.SIGNIFICANCE STATEMENT Some
              patients with Parkinson's disease are offered treatment through
              surgery, which consists of delivering electrical current to
              regions deep within the brain. This study shows that stimulation
              of an area located on the brain surface, known as the secondary
              motor cortex, can also reverse movement disorders in mice.
              Authors have used a brain stimulation technique called
              optogenetics, which allowed targeting a specific type of surface
              neuron that communicates with the deep part of the brain involved
              in movement control. The study also shows that a combination of
              this stimulation with drug treatment might be useful to treat
              memory impairment, a kind of cognitive problem in Parkinson's
              disease.",
  journal  = "J. Neurosci.",
  volume   =  39,
  number   =  17,
  pages    = "3234--3248",
  month    =  apr,
  year     =  2019,
  keywords = "Parkinson's disorder; brain stimulation; cognition; movement;
              optogenetics; prefrontal cortex;Locomotion;To Read",
  language = "en"
}

@ARTICLE{Schiemann2015-th,
  title     = "Cellular mechanisms underlying behavioral state-dependent
               bidirectional modulation of motor cortex output",
  author    = "Schiemann, Julia and Puggioni, Paolo and Dacre, Joshua and
               Pelko, Miha and Domanski, Aleksander and van Rossum, Mark C W
               and Duguid, Ian",
  abstract  = "Neuronal activity in primary motor cortex (M1) correlates with
               behavioral state, but the cellular mechanisms underpinning
               behavioral state-dependent modulation of M1 output remain
               largely unresolved. Here, we performed in vivo patch-clamp
               recordings from layer 5B (L5B) pyramidal neurons in awake mice
               during quiet wakefulness and self-paced, voluntary movement. We
               show that L5B output neurons display bidirectional (i.e.,
               enhanced or suppressed) firing rate changes during movement,
               mediated via two opposing subthreshold mechanisms: (1) a global
               decrease in membrane potential variability that reduced L5B
               firing rates (L5Bsuppressed neurons), and (2) a coincident
               noradrenaline-mediated increase in excitatory drive to a
               subpopulation of L5B neurons (L5Benhanced neurons) that elevated
               firing rates. Blocking noradrenergic receptors in forelimb M1
               abolished the bidirectional modulation of M1 output during
               movement and selectively impaired contralateral forelimb motor
               coordination. Together, our results provide a mechanism for how
               noradrenergic neuromodulation and network-driven input changes
               bidirectionally modulate M1 output during motor behavior.",
  journal   = "Cell Rep.",
  publisher = "Elsevier",
  volume    =  11,
  number    =  8,
  pages     = "1319--1330",
  month     =  may,
  year      =  2015,
  keywords  = "To Read",
  language  = "en"
}

@ARTICLE{Ebbesen2017-cm,
  title    = "Motor cortex - to act or not to act?",
  author   = "Ebbesen, Christian Laut and Brecht, Michael",
  abstract = "The motor cortex is a large frontal structure in the cerebral
              cortex of eutherian mammals. A vast array of evidence implicates
              the motor cortex in the volitional control of motor output, but
              how does the motor cortex exert this 'control'? Historically,
              ideas regarding motor cortex function have been shaped by the
              discovery of cortical 'motor maps' - that is, ordered
              representations of stimulation-evoked movements in anaesthetized
              animals. Volitional control, however, entails the initiation of
              movements and the ability to suppress undesired movements. In
              this article, we highlight classic and recent findings that
              emphasize that motor cortex neurons have a role in both
              processes.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  18,
  number   =  11,
  pages    = "694--705",
  month    =  oct,
  year     =  2017,
  language = "en"
}

@ARTICLE{Calton2009-hj,
  title    = "Where am {I} and how will {I} get there from here? A role for
              posterior parietal cortex in the integration of spatial
              information and route planning",
  author   = "Calton, Jeffrey L and Taube, Jeffrey S",
  abstract = "The ability of an organism to accurately navigate from one place
              to another requires integration of multiple spatial constructs,
              including the determination of one's position and direction in
              space relative to allocentric landmarks, movement velocity, and
              the perceived location of the goal of the movement. In this
              review, we propose that while limbic areas are important for the
              sense of spatial orientation, the posterior parietal cortex is
              responsible for relating this sense with the location of a
              navigational goal and in formulating a plan to attain it. Hence,
              the posterior parietal cortex is important for the computation of
              the correct trajectory or route to be followed while navigating.
              Prefrontal and motor areas are subsequently responsible for
              executing the planned movement. Using this theory, we are able to
              bridge the gap between the rodent and primate literatures by
              suggesting that the allocentric role of the rodent PPC is largely
              analogous to the egocentric role typically emphasized in
              primates, that is, the integration of spatial orientation with
              potential goals in the planning of goal-directed movements.",
  journal  = "Neurobiol. Learn. Mem.",
  volume   =  91,
  number   =  2,
  pages    = "186--196",
  month    =  feb,
  year     =  2009,
  keywords = "navigation;To Read",
  language = "en"
}

@ARTICLE{Cho2001-nw,
  title     = "Head direction, place, and movement correlates for cells in the
               rat retrosplenial cortex",
  author    = "Cho, J and Sharp, P E",
  abstract  = "The retrosplenial cortex is strongly connected with brain
               regions involved in spatial signaling. To test whether it also
               codes space, single cells were recorded while rats navigated in
               an open field. As in earlier work (L. L. Chen, L. H. Lin, C. A.
               Barnes, \& B. L. McNaughton, 1994; L. L. Chen, L. H. Lin, E. J.
               Green, C. A. Barnes, \& B. L. McNaughton, 1994), the authors
               found head direction cells with properties similar to those in
               other areas. These cells were slightly anticipatory. Another
               cell type fired to particular combinations of location,
               direction, and movement, which suggested that they may fire
               whenever the rat approaches a particular location, using a
               particular locomotor behavior. The remaining cells could not be
               clearly categorized but also showed a significant correlation
               with one or more of the spatial-movement variables examined. The
               fact that the retrosplenial cortex contains spatial and
               movement-related signals and is connected with the motor cortex
               suggests that it may play a role in path integration or
               navigational motor planning.",
  journal   = "Behav. Neurosci.",
  publisher = "psycnet.apa.org",
  volume    =  115,
  number    =  1,
  pages     = "3--25",
  month     =  feb,
  year      =  2001,
  keywords  = "navigation;To Read",
  language  = "en"
}

@ARTICLE{Li2015-tj,
  title    = "A motor cortex circuit for motor planning and movement",
  author   = "Li, Nuo and Chen, Tsai-Wen and Guo, Zengcai V and Gerfen, Charles
              R and Svoboda, Karel",
  abstract = "Activity in motor cortex predicts specific movements seconds
              before they occur, but how this preparatory activity relates to
              upcoming movements is obscure. We dissected the conversion of
              preparatory activity to movement within a structured motor cortex
              circuit. An anterior lateral region of the mouse cortex (a
              possible homologue of premotor cortex in primates) contains equal
              proportions of intermingled neurons predicting ipsi- or
              contralateral movements, yet unilateral inactivation of this
              cortical region during movement planning disrupts contralateral
              movements. Using cell-type-specific electrophysiology, cellular
              imaging and optogenetic perturbation, we show that layer 5
              neurons projecting within the cortex have unbiased laterality.
              Activity with a contralateral population bias arises specifically
              in layer 5 neurons projecting to the brainstem, and only late
              during movement planning. These results reveal the transformation
              of distributed preparatory activity into movement commands within
              hierarchically organized cortical circuits.",
  journal  = "Nature",
  volume   =  519,
  number   =  7541,
  pages    = "51--56",
  month    =  mar,
  year     =  2015,
  keywords = "To Read",
  language = "en"
}

@ARTICLE{McNaughton1994-hv,
  title    = "Cortical representation of motion during unrestrained spatial
              navigation in the rat",
  author   = "McNaughton, B L and Mizumori, S J and Barnes, C A and Leonard, B
              J and Marquis, M and Green, E J",
  abstract = "Neural activity related to unrestrained movement through space
              was studied in rat sensorimotor and posterior parietal cortices
              during performance of an eight-arm, radial maze task. Nearly half
              of the cells exhibited movement-related activity that
              discriminated among three basic modes of locomotion: left turns,
              right turns, and forward motion. Correlates ranged from strong
              excitation (relative to the still condition) to strong
              inhibition, and were distributed among the movement modes in a
              variety of different ways. For example, cells that discriminated
              between clockwise and counterclockwise turns did so with either
              antagonistic responses or simple excitation or inhibition. Others
              showed either excitation or inhibition relative to both turning
              and the still condition, and hence were selective for forward
              motion. Many cells exhibited somatosensory responsiveness;
              however, in agreement with findings of others, motion correlates
              could rarely be sensibly explained by the somatosensory response.
              Moreover, movement correlates sometimes varied considerably with
              spatial context. Some cells exhibited more complex motion
              correlates, such as an apparent dependence on the nature of the
              preceding movement. Irrespective of the specific sensory or motor
              determinants of cell activity, which varied considerably among
              cells, the posterior neocortex of the rat appears to generate a
              robust and redundant internal representation of body motion
              through space. Such a representation could be useful in
              constructing ``cognitive maps'' of the environment.",
  journal  = "Cereb. Cortex",
  volume   =  4,
  number   =  1,
  pages    = "27--39",
  month    =  jan,
  year     =  1994,
  keywords = "navigation",
  language = "en"
}

@ARTICLE{Kiehn2006-wi,
  title     = "Locomotor circuits in the mammalian spinal cord",
  author    = "Kiehn, Ole",
  abstract  = "Intrinsic spinal networks, known as central pattern generators
               (CPGs), control the timing and pattern of the muscle activity
               underlying locomotion in mammals. This review discusses new
               advances in understanding the mammalian CPGs with a focus on
               experiments that address the overall network structure as well
               as the identification of CPG neurons. I address the
               identification of excitatory CPG neurons and their role in
               rhythm generation, the organization of flexor-extensor networks,
               and the diverse role of commissural interneurons in coordinating
               left-right movements. Molecular and genetic approaches that have
               the potential to elucidate the function of populations of CPG
               interneurons are also discussed.",
  journal   = "Annu. Rev. Neurosci.",
  publisher = "annualreviews.org",
  volume    =  29,
  pages     = "279--306",
  year      =  2006,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Fukuoka2015-ks,
  title    = "A simple rule for quadrupedal gait generation determined by leg
              loading feedback: a modeling study",
  author   = "Fukuoka, Yasuhiro and Habu, Yasushi and Fukui, Takahiro",
  abstract = "We discovered a specific rule for generating typical quadrupedal
              gaits (the order of the movement of four legs) through a
              simulated quadrupedal locomotion, in which unprogrammed gaits
              (diagonal/lateral sequence walks, left/right-lead canters, and
              left/right-lead transverse gallops) spontaneously emerged because
              of leg loading feedbacks to the CPGs hard-wired to produce a
              default trot. Additionally, all gaits transitioned according to
              speed, as seen in animals. We have therefore hypothesized that
              various gaits derive from a trot because of posture control
              through leg loading feedback. The body tilt on the two support
              legs of each diagonal pair during trotting was classified into
              three types (level, tilted up, or tilted down) according to
              speed. The load difference between the two legs led to the phase
              difference between their CPGs via the loading feedbacks,
              resulting in nine gaits (3(2): three tilts to the power of two
              diagonal pairs) including the aforementioned.",
  journal  = "Sci. Rep.",
  volume   =  5,
  pages    = "8169",
  month    =  feb,
  year     =  2015,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Inagaki_undated-th,
  title    = "A midbrain - thalamus - cortex circuit reorganizes cortical
              dynamics to initiate planned movement",
  author   = "Inagaki, Hidehiko K and Chen, Susu and Ridder, Margreet C and
              Sah, Pankaj and Li, Nuo and Yang, Zidan and Hasanbegovic, Hana
              and Gao, Zhenyu and Gerfen, Charles R and Svoboda, Karel",
  keywords = "To Read"
}

@UNPUBLISHED{Roseberry2019-iz,
  title    = "Locomotor suppression by a monosynaptic amygdala to brainstem
              circuit",
  author   = "Roseberry, Thomas K and Lalive, Arnaud L and Margolin, Benjamin D
              and Kreitzer, Anatol C",
  abstract = "Abstract The control of locomotion is fundamental to vertebrate
              animal survival. Defensive situations require an animal to
              rapidly decide whether to run away or suppress locomotor activity
              to avoid detection. While much of the neural circuitry involved
              in defensive action selection has been elucidated, top-down
              modulation of brainstem locomotor circuitry remains unclear. Here
              we provide evidence for the existence and functionality of a
              monosynaptic connection from the central amygdala (CeA) to the
              mesencephalic locomotor region (MLR) that inhibits locomotion in
              unconditioned and conditioned defensive behavior in mice. We show
              that locomotion stimulated by airpuff coincides with increased
              activity of MLR glutamatergic neurons. Using retrograde tracing
              and ex vivo electrophysiology, we find that the CeA makes a
              monosynaptic connection with the MLR. In the open field, in vivo
              stimulation of this projection suppressed spontaneous locomotion,
              whereas inhibition of this projection had no effect. However,
              inhibiting CeA terminals within the MLR increased both neural
              activity and locomotor responses to airpuff. Finally, using a
              conditioned avoidance paradigm known to activate CeA neurons, we
              find that inhibition of the CeA projection increased successful
              escape, whereas activating the projection reduced escape.
              Together these results provide evidence for a new circuit
              substrate influencing locomotion and defensive behaviors.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "724252",
  month    =  aug,
  year     =  2019,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Carvalho2020-pw,
  title    = "A Brainstem Locomotor Circuit Drives the Activity of Speed Cells
              in the Medial Entorhinal Cortex",
  author   = "Carvalho, Miguel M and Tanke, Nouk and Kropff, Emilio and Witter,
              Menno P and Moser, May-Britt and Moser, Edvard I",
  abstract = "Locomotion activates an array of sensory inputs that may help
              build the self-position map of the medial entorhinal cortex
              (MEC). In this map, speed-coding neurons are thought to
              dynamically update representations of the animal's position. A
              possible origin for the entorhinal speed signal is the
              mesencephalic locomotor region (MLR), which is critically
              involved in the activation of locomotor programs. Here, we
              describe, in rats, a circuit connecting the pedunculopontine
              tegmental nucleus (PPN) of the MLR to the MEC via the horizontal
              limb of the diagonal band of Broca (HDB). At each level of this
              pathway, locomotion speed is linearly encoded in neuronal firing
              rates. Optogenetic activation of PPN cells drives locomotion and
              modulates activity of speed-modulated neurons in HDB and MEC. Our
              results provide evidence for a pathway by which brainstem speed
              signals can reach cortical structures implicated in navigation
              and higher-order dynamic representations of space.",
  journal  = "Cell Rep.",
  volume   =  32,
  number   =  10,
  pages    = "108123",
  month    =  sep,
  year     =  2020,
  keywords = "diagonal band of Broca; medial entorhinal cortex; mesencephalic
              locomotor region; pedunculopontine tegmental nucleus; speed
              cells;Locomotion",
  language = "en"
}

@UNPUBLISHED{Dautan2020-lv,
  title    = "Modulation of motor behavior by the mesencephalic locomotor
              region",
  author   = "Dautan, Daniel and Kov{\'a}cs, Adrienn and Bayasgalan,
              Tsogbadrakh and Diaz-Acevedo, Miguel A and Pal, Balazs and
              Mena-Segovia, Juan",
  abstract = "The mesencephalic locomotor region (MLR) serves as an interface
              between higher-order motor systems and lower motor neurons. The
              excitatory module of the MLR is composed of the pedunculopontine
              nucleus (PPN) and the cuneiform nucleus (CnF), and their
              activation has been proposed to elicit different modalities of
              movement, but how the differences in connectivity and
              physiological properties explain their contributions to motor
              activity is not known. Here we report that CnF glutamatergic
              neurons are electrophysiologically homogeneous and have
              short-range axonal projections, whereas PPN glutamatergic neurons
              are heterogeneous and maintain long-range connections, most
              notably with the basal ganglia. Optogenetic activation of CnF
              neurons produced fast-onset, involuntary motor activity mediated
              by short-lasting muscle activation. In contrast, activation of
              PPN neurons produced long-lasting increases in muscle tone that
              reduced motor activity and disrupted gait. Our results thus
              reveal a differential contribution to motor behavior by the
              structures that compose the MLR. \#\#\# Competing Interest
              Statement The authors have declared no competing interest.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.06.25.172296",
  month    =  jun,
  year     =  2020,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Ruder2016-iv,
  title     = "{Long-Distance} Descending Spinal Neurons Ensure Quadrupedal
               Locomotor Stability",
  author    = "Ruder, Ludwig and Takeoka, Aya and Arber, Silvia",
  abstract  = "Locomotion is an essential animal behavior used for
               translocation. The spinal cord acts as key executing center, but
               how it coordinates many body parts located across distance
               remains poorly understood. Here we employed mouse genetic and
               viral approaches to reveal organizational principles of
               long-projecting spinal circuits and their role in quadrupedal
               locomotion. Using neurotransmitter identity, developmental
               origin, and projection patterns as criteria, we uncover that
               spinal segments controlling forelimbs and hindlimbs are
               bidirectionally connected by symmetrically organized direct
               synaptic pathways that encompass multiple genetically tractable
               neuronal subpopulations. We demonstrate that selective ablation
               of descending spinal neurons linking cervical to lumbar segments
               impairs coherent locomotion, by reducing postural stability and
               speed during exploratory locomotion, as well as perturbing
               interlimb coordination during reinforced high-speed stepping.
               Together, our results implicate a highly organized long-distance
               projection system of spinal origin in the control of postural
               body stabilization and reliability during quadrupedal
               locomotion.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  92,
  number    =  5,
  pages     = "1063--1078",
  month     =  dec,
  year      =  2016,
  keywords  = "genetic identity; interlimb coordination; locomotion; motor
               control; posture; spinal cord;Locomotion",
  language  = "en"
}

@ARTICLE{Drew2015-sv,
  title     = "Taking the next step: cortical contributions to the control of
               locomotion",
  author    = "Drew, Trevor and Marigold, Daniel S",
  abstract  = "The planning and execution of both discrete voluntary movements
               and visually guided locomotion depends on the contribution of
               multiple cortical areas. In this review, we discuss recent
               experiments that address the contribution of the posterior
               parietal cortex (PPC) and the motor cortex to the control of
               locomotion. The results from these experiments show that the PPC
               contributes to the planning of locomotion by providing an
               estimate of the position of an animal with respect to objects in
               its path. In contrast, the motor cortex contributes primarily to
               the execution of gait modifications by modulating the activity
               of groups of synergistic muscles active at different times
               during the gait cycle.",
  journal   = "Curr. Opin. Neurobiol.",
  publisher = "Elsevier",
  volume    =  33,
  pages     = "25--33",
  month     =  aug,
  year      =  2015,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Ueno2011-tt,
  title     = "Kinematic analyses reveal impaired locomotion following injury
               of the motor cortex in mice",
  author    = "Ueno, Masaki and Yamashita, Toshihide",
  abstract  = "Brain injury in the motor cortex can result in deleterious
               functional deficits of skilled and fine motor functions.
               However, in contrast to humans, the destruction of cortex and
               its descending fibers has been thought not to cause remarkable
               deficits in simple locomotion in quadropedal animals. In the
               present study, we aimed to investigate in detail how lesion of
               the sensorimotor cortex affected locomotion ability in mice
               using the KinemaTracer system, a novel video-based kinematic
               analyzer. We found that traumatic injury to the left
               sensorimotor cortex induced several apparent deficits in the
               movement of contralesional right limbs during treadmill
               locomotion. The step length of right limbs decreased, and the
               speed in the forward direction was abrogated in the swing phase.
               The coordinates and angle of each joint were also changed after
               the injury. Some of the abnormal values in these parameters
               gradually recovered near the control level. The number of
               cFos-expressing neurons following locomotion significantly
               decreased in the right side of the spinal cord in injured mice,
               suggesting a role for cortex and descending fibers in
               locomotion. In contrast, interlimb coordination did not change
               remarkably even after the injury, supporting the notion that the
               basic locomotor pattern was determined by intraspinal neural
               circuits. These results indicate that the motor cortex and its
               descending fibers regulate several aspects of fine limb movement
               during locomotion. Our findings provide practical parameters to
               assess motor deficits and recovery following cortical injury in
               mice.",
  journal   = "Exp. Neurol.",
  publisher = "Elsevier",
  volume    =  230,
  number    =  2,
  pages     = "280--290",
  month     =  aug,
  year      =  2011,
  keywords  = "Locomotion;To Read",
  language  = "en"
}

@ARTICLE{Holmes2006-fn,
  title     = "The Dynamics of Legged Locomotion: Models, Analyses, and
               Challenges",
  author    = "Holmes, Philip and Full, Robert J and Koditschek, Dan and
               Guckenheimer, John",
  abstract  = "Cheetahs and beetles run, dolphins and salmon swim, and bees and
               birds fly with grace and economy surpassing our technology.
               Evolution has shaped the breathtaking abilities of animals,
               leaving us the challenge of reconstructing their targets of
               control and mechanisms of dexterity. In this review we explore a
               corner of this fascinating world. We describe mathematical
               models for legged animal locomotion, focusing on rapidly running
               insects and highlighting past achievements and challenges that
               remain. Newtonian body--limb dynamics are most naturally
               formulated as piecewise-holonomic rigid body mechanical systems,
               whose constraints change as legs touch down or lift off. Central
               pattern generators and proprioceptive sensing require models of
               spiking neurons and simplified phase oscillator descriptions of
               ensembles of them. A full neuromechanical model of a running
               animal requires integration of these elements, along with
               proprioceptive feedback and models of goal-oriented sensing,
               planning, and learning. We outline relevant background material
               from biomechanics and neurobiology, explain key properties of
               the hybrid dynamical systems that underlie legged locomotion
               models, and provide numerous examples of such models, from the
               simplest, completely soluble ``peg-leg walker'' to complex
               neuromuscular subsystems that are yet to be assembled into
               models of behaving animals. This final integration in a
               tractable and illuminating model is an outstanding challenge.",
  journal   = "SIAM Rev.",
  publisher = "Society for Industrial and Applied Mathematics",
  volume    =  48,
  number    =  2,
  pages     = "207--304",
  month     =  jan,
  year      =  2006,
  keywords  = "Locomotion;To Read"
}

@ARTICLE{Schwenkgrub2020-yl,
  title     = "Deep imaging in the brainstem reveals functional heterogeneity
               in V2a neurons controlling locomotion",
  author    = "Schwenkgrub, Joanna and Harrell, Evan R and Bathellier, Brice
               and Bouvier, Julien",
  abstract  = "V2a neurons are a genetically defined cell class that forms a
               major excitatory descending pathway from the brainstem reticular
               formation to the spinal cord. Their activation has been linked
               to the termination of locomotor activity based on broad
               optogenetic manipulations. However, because of the difficulties
               involved in accessing brainstem structures for in vivo cell
               type-specific recordings, V2a neuron function has never been
               directly observed during natural behaviors. Here, we imaged the
               activity of V2a neurons using micro-endoscopy in freely moving
               mice. We find that as many as half of the V2a neurons are
               excited at locomotion arrest and with low reliability. Other V2a
               neurons are inhibited at locomotor arrests and/or activated
               during other behaviors such as locomotion initiation or
               stationary grooming. Our results establish that V2a neurons not
               only drive stops as suggested by bulk optogenetics but also are
               stratified into subpopulations that likely contribute to diverse
               motor patterns.",
  journal   = "Sci Adv",
  publisher = "advances.sciencemag.org",
  volume    =  6,
  number    =  49,
  month     =  dec,
  year      =  2020,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Lemieux2019-yc,
  title     = "Glutamatergic neurons of the gigantocellular reticular nucleus
               shape locomotor pattern and rhythm in the freely behaving mouse",
  author    = "Lemieux, Maxime and Bretzner, Frederic",
  abstract  = "Because of their intermediate position between supraspinal
               locomotor centers and spinal circuits, gigantocellular reticular
               nucleus (GRN) neurons play a key role in motor command. However,
               the functional contribution of glutamatergic GRN neurons in
               initiating, maintaining, and stopping locomotion is still
               unclear. Combining electromyographic recordings with optogenetic
               manipulations in freely behaving mice, we investigate the
               functional contribution of glutamatergic brainstem neurons of
               the GRN to motor and locomotor activity. Short-pulse
               photostimulation of one side of the glutamatergic GRN did not
               elicit locomotion but evoked distinct motor responses in flexor
               and extensor muscles at rest and during locomotion.
               Glutamatergic GRN outputs to the spinal cord appear to be gated
               according to the spinal locomotor network state. Increasing the
               duration of photostimulation increased motor and postural tone
               at rest and reset locomotor rhythm during ongoing locomotion. In
               contrast, photoinhibition impaired locomotor pattern and rhythm.
               We conclude that unilateral activation of glutamatergic GRN
               neurons triggered motor activity and modified ongoing locomotor
               pattern and rhythm.",
  journal   = "PLoS Biol.",
  publisher = "journals.plos.org",
  volume    =  17,
  number    =  4,
  pages     = "e2003880",
  month     =  apr,
  year      =  2019,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Karadimas2020-ub,
  title     = "Sensory cortical control of movement",
  author    = "Karadimas, Spyridon K and Satkunendrarajah, Kajana and
               Laliberte, Alex M and Ringuette, Dene and Weisspapir, Iliya and
               Li, Lijun and Gosgnach, Simon and Fehlings, Michael G",
  abstract  = "Walking in our complex environment requires continual higher
               order integrated spatiotemporal information. This information is
               processed in the somatosensory cortex, and it has long been
               presumed that it influences movement via descending tracts
               originating from the motor cortex. Here we show that neuronal
               activity in the primary somatosensory cortex tightly correlates
               with the onset and speed of locomotion in freely moving mice.
               Using optogenetics and pharmacogenetics in combination with in
               vivo and in vitro electrophysiology, we provide evidence for a
               direct corticospinal pathway from the primary somatosensory
               cortex that synapses with cervical excitatory neurons and
               modulates the lumbar locomotor network independently of the
               motor cortex and other supraspinal locomotor centers.
               Stimulation of this pathway enhances speed of locomotion, while
               inhibition decreases locomotor speed and ultimately terminates
               stepping. Our findings reveal a novel pathway for neural control
               of movement whereby the somatosensory cortex directly influences
               motor behavior, possibly in response to environmental cues.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  23,
  number    =  1,
  pages     = "75--84",
  month     =  jan,
  year      =  2020,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Bouvier2015-nm,
  title    = "Descending Command Neurons in the Brainstem that Halt Locomotion",
  author   = "Bouvier, Julien and Caggiano, Vittorio and Leiras, Roberto and
              Caldeira, Vanessa and Bellardita, Carmelo and Balueva, Kira and
              Fuchs, Andrea and Kiehn, Ole",
  abstract = "The episodic nature of locomotion is thought to be controlled by
              descending inputs from the brainstem. Most studies have largely
              attributed this control to initiating excitatory signals, but
              little is known about putative commands that may specifically
              determine locomotor offset. To link identifiable brainstem
              populations to a potential locomotor stop signal, we used
              developmental genetics and considered a discrete neuronal
              population in the reticular formation: the V2a neurons. We find
              that those neurons constitute a major excitatory pathway to
              locomotor areas of the ventral spinal cord. Selective activation
              of V2a neurons of the rostral medulla stops ongoing locomotor
              activity, owing to an inhibition of premotor locomotor networks
              in the spinal cord. Moreover, inactivation of such neurons
              decreases spontaneous stopping in vivo. Therefore, the V2a ``stop
              neurons'' represent a glutamatergic descending pathway that
              favors immobility and may thus help control the episodic nature
              of locomotion.",
  journal  = "Cell",
  volume   =  163,
  number   =  5,
  pages    = "1191--1203",
  month    =  nov,
  year     =  2015,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Caggiano2018-td,
  title    = "Midbrain circuits that set locomotor speed and gait selection",
  author   = "Caggiano, V and Leiras, R and Go{\~n}i-Erro, H and Masini, D and
              Bellardita, C and Bouvier, J and Caldeira, V and Fisone, G and
              Kiehn, O",
  abstract = "Locomotion is a fundamental motor function common to the animal
              kingdom. It is implemented episodically and adapted to
              behavioural needs, including exploration, which requires slow
              locomotion, and escape behaviour, which necessitates faster
              speeds. The control of these functions originates in brainstem
              structures, although the neuronal substrate(s) that support them
              have not yet been elucidated. Here we show in mice that speed and
              gait selection are controlled by glutamatergic excitatory neurons
              (GlutNs) segregated in two distinct midbrain nuclei: the
              cuneiform nucleus (CnF) and the pedunculopontine nucleus (PPN).
              GlutNs in both of these regions contribute to the control of
              slower, alternating-gait locomotion, whereas only GlutNs in the
              CnF are able to elicit high-speed, synchronous-gait locomotion.
              Additionally, both the activation dynamics and the input and
              output connectivity matrices of GlutNs in the PPN and the CnF
              support explorative and escape locomotion, respectively. Our
              results identify two regions in the midbrain that act in
              conjunction to select context-dependent locomotor behaviours.",
  journal  = "Nature",
  volume   =  553,
  number   =  7689,
  pages    = "455--460",
  month    =  jan,
  year     =  2018,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Usseglio2020-nl,
  title    = "Control of Orienting Movements and Locomotion by
              {Projection-Defined} Subsets of Brainstem V2a Neurons",
  author   = "Usseglio, Giovanni and Gatier, Edwin and Heuz{\'e}, Aur{\'e}lie
              and H{\'e}rent, Coralie and Bouvier, Julien",
  abstract = "Spatial orientation requires the execution of lateralized
              movements and a change in the animal's heading in response to
              multiple sensory modalities. While much research has focused on
              the circuits for sensory integration, chiefly to the midbrain
              superior colliculus (SC), the downstream cells and circuits that
              engage adequate motor actions have remained elusive. Furthermore,
              the mechanisms supporting trajectory changes are still
              speculative. Here, using transneuronal viral tracings in mice, we
              show that brainstem V2a neurons, a genetically defined subtype of
              glutamatergic neurons of the reticular formation, receive
              putative synaptic inputs from the contralateral SC. This makes
              them a candidate relay of lateralized orienting commands. We next
              show that unilateral optogenetic activations of brainstem V2a
              neurons in vivo evoked ipsilateral orienting-like responses of
              the head and the nose tip on stationary mice. When animals are
              walking, similar stimulations impose a transient locomotor arrest
              followed by a change of trajectory. Third, we reveal that these
              distinct motor actions are controlled by dedicated V2a subsets
              each projecting to a specific spinal cord segment, with at least
              (1) a lumbar-projecting subset whose unilateral activation
              specifically controls locomotor speed but neither impacts
              trajectory nor evokes orienting movements, and (2) a
              cervical-projecting subset dedicated to head orientation, but not
              to locomotor speed. Activating the latter subset suffices to
              steer the animals' directional heading, placing the head
              orientation as the prime driver of locomotor trajectory. V2a
              neurons and their modular organization may therefore underlie the
              orchestration of multiple motor actions during multi-faceted
              orienting behaviors.",
  journal  = "Curr. Biol.",
  volume   =  30,
  number   =  23,
  pages    = "4665--4681.e6",
  month    =  dec,
  year     =  2020,
  keywords = "V2a neurons; brainstem; circuit tracings; locomotion; motor
              control; mouse; optogenetics; orientation; reticulospinal
              neurons; spinal cord;Locomotion",
  language = "en"
}

@ARTICLE{Taylor1982-pi,
  title     = "Energetics and mechanics of terrestrial locomotion. I. Metabolic
               energy consumption as a function of speed and body size in birds
               and mammals",
  author    = "Taylor, C R and Heglund, N C and Maloiy, G M",
  abstract  = "This series of four papers investigates the link between the
               energetics and the mechanics of terrestrial locomotion. Two
               experimental variables are used throughout the study: speed and
               body size. Mass-specific metabolic rates of running animals can
               be varied by about tenfold using either variable. This first
               paper considers metabolic energy consumed during terrestrial
               locomotion. New data relating rate of oxygen consumption and
               speed are reported for: eight species of wild and domestic
               artiodactyls; seven species of carnivores; four species of
               primates; and one species of rodent. These are combined with
               previously published data to formulate a new allometric equation
               relating mass-specific rates of oxygen consumed (VO2/Mb) during
               locomotion at a constant speed to speed and body mass (based on
               data from 62 avian and mammalian species): VO2/Mb = 0.533
               Mb-0.316.vg + 0.300 Mb-0.303 where VO2/Mb has the units ml O2
               s-1 kg-1; Mb is in kg; and vg is in m s-1. This equation can be
               expressed in terms of mass-specific rates of energy consumption
               (Emetab/Mb) using the energetic equivalent of 1 ml O2 = 20.1 J
               because the contribution of anaerobic glycolysis was negligible:
               Emetab/Mb = 10.7 Mb-0.316.vg + 6.03 Mb-0.303 where Emetab/Mb has
               the units watts/kg. This new relationship applies equally well
               to bipeds and quadrupeds and differs little from the allometric
               equation reported 12 years ago by Taylor, Schmid-Nielsen \& Raab
               (1970). Ninety per cent of the values calculated from this
               genera equation for the diverse assortment of avian and
               mammalian species included in this regression fall within 25\%
               of the observed values at the middle of the speed range where
               measurements were made. This agreement is impressive when one
               considers that mass-specific rates of oxygen consumption
               differed by more than 1400\% over this size range of animals.",
  journal   = "J. Exp. Biol.",
  publisher = "jeb.biologists.org",
  volume    =  97,
  pages     = "1--21",
  month     =  apr,
  year      =  1982,
  keywords  = "Locomotion",
  language  = "en"
}

@INCOLLECTION{Matsuyama2004-fv,
  title     = "Locomotor role of the corticoreticular--reticulospinal--spinal
               interneuronal system",
  booktitle = "Progress in Brain Research",
  author    = "Matsuyama, Kiyoji and Mori, Futoshi and Nakajima, Katsumi and
               Drew, Trevor and Aoki, Mamoru and Mori, Shigemi",
  abstract  = "In vertebrates, the descending reticulospinal pathway is the
               primary means of conveying locomotor command signals from higher
               motor centers to spinal interneuronal circuits, the latter
               including the central pattern generators for locomotion. The
               pathway is morphologically heterogeneous, being composed of
               various types of in-parallel-descending axons, which terminate
               with different arborization patterns in the spinal cord. Such
               morphology suggests that this pathway and its target spinal
               interneurons comprise varying types of functional subunits,
               which have a wide variety of functional roles, as dictated by
               command signals from the higher motor centers. Corticoreticular
               fibers are one of the major output pathways from the motor
               cortex to the brainstem. They project widely and diffusely
               within the pontomedullary reticular formation. Such a diffuse
               projection pattern seems well suited to combining and
               integrating the function of the various types of reticulospinal
               neurons, which are widely scattered throughout the
               pontomedullary reticular formation. The
               corticoreticular--reticulospinal--spinal interneuronal
               connections appear to operate as a cohesive, yet flexible,
               control system for the elaboration of a wide variety of
               movements, including those that combine goal-directed locomotion
               with other motor actions.",
  publisher = "Elsevier",
  volume    =  143,
  pages     = "239--249",
  month     =  jan,
  year      =  2004,
  keywords  = "Locomotion"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@INCOLLECTION{Velagic2008-nb,
  title     = "Nonlinear motion control of mobile robot dynamic model",
  booktitle = "Motion planning",
  author    = "Velagic, Jasmin and Lacevic, Bakir and Osmic, Nedim",
  abstract  = "The problem of motion planning and control of mobile robots has
               attracted the interest of researchers in view of its theoretical
               challenges because of their obvious relevance in applications.
               From a control viewpoint, the peculiar nature of nonholonomic
               kinematics and dynamic complexity of the mobile robot makes that
               feedback stabilization at a given posture cannot be achieved via
               smooth time-invariant control (Oriolo et al., 2002). This
               indicates that the problem is truly nonlinear; linear control is
               ineffective, and innovative design techniques …",
  publisher = "IntechOpen",
  year      =  2008,
  keywords  = "control"
}

@UNPUBLISHED{Kao2020-dl,
  title    = "Optimal anticipatory control as a theory of motor preparation: a
              thalamo-cortical circuit model",
  author   = "Kao, Ta-Chu and Sadabadi, Mahdieh S and Hennequin, Guillaume",
  abstract = "Summary Across a range of motor and cognitive tasks, cortical
              activity can be accurately described by low-dimensional dynamics
              unfolding from specific initial conditions on every trial. These
              ``preparatory states'' largely determine the subsequent evolution
              of both neural activity and behaviour, and their importance
              raises questions regarding how they are --- or ought to be ---
              set. Here, we formulate motor preparation as optimal prospective
              control of future movements. The solution is a form of internal
              control of cortical circuit dynamics, which can be implemented as
              a thalamo-cortical loop gated by the basal ganglia. Critically,
              optimal control predicts selective quenching of variability in
              components of preparatory population activity that have future
              motor consequences, but not in others. This is consistent with
              recent perturbation experiments performed in mice, and with our
              novel analysis of monkey motor cortex activity during reaching.
              Together, these results suggest optimal anticipatory control of
              movement.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.02.02.931246",
  month    =  feb,
  year     =  2020,
  keywords = "control",
  language = "en"
}

@ARTICLE{Marshall2020-rp,
  title    = "Continuous {Whole-Body} {3D} Kinematic Recordings across the
              Rodent Behavioral Repertoire",
  author   = "Marshall, Jesse D and Aldarondo, Diego E and Dunn, Timothy W and
              Wang, William L and Berman, Gordon J and {\"O}lveczky, Bence P",
  abstract = "In mammalian animal models, high-resolution kinematic tracking is
              restricted to brief sessions in constrained environments,
              limiting our ability to probe naturalistic behaviors and their
              neural underpinnings. To address this, we developed CAPTURE
              (Continuous Appendicular and Postural Tracking Using
              Retroreflector Embedding), a behavioral monitoring system that
              combines motion capture and deep learning to continuously track
              the 3D kinematics of a rat's head, trunk, and limbs for week-long
              timescales in freely behaving animals. CAPTURE realizes 10- to
              100-fold gains in precision and robustness compared with existing
              convolutional network approaches to behavioral tracking. We
              demonstrate CAPTURE's ability to comprehensively profile the
              kinematics and sequential organization of natural rodent
              behavior, its variation across individuals, and its perturbation
              by drugs and disease, including identifying perseverative
              grooming states in a rat model of fragile X syndrome. CAPTURE
              significantly expands the range of behaviors and contexts that
              can be quantitatively investigated, opening the door to a new
              understanding of natural behavior and its neural basis.",
  journal  = "Neuron",
  month    =  dec,
  year     =  2020,
  keywords = "animal tracking; autism; behavior; computational ethology;
              grooming; individuality; motion capture; phenotyping",
  language = "en"
}

@ARTICLE{Simmons2009-ax,
  title     = "Comparing histological data from different brains: sources of
               error and strategies for minimizing them",
  author    = "Simmons, Donna M and Swanson, Larry W",
  abstract  = "The recent development of brain atlases with computer graphics
               templates, and of huge databases of neurohistochemical data on
               the internet, has forced a systematic re-examination of errors
               associated with comparing histological features between adjacent
               sections of the same brain, between brains treated in the same
               way, and between brains from groups treated in different ways.
               The long-term goal is to compare as accurately as possible a
               broad array of data from experimental brains within the
               framework of reference atlases. Main sources of error, each of
               which ideally should be measured and minimized, include
               intrinsic biological variation, linear and nonlinear distortion
               of histological sections, plane of section differences between
               each brain, section alignment problems, and sampling errors.
               These variables are discussed, along with approaches to error
               estimation and minimization in terms of a specific example-the
               distribution of neuroendocrine neurons in the rat
               paraventricular nucleus. Based on the strategy developed here,
               the main conclusion is that the best long-term solution is a
               high-resolution 3D computer graphics model of the brain that can
               be sliced in any plane and used as the framework for
               quantitative neuroanatomy, databases, knowledge management
               systems, and structure-function modeling. However, any approach
               to the automatic annotation of neuroanatomical data-relating its
               spatial distribution to a reference atlas-should deal
               systematically with these sources of error, which reduce
               localization reliability.",
  journal   = "Brain Res. Rev.",
  publisher = "Elsevier",
  volume    =  60,
  number    =  2,
  pages     = "349--367",
  month     =  may,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Hahn2020-rj,
  title     = "An open access mouse brain flatmap and upgraded rat and human
               brain flatmaps based on current reference atlases",
  author    = "Hahn, Joel D and Swanson, Larry W and Bowman, Ian and Foster,
               Nicholas N and Zingg, Brian and Bienkowski, Michael S and
               Hintiryan, Houri and Dong, Hong-Wei",
  abstract  = "Here we present a flatmap of the mouse central nervous system
               (CNS) (brain) and substantially enhanced flatmaps of the rat and
               human brain. Also included are enhanced representations of
               nervous system white matter tracts, ganglia, and nerves, and an
               enhanced series of 10 flatmaps showing different stages of rat
               brain development. The adult mouse and rat brain flatmaps
               provide layered diagrammatic representation of CNS divisions,
               according to their arrangement in corresponding reference
               atlases: Brain Maps 4.0 (BM4, rat) (Swanson, The Journal of
               Comparative Neurology, 2018, 526, 935-943), and the first
               version of the Allen Reference Atlas (mouse) (Dong, The Allen
               reference atlas, (book + CD-ROM): A digital color brain atlas of
               the C57BL/6J male mouse, 2007). To facilitate comparative
               analysis, both flatmaps are scaled equally, and the divisional
               hierarchy of gray matter follows a topographic arrangement used
               in BM4. Also included with the mouse and rat brain flatmaps are
               cerebral cortex atlas level contours based on the reference
               atlases, and direct graphical and tabular comparison of regional
               parcellation. To encourage use of the brain flatmaps, they were
               designed and organized, with supporting reference tables, for
               ease-of-use and to be amenable to computational applications. We
               demonstrate how they can be adapted to represent novel
               parcellations resulting from experimental data, and we provide a
               proof-of-concept for how they could form the basis of a
               web-based graphical data viewer and analysis platform. The
               mouse, rat, and human brain flatmap vector graphics files (Adobe
               Reader/Acrobat viewable and Adobe Illustrator editable) and
               supporting tables are provided open access; they constitute a
               broadly applicable neuroscience toolbox resource for researchers
               seeking to map and perform comparative analysis of brain data.",
  journal   = "J. Comp. Neurol.",
  publisher = "Wiley",
  number    = "cne.24966",
  month     =  jun,
  year      =  2020,
  keywords  = "brain atlases; brain flatmap; brain mapping; computer graphics;
               human; mouse; rat",
  copyright = "http://onlinelibrary.wiley.com/termsAndConditions\#vor",
  language  = "en"
}

@ARTICLE{Maheswaranathan2020-fy,
  title         = "How recurrent networks implement contextual processing in
                   sentiment analysis",
  author        = "Maheswaranathan, Niru and Sussillo, David",
  abstract      = "Neural networks have a remarkable capacity for contextual
                   processing--using recent or nearby inputs to modify
                   processing of current input. For example, in natural
                   language, contextual processing is necessary to correctly
                   interpret negation (e.g. phrases such as ``not bad'').
                   However, our ability to understand how networks process
                   context is limited. Here, we propose general methods for
                   reverse engineering recurrent neural networks (RNNs) to
                   identify and elucidate contextual processing. We apply these
                   methods to understand RNNs trained on sentiment
                   classification. This analysis reveals inputs that induce
                   contextual effects, quantifies the strength and timescale of
                   these effects, and identifies sets of these inputs with
                   similar properties. Additionally, we analyze contextual
                   effects related to differential processing of the beginning
                   and end of documents. Using the insights learned from the
                   RNNs we improve baseline Bag-of-Words models with simple
                   extensions that incorporate contextual modification,
                   recovering greater than 90\% of the RNN's performance
                   increase over the baseline. This work yields a new
                   understanding of how RNNs process contextual information,
                   and provides tools that should provide similar insight more
                   broadly.",
  month         =  apr,
  year          =  2020,
  keywords      = "RNN;RNN To read",
  archivePrefix = "arXiv",
  primaryClass  = "cs.CL",
  eprint        = "2004.08013"
}

@ARTICLE{Madhav2020-qs,
  title     = "The Synergy Between Neuroscience and Control Theory: The Nervous
               System as Inspiration for Hard Control Challenges",
  author    = "Madhav, Manu S and Cowan, Noah J",
  abstract  = "Here, we review the role of control theory in modeling neural
               control systems through a top-down analysis approach.
               Specifically, we examine the role of the brain and central
               nervous system as the controller in the organism, connected to
               but isolated from the rest of the animal through insulated
               interfaces. Though biological and engineering control systems
               operate on similar principles, they differ in several critical
               features, which makes drawing inspiration from biology for
               engineering controllers challenging but worthwhile. We also
               outline a procedure that the control theorist can use to draw
               inspiration from the biological controller: starting from the
               intact, behaving animal; designing experiments to deconstruct
               and model hierarchies of feedback; modifying feedback
               topologies; perturbing inputs and plant dynamics; using the
               resultant outputs to perform system identification; and tuning
               and validating the resultant control-theoretic model using
               specially engineered robophysical models.",
  journal   = "Annu. Rev. Control Robot. Auton. Syst.",
  publisher = "Annual Reviews",
  volume    =  3,
  number    =  1,
  pages     = "243--267",
  month     =  may,
  year      =  2020
}

@ARTICLE{Fieseler2020-ne,
  title         = "Unsupervised learning of control signals and their encodings
                   in $\textit{C. elegans}$ whole-brain recordings",
  author        = "Fieseler, Charles and Zimmer, Manuel and Nathan Kutz, J",
  abstract      = "Recent whole brain imaging experiments on $\textit\{C.
                   elegans\}$ has revealed that the neural population dynamics
                   encode motor commands and stereotyped transitions between
                   behaviors on low dimensional manifolds. Efforts to
                   characterize the dynamics on this manifold have used
                   piecewise linear models to describe the entire state space,
                   but it is unknown how a single, global dynamical model can
                   generate the observed dynamics. Here, we propose a control
                   framework to achieve such a global model of the dynamics,
                   whereby underlying linear dynamics is actuated by sparse
                   control signals. This method learns the control signals in
                   an unsupervised way from data, then uses $\textit\{ Dynamic
                   Mode Decomposition with control\}$ (DMDc) to create the
                   first global, linear dynamical system that can reconstruct
                   whole-brain imaging data. These control signals are shown to
                   be implicated in transitions between behaviors. In addition,
                   we analyze the time-delay encoding of these control signals,
                   showing that these transitions can be predicted from neurons
                   previously implicated in behavioral transitions, but also
                   additional neurons previously unidentified. Moreover, our
                   decomposition method allows one to understand the observed
                   nonlinear global dynamics instead as linear dynamics with
                   control. The proposed mathematical framework is generic and
                   can be generalized to other neurosensory systems,
                   potentially revealing transitions and their encodings in a
                   completely unsupervised way.",
  month         =  jan,
  year          =  2020,
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.QM",
  eprint        = "2001.08346"
}

@ARTICLE{Jude2020-mq,
  title         = "Hippocampal representations emerge when training recurrent
                   neural networks on a memory dependent maze navigation task",
  author        = "Jude, Justin and Hennig, Matthias H",
  abstract      = "Can neural networks learn goal-directed behaviour using
                   similar strategies to the brain, by combining the
                   relationships between the current state of the organism and
                   the consequences of future actions? Recent work has shown
                   that recurrent neural networks trained on goal based tasks
                   can develop representations resembling those found in the
                   brain, entorhinal cortex grid cells, for instance. Here we
                   explore the evolution of the dynamics of their internal
                   representations and compare this with experimental data. We
                   observe that once a recurrent network is trained to learn
                   the structure of its environment solely based on sensory
                   prediction, an attractor based landscape forms in the
                   network's representation, which parallels hippocampal place
                   cells in structure and function. Next, we extend the
                   predictive objective to include Q-learning for a reward
                   task, where rewarding actions are dependent on delayed cue
                   modulation. Mirroring experimental findings in hippocampus
                   recordings in rodents performing the same task, this
                   training paradigm causes nonlocal neural activity to sweep
                   forward in space at decision points, anticipating the future
                   path to a rewarded location. Moreover, prevalent choice and
                   cue-selective neurons form in this network, again
                   recapitulating experimental findings. Together, these
                   results indicate that combining predictive, unsupervised
                   learning of the structure of an environment with
                   reinforcement learning can help understand the formation of
                   hippocampus-like representations containing both spatial and
                   task-relevant information.",
  month         =  dec,
  year          =  2020,
  keywords      = "RNN;RNN To read",
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.NC",
  eprint        = "2012.01328"
}

@UNPUBLISHED{Schaeffer2020-qv,
  title    = "Reverse-engineering Recurrent Neural Network solutions to a
              hierarchical inference task for mice",
  author   = "Schaeffer, Rylan and Khona, Mikail and Meshulam, Leenoy and
              {International Brain Laboratory} and Fiete, Ila Rani",
  abstract = "We study how recurrent neural networks (RNNs) solve a
              hierarchical inference task involving two latent variables and
              disparate timescales separated by 1-2 orders of magnitude. The
              task is of interest to the International Brain Laboratory, a
              global collaboration of experimental and theoretical
              neuroscientists studying how the mammalian brain generates
              behavior. We make four discoveries. First, RNNs learn behavior
              that is quantitatively similar to ideal Bayesian baselines.
              Second, RNNs perform inference by learning a two-dimensional
              subspace defining beliefs about the latent variables. Third, the
              geometry of RNN dynamics reflects an induced coupling between the
              two separate inference processes necessary to solve the task.
              Fourth, we perform model compression through a novel form of
              knowledge distillation on hidden representations --
              Representations and Dynamics Distillation (RADD)-- to reduce the
              RNN dynamics to a low-dimensional, highly interpretable model.
              This technique promises a useful tool for interpretability of
              high dimensional nonlinear dynamical systems. Altogether, this
              work yields predictions to guide exploration and analysis of
              mouse neural data and circuity. \#\#\# Competing Interest
              Statement The authors have declared no competing interest.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.06.09.142745",
  month    =  jun,
  year     =  2020,
  keywords = "RNN",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@UNPUBLISHED{Van_der_Zouwen2020-zn,
  title    = "Freely behaving mice can brake and turn during optogenetic
              stimulation of the Mesencephalic Locomotor Region",
  author   = "van der Zouwen, Cornelis Immanuel and Boutin, Jo{\"e}l and
              Foug{\`e}re, Maxime and Flaive, Aur{\'e}lie and Vivancos,
              M{\'e}lanie and Santuz, Alessandro and Akay, Turgay and Sarret,
              Philippe and Ryczko, Dimitri",
  abstract = "Background Stimulation of the Mesencephalic Locomotor Region (
              MLR ) is increasingly considered as a target to improve locomotor
              function in Parkinson's disease, spinal cord injury and stroke. A
              key function of the MLR is to control the speed of forward
              symmetrical locomotor movements. However, the ability of freely
              moving mammals to integrate environmental cues to brake and turn
              during MLR stimulation is poorly documented. Objective/hypothesis
              We investigated whether freely behaving mice could brake or turn
              based on environmental cues during MLR stimulation. Methods We
              stimulated the cuneiform nucleus in mice expressing
              channelrhodopsin in Vglut2-positive neurons in a Cre-dependent
              manner (Vglut2-ChR2-EYFP) using optogenetics. We detected
              locomotor movements using deep learning. We used patch-clamp
              recordings to validate the functional expression of
              channelrhodopsin and neuroanatomy to visualize the stimulation
              sites. Results Optogenetic stimulation of the MLR evoked
              locomotion and increasing laser power increased locomotor speed.
              Gait diagram and limb kinematics were similar during spontaneous
              and optogenetic-evoked locomotion. Mice could brake and make
              sharp turns (∼90⁰) when approaching a corner during MLR
              stimulation in an open-field arena. The speed during the turn was
              scaled with the speed before the turn, and with the turn angle.
              In a reporter mouse, many Vglut2-ZsGreen neurons were
              immunopositive for glutamate in the MLR. Patch-clamp recordings
              in Vglut2-ChR2-EYFP mice show that blue light evoked short
              latency spiking in MLR neurons. Conclusion MLR glutamatergic
              neurons are a relevant target to improve locomotor activity
              without impeding the ability to brake and turn when approaching
              an obstacle, thus ensuring smooth and adaptable navigation.
              Highlights \#\#\# Competing Interest Statement The authors have
              declared no competing interest.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.11.30.404525",
  month    =  dec,
  year     =  2020,
  keywords = "Locomotion",
  language = "en"
}

@UNPUBLISHED{Harris2020-im,
  title    = "Nonsense correlations in neuroscience",
  author   = "Harris, Kenneth D",
  abstract = "Most neurophysiological signals exhibit slow continuous trends
              over time. Because standard correlation analyses assume that all
              samples are independent, they can yield apparently significant
              ``nonsense correlations'' even for signals that are completely
              unrelated. Here we compare the performance of several methods for
              assessing correlations between timeseries, using simulated slowly
              drifting signals with and without genuine correlations. The best
              performance was obtained from a ``pseudosession method'', which
              relies on one of the signals being randomly generated by the
              experimenter, or a ``session perturbation'' method which requires
              multiple recordings under the same conditions. If neither of
              these is applicable, we find that a ``linear shift method can
              work well, but only when one of the signals is stationary.
              Methods based on cross-validation, circular shifting, phase
              randomization, or detrending gave up to 100\% false positive
              rates in our simulations. We conclude that analysis of neural
              timeseries is best performed when stationarity and randomization
              is built into the experimental design. \#\#\# Competing Interest
              Statement The authors have declared no competing interest.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.11.29.402719",
  month    =  nov,
  year     =  2020,
  language = "en"
}

@UNPUBLISHED{Michaels2020-ut,
  title    = "A modular neural network model of grasp movement generation",
  author   = "Michaels, Jonathan A and Schaffelhofer, Stefan and Agudelo-Toro,
              Andres and Scherberger, Hansj{\"o}rg",
  abstract = "Summary One of the primary ways we interact with the world is
              using our hands. In macaques, the circuit spanning the anterior
              intraparietal area, the hand area of the ventral premotor cortex,
              and the primary motor cortex is necessary for transforming visual
              information into grasping movements. We hypothesized that a
              recurrent neural network mimicking the multi-area structure of
              the anatomical circuit and using visual features to generate the
              required muscle dynamics to grasp objects would explain the
              neural and computational basis of the grasping circuit. Modular
              networks with object feature input and sparse inter-module
              connectivity outperformed other models at explaining neural data
              and the inter-area relationships present in the biological
              circuit, despite the absence of neural data during network
              training. Network dynamics were governed by simple rules, and
              targeted lesioning of modules produced deficits similar to those
              observed in lesion studies, providing a potential explanation for
              how grasping movements are generated.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "742189",
  month    =  feb,
  year     =  2020,
  keywords = "RNN;RNN To read;To Read",
  language = "en"
}

@ARTICLE{Harris2020-oh,
  title     = "Array programming with {NumPy}",
  author    = "Harris, Charles R and Millman, K Jarrod and van der Walt,
               St{\'e}fan J and Gommers, Ralf and Virtanen, Pauli and
               Cournapeau, David and Wieser, Eric and Taylor, Julian and Berg,
               Sebastian and Smith, Nathaniel J and Kern, Robert and Picus,
               Matti and Hoyer, Stephan and van Kerkwijk, Marten H and Brett,
               Matthew and Haldane, Allan and Del R{\'\i}o, Jaime Fern{\'a}ndez
               and Wiebe, Mark and Peterson, Pearu and G{\'e}rard-Marchant,
               Pierre and Sheppard, Kevin and Reddy, Tyler and Weckesser,
               Warren and Abbasi, Hameer and Gohlke, Christoph and Oliphant,
               Travis E",
  abstract  = "Array programming provides a powerful, compact and expressive
               syntax for accessing, manipulating and operating on data in
               vectors, matrices and higher-dimensional arrays. NumPy is the
               primary array programming library for the Python language. It
               has an essential role in research analysis pipelines in fields
               as diverse as physics, chemistry, astronomy, geoscience,
               biology, psychology, materials science, engineering, finance and
               economics. For example, in astronomy, NumPy was an important
               part of the software stack used in the discovery of
               gravitational waves1 and in the first imaging of a black hole2.
               Here we review how a few fundamental array concepts lead to a
               simple and powerful programming paradigm for organizing,
               exploring and analysing scientific data. NumPy is the foundation
               upon which the scientific Python ecosystem is constructed. It is
               so pervasive that several projects, targeting audiences with
               specialized needs, have developed their own NumPy-like
               interfaces and array objects. Owing to its central position in
               the ecosystem, NumPy increasingly acts as an interoperability
               layer between such array computation libraries and, together
               with its application programming interface (API), provides a
               flexible framework to support the next decade of scientific and
               industrial analysis.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  585,
  number    =  7825,
  pages     = "357--362",
  month     =  sep,
  year      =  2020,
  language  = "en"
}

@UNPUBLISHED{BRAIN_Initiative_Cell_Census_Network_BICCN2020-cp,
  title    = "A multimodal cell census and atlas of the mammalian primary motor
              cortex",
  author   = "{BRAIN Initiative Cell Census Network (BICCN)} and Adkins, Ricky
              S and Aldridge, Andrew I and Allen, Shona and Ament, Seth A and
              An, Xu and Armand, Ethan and Ascoli, Giorgio A and Bakken, Trygve
              E and Bandrowski, Anita and Banerjee, Samik and Barkas, Nikolaos
              and Bartlett, Anna and Bateup, Helen S and Margarita Behrens, M
              and Berens, Philipp and Berg, Jim and Bernabucci, Matteo and
              Bernaerts, Yves and Bertagnolli, Darren and Biancalani, Tommaso
              and Boggeman, Lara and Sina Booeshaghi, A and Bowman, Ian and
              Bravo, H{\'e}ctor Corrada and Cadwell, Cathryn Ren{\'e} and
              Callaway, Edward M and Carlin, Benjamin and O'Connor, Carolyn and
              Carter, Robert and Casper, Tamara and Castanon, Rosa G and
              Castro, Jesus Ramon and Chance, Rebecca K and Chatterjee, Apaala
              and Chen, Huaming and Chun, Jerold and Colantuoni, Carlo and
              Crabtree, Jonathan and Creasy, Heather and Crichton, Kirsten and
              Crow, Megan and D'Orazi, Florence D and Daigle, Tanya L and
              Dalley, Rachel and Dee, Nick and Degatano, Kylee and Dichter,
              Benjamin and Diep, Dinh and Ding, Liya and Ding, Song-Lin and
              Dominguez, Bertha and Dong, Hong-Wei and Dong, Weixiu and
              Dougherty, Elizabeth L and Dudoit, Sandrine and Ecker, Joseph R
              and Eichhorn, Stephen W and Fang, Rongxin and Felix, Victor and
              Feng, Guoping and Feng, Zhao and Fischer, Stephan and
              Fitzpatrick, Conor and Fong, Olivia and Foster, Nicholas N and
              Galbavy, William and Gee, James C and Ghosh, Satrajit S and
              Giglio, Michelle and Gillespie, Thomas H and Gillis, Jesse and
              Goldman, Melissa and Goldy, Jeff and Gong, Hui and Gou, Lin and
              Grauer, Michael and Halchenko, Yaroslav O and Harris, Julie A and
              Hartmanis, Leonard and Hatfield, Joshua T and Hawrylycz, Mike and
              Helba, Brian and Herb, Brian R and Hertzano, Ronna and Hintiryan,
              Houri and Hirokawa, Karla E and Hockemeyer, Dirk and Hodge,
              Rebecca D and Hood, Greg and Horwitz, Gregory D and Hou, Xiaomeng
              and Hu, Lijuan and Hu, Qiwen and Josh Huang, Z and Huo, Bingxing
              and Ito-Cole, Tony and Jacobs, Matthew and Jia, Xueyan and Jiang,
              Shengdian and Jiang, Tao and Jiang, Xiaolong and Jin, Xin and
              Jorstad, Nikolas L and Kalmbach, Brian E and Kancherla, Jayaram
              and Dirk Keene, C and Kelly, Kathleen and Khajouei, Farzaneh and
              Kharchenko, Peter V and Kim, Gukhan and Ko, Andrew L and Kobak,
              Dmitry and Konwar, Kishori and Kramer, Daniel J and Krienen,
              Fenna M and Kroll, Matthew and Kuang, Xiuli and Kuo, Hsien-Chi
              and Lake, Blue B and Larsen, Rachael and Lathia, Kanan and
              Laturnus, Sophie and Lee, Angus Y and Lee, Cheng-Ta and Lee,
              Kuo-Fen and Lein, Ed S and Lesnar, Phil and Li, Anan and Li,
              Xiangning and Li, Xu and Li, Yang Eric and Li, Yaoyao and Li,
              Yuanyuan and Lim, Byungkook and Linnarsson, Sten and Liu,
              Christine S and Liu, Hanqing and Liu, Lijuan and Lucero, Jacinta
              D and Luo, Chongyuan and Luo, Qingming and Macosko, Evan Z and
              Mahurkar, Anup and Martone, Maryann E and Matho, Katherine S and
              McCarroll, Steven A and McCracken, Carrie and McMillen, Delissa
              and Miranda, Elanine and Mitra, Partha P and Miyazaki, Paula
              Assakura and Mizrachi, Judith and Mok, Stephanie and Mukamel,
              Eran A and Mulherkar, Shalaka and Nadaf, Naeem M and Naeemi,
              Maitham and Narasimhan, Arun and Nery, Joseph R and Ng, Lydia and
              Ngai, John and Nguyen, Thuc Nghi and Nickel, Lance and Nicovich,
              Philip R and Niu, Sheng-Yong and Ntranos, Vasilis and Nunn,
              Michael and Olley, Dustin and Orvis, Joshua and Osteen, Julia K
              and Osten, Pavel and Owen, Scott F and Pachter, Lior and
              Palaniswamy, Ramesh and Palmer, Carter R and Pang, Yan and Peng,
              Hanchuan and Pham, Thanh and Pinto-Duarte, Antonio and
              Plongthongkum, Nongluk and Poirion, Olivier and Preissl,
              Sebastian and Purdom, Elizabeth and Qu, Lei and Rashid, Mohammad
              and Reed, Nora M and Regev, Aviv and Ren, Bing and Ren, Miao and
              Rimorin, Christine and Risso, Davide and Rivkin, Angeline C and
              Mu{\~n}oz-Casta{\~n}eda, Rodrigo and Romanow, William J and
              Ropelewski, Alexander J and de B{\'e}zieux, Hector Roux and Ruan,
              Zongcai and Sandberg, Rickard and Savoia, Steven and Scala,
              Federico and Schor, Michael and Shen, Elise and Siletti, Kimberly
              and Smith, Jared B and Smith, Kimberly and Somasundaram, Saroja
              and Song, Yuanyuan and Sorensen, Staci A and Stafford, David A
              and Street, Kelly and Sulc, Josef and Sunkin, Susan and Svensson,
              Valentine and Tan, Pengcheng and Tan, Zheng Huan and Tasic,
              Bosiljka and Thompson, Carol and Tian, Wei and Tickle, Timothy L
              and Tieu, Michael and Ting, Jonathan T and Tolias, Andreas Savas
              and Torkelson, Amy and Tung, Herman and Vaishnav, Eeshit Dhaval
              and Van den Berge, Koen and van Velthoven, Cindy T J and
              Vanderburg, Charles R and Veldman, Matthew B and Vu, Minh and
              Wakeman, Wayne and Wang, Peng and Wang, Quanxin and Wang, Xinxin
              and Wang, Yimin and Wang, Yun and Welch, Joshua D and White, Owen
              and Williams, Elora and Xie, Fangming and Xie, Peng and Xiong,
              Feng and William Yang, X and Yanny, Anna Marie and Yao, Zizhen
              and Yin, Lulu and Yu, Yang and Yuan, Jing and Zeng, Hongkui and
              Zhang, Kun and Zhang, Meng and Zhang, Zhuzhu and Zhao, Sujun and
              Zhao, Xuan and Zhou, Jingtian and Zhuang, Xiaowei and Zingg,
              Brian",
  abstract = "We report the generation of a multimodal cell census and atlas of
              the mammalian primary motor cortex (MOp or M1) as the initial
              product of the BRAIN Initiative Cell Census Network (BICCN). This
              was achieved by coordinated large-scale analyses of single-cell
              transcriptomes, chromatin accessibility, DNA methylomes,
              spatially resolved single-cell transcriptomes, morphological and
              electrophysiological properties, and cellular resolution
              input-output mapping, integrated through cross-modal
              computational analysis. Together, our results advance the
              collective knowledge and understanding of brain cell type
              organization: First, our study reveals a unified molecular
              genetic landscape of cortical cell types that congruently
              integrates their transcriptome, open chromatin and DNA
              methylation maps. Second, cross-species analysis achieves a
              unified taxonomy of transcriptomic types and their hierarchical
              organization that are conserved from mouse to marmoset and human.
              Third, cross-modal analysis provides compelling evidence for the
              epigenomic, transcriptomic, and gene regulatory basis of neuronal
              phenotypes such as their physiological and anatomical properties,
              demonstrating the biological validity and genomic underpinning of
              neuron types and subtypes. Fourth, in situ single-cell
              transcriptomics provides a spatially-resolved cell type atlas of
              the motor cortex. Fifth, integrated transcriptomic, epigenomic
              and anatomical analyses reveal the correspondence between neural
              circuits and transcriptomic cell types. We further present an
              extensive genetic toolset for targeting and fate mapping
              glutamatergic projection neuron types toward linking their
              developmental trajectory to their circuit function. Together, our
              results establish a unified and mechanistic framework of neuronal
              cell type organization that integrates multi-layered molecular
              genetic and spatial information with multi-faceted phenotypic
              properties. \#\#\# Competing Interest Statement The competing
              interests are detailed in the Competing Interests section in the
              manuscript file.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.10.19.343129",
  month    =  oct,
  year     =  2020,
  language = "en"
}

@ARTICLE{Humphries2020-nf,
  title         = "Strong and weak principles of neural dimension reduction",
  author        = "Humphries, Mark D",
  abstract      = "If spikes are the medium, what is the message? Answering
                   that question is driving the development of large-scale,
                   single neuron resolution recordings from behaving animals,
                   on the scale of thousands of neurons. But these data are
                   inherently high-dimensional, with as many dimensions as
                   neurons - so how do we make sense of them? For many the
                   answer is to reduce the number of dimensions. Here I argue
                   we can distinguish weak and strong principles of neural
                   dimension reduction. The weak principle is that dimension
                   reduction is a convenient tool for making sense of complex
                   neural data. The strong principle is that dimension
                   reduction shows us how neural circuits actually operate and
                   compute. Elucidating these principles is crucial, for which
                   we subscribe to provides radically different interpretations
                   of the same neural activity data. I show how we could make
                   either the weak or strong principles appear to be true based
                   on innocuous looking decisions about how we use dimension
                   reduction on our data. To counteract these confounds, I
                   outline the experimental evidence for the strong principle
                   that do not come from dimension reduction; but also show
                   there are a number of neural phenomena that the strong
                   principle fails to address. To reconcile these conflicting
                   data, I suggest that the brain has both principles at play.",
  month         =  nov,
  year          =  2020,
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.NC",
  eprint        = "2011.08088"
}

@ARTICLE{Sussillo2015-xp,
  title    = "A neural network that finds a naturalistic solution for the
              production of muscle activity",
  author   = "Sussillo, David and Churchland, Mark M and Kaufman, Matthew T and
              Shenoy, Krishna V",
  abstract = "It remains an open question how neural responses in motor cortex
              relate to movement. We explored the hypothesis that motor cortex
              reflects dynamics appropriate for generating temporally patterned
              outgoing commands. To formalize this hypothesis, we trained
              recurrent neural networks to reproduce the muscle activity of
              reaching monkeys. Models had to infer dynamics that could
              transform simple inputs into temporally and spatially complex
              patterns of muscle activity. Analysis of trained models revealed
              that the natural dynamical solution was a low-dimensional
              oscillator that generated the necessary multiphasic commands.
              This solution closely resembled, at both the single-neuron and
              population levels, what was observed in neural recordings from
              the same monkeys. Notably, data and simulations agreed only when
              models were optimized to find simple solutions. An appealing
              interpretation is that the empirically observed dynamics of motor
              cortex may reflect a simple solution to the problem of generating
              temporally patterned descending commands.",
  journal  = "Nat. Neurosci.",
  volume   =  18,
  number   =  7,
  pages    = "1025--1033",
  month    =  jul,
  year     =  2015,
  keywords = "RNN;RNN To read",
  language = "en"
}

@ARTICLE{Young2020-du,
  title    = "{Whole-Brain} Image Analysis and Anatomical Atlas {3D} Generation
              Using {MagellanMapper}",
  author   = "Young, David M and Duhn, Clif and Gilson, Michael and Nojima, Mai
              and Yuruk, Deniz and Kumar, Aparna and Yu, Weimiao and Sanders,
              Stephan J",
  abstract = "MagellanMapper is a software suite designed for visual inspection
              and end-to-end automated processing of large-volume, 3D brain
              imaging datasets in a memory-efficient manner. The rapidly
              growing number of large-volume, high-resolution datasets
              necessitates visualization of raw data at both macro- and
              microscopic levels to assess the quality of data, as well as
              automated processing to quantify data in an unbiased manner for
              comparison across a large number of samples. To facilitate these
              analyses, MagellanMapper provides both a graphical user interface
              for manual inspection and a command-line interface for automated
              image processing. At the macroscopic level, the graphical
              interface allows researchers to view full volumetric images
              simultaneously in each dimension and to annotate anatomical label
              placements. At the microscopic level, researchers can inspect
              regions of interest at high resolution to build ground truth data
              of cellular locations such as nuclei positions. Using the
              command-line interface, researchers can automate cell detection
              across volumetric images, refine anatomical atlas labels to fit
              underlying histology, register these atlases to sample images,
              and perform statistical analyses by anatomical region.
              MagellanMapper leverages established open-source computer vision
              libraries and is itself open source and freely available for
              download and extension. \copyright{} 2020 Wiley Periodicals LLC.
              Basic Protocol 1: MagellanMapper installation Alternate Protocol:
              Alternative methods for MagellanMapper installation Basic
              Protocol 2: Import image files into MagellanMapper Basic Protocol
              3: Region of interest visualization and annotation Basic Protocol
              4: Explore an atlas along all three dimensions and register to a
              sample brain Basic Protocol 5: Automated 3D anatomical atlas
              construction Basic Protocol 6: Whole-tissue cell detection and
              quantification by anatomical label Support Protocol: Import a
              tiled microscopy image in proprietary format into MagellanMapper.",
  journal  = "Curr. Protoc. Neurosci.",
  volume   =  94,
  number   =  1,
  pages    = "e104",
  month    =  dec,
  year     =  2020,
  keywords = "3D atlas; graphical interface; image processing; microscopy
              images; tissue clearing",
  language = "en"
}

@UNPUBLISHED{Jin2019-xr,
  title    = "{SMART}: An open source extension of {WholeBrain} for {iDISCO+}
              {LSFM} intact mouse brain registration and segmentation",
  author   = "Jin, Michelle and Nguyen, Joseph D and Weber, Sophia J and
              Mejias-Aponte, Carlos A and Madangopal, Rajtarun and Golden, Sam
              A",
  abstract = "Abstract Mapping immediate early gene (IEG) expression across
              intact brains is becoming a popular approach for identifying the
              brain-wide activity patterns underlying behavior. Registering
              whole brains to an anatomical atlas presents a technical
              challenge that has predominantly been tackled using automated
              voxel-based registration methods; however, these methods may fail
              when brains are damaged or only partially imaged, can be
              challenging to correct, and require substantial computational
              power. Here we present an open source package in R called SMART
              (semi-manual alignment to reference templates) as an extension to
              the WholeBrain framework for automated segmentation and
              semi-automated registration of experimental images to vectorized
              atlas plates from the Allen Brain Institute Mouse Common
              Coordinate Framework (CCF).The SMART package was created with the
              novice programmer in mind and introduces a streamlined pipeline
              for aligning, registering, and segmenting large LSFM volumetric
              datasets with the CCF across the anterior-posterior axis, using a
              simple `choice game' and interactive user-friendly menus. SMART
              further provides the flexibility to register partial brains or
              discrete user-chosen experimental images across the CCF, making
              it compatible with analysis of traditionally sectioned coronal
              brain slices. In addition to SMART, we introduce a modified
              tissue clearing protocol based on the iDISCO+ procedure that is
              optimized for uniform Fos antibody labeling and tissue clearing
              across whole intact mouse brains. Here we demonstrate the utility
              of the SMART-WholeBrain pipeline, in conjunction with the
              modified iDISCO+ Fos procedure, by providing example datasets
              alongside a full user tutorial. Finally, we present a subset of
              these data online in an interactive web applet. The complete
              SMART package is available for download on GitHub.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "727529",
  month    =  aug,
  year     =  2019,
  language = "en"
}

@ARTICLE{Song2020-sg,
  title    = "Precise Mapping of Single Neurons by Calibrated {3D}
              Reconstruction of Brain Slices Reveals Topographic Projection in
              Mouse Visual Cortex",
  author   = "Song, Jun Ho and Choi, Woochul and Song, You-Hyang and Kim,
              Jae-Hyun and Jeong, Daun and Lee, Seung-Hee and Paik, Se-Bum",
  abstract = "Recent breakthroughs in neuroanatomical tracing methods have
              helped unravel complicated neural connectivity in whole-brain
              tissue at single-cell resolution. However, in most cases,
              analysis of brain images remains dependent on highly subjective
              and sample-specific manual processing, preventing precise
              comparison across sample animals. In the present study, we
              introduce AMaSiNe, software for automated mapping of single
              neurons in the standard mouse brain atlas with annotated regions.
              AMaSiNe automatically calibrates misaligned and deformed slice
              samples to locate labeled neuronal positions from multiple brain
              samples into the standardized 3D Allen Mouse Brain Reference
              Atlas. We exploit the high fidelity and reliability of AMaSiNe to
              investigate the topographic structures of feedforward projections
              from the lateral geniculate nucleus to the primary visual area by
              reconstructing rabies-virus-injected brain slices in 3D space.
              Our results demonstrate that distinct organization of neural
              projections can be precisely mapped using AMaSiNe.",
  journal  = "Cell Rep.",
  volume   =  31,
  number   =  8,
  pages    = "107682",
  month    =  may,
  year     =  2020,
  keywords = "Allen Mouse Brain Reference Atlas; automated brain mapping; brain
              image registration; brain slice calibration; mouse brain slice;
              retrograde tracing; single-neuron mapping; standard 3D brain
              atlas; topographic projection; visual cortex",
  language = "en"
}

@UNPUBLISHED{Mano2020-dx,
  title    = "{CUBIC-Cloud}: An Integrative Computational Framework Towards
              Community-driven {Whole-Mouse-Brain} Mapping",
  author   = "Mano, Tomoyuki and Murata, Ken and Kon, Kazuhiro and Shimizu,
              Chika and Ono, Hiroaki and Shi, Shoi and Yamada, Rikuhiro G and
              Miyamichi, Kazunari and Susaki, Etsuo A and Touhara, Kazushige
              and Ueda, Hiroki R",
  abstract = "Recent advancements in tissue clearing technologies have offered
              unparalleled opportunities for researchers to explore the whole
              mouse brain at cellular resolution. With the expansion of this
              experimental technique, however, a scalable and easy-to-use
              computational tool is in demand to effectively analyze and
              integrate whole-brain mapping datasets. To that end, here we
              present CUBIC-Cloud, a cloud-based framework to quantify,
              visualize and integrate whole mouse brain data. CUBIC-Cloud is a
              fully automated system where users can upload their whole-brain
              data, run analysis and publish the results. We demonstrate the
              generality of CUBIC-Cloud by a variety of applications. First, we
              investigated brain-wide distribution of PV, Sst, ChAT, Th and
              Iba1 expressing cells. Second, A$\beta$ plaque deposition in AD
              model mouse brains were quantified. Third, we reconstructed
              neuronal activity profile under LPS-induced inflammation by c-Fos
              immunostaining. Last, we show brain-wide connectivity mapping by
              pseudo-typed Rabies virus. Together, CUBIC-Cloud provides an
              integrative platform to advance scalable and collaborative
              whole-brain mapping. \#\#\# Competing Interest Statement T.M. and
              H.R.U. filed a patent application regarding the CUBIC-Cloud
              software. CUBIC-Cloud web service is provided and maintained by
              CUBICStars Inc.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.08.28.271031",
  month    =  aug,
  year     =  2020,
  language = "en"
}

@ARTICLE{Goubran2019-je,
  title    = "Multimodal image registration and connectivity analysis for
              integration of connectomic data from microscopy to {MRI}",
  author   = "Goubran, Maged and Leuze, Christoph and Hsueh, Brian and Aswendt,
              Markus and Ye, Li and Tian, Qiyuan and Cheng, Michelle Y and
              Crow, Ailey and Steinberg, Gary K and McNab, Jennifer A and
              Deisseroth, Karl and Zeineh, Michael",
  abstract = "3D histology, slice-based connectivity atlases, and diffusion MRI
              are common techniques to map brain wiring. While there are many
              modality-specific tools to process these data, there is a lack of
              integration across modalities. We develop an automated resource
              that combines histologically cleared volumes with connectivity
              atlases and MRI, enabling the analysis of histological features
              across multiple fiber tracts and networks, and their correlation
              with in-vivo biomarkers. We apply our pipeline in a murine stroke
              model, demonstrating not only strong correspondence between MRI
              abnormalities and CLARITY-tissue staining, but also uncovering
              acute cellular effects in areas connected to the ischemic core.
              We provide improved maps of connectivity by quantifying
              projection terminals from CLARITY viral injections, and integrate
              diffusion MRI with CLARITY viral tracing to compare connectivity
              maps across scales. Finally, we demonstrate tract-level
              histological changes of stroke through this multimodal
              integration. This resource can propel investigations of network
              alterations underlying neurological disorders.",
  journal  = "Nat. Commun.",
  volume   =  10,
  number   =  1,
  pages    = "5504",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@ARTICLE{Renier2016-cx,
  title    = "Mapping of Brain Activity by Automated Volume Analysis of
              Immediate Early Genes",
  author   = "Renier, Nicolas and Adams, Eliza L and Kirst, Christoph and Wu,
              Zhuhao and Azevedo, Ricardo and Kohl, Johannes and Autry, Anita E
              and Kadiri, Lolahon and Umadevi Venkataraju, Kannan and Zhou, Yu
              and Wang, Victoria X and Tang, Cheuk Y and Olsen, Olav and Dulac,
              Catherine and Osten, Pavel and Tessier-Lavigne, Marc",
  abstract = "Understanding how neural information is processed in
              physiological and pathological states would benefit from precise
              detection, localization, and quantification of the activity of
              all neurons across the entire brain, which has not, to date, been
              achieved in the mammalian brain. We introduce a pipeline for
              high-speed acquisition of brain activity at cellular resolution
              through profiling immediate early gene expression using
              immunostaining and light-sheet fluorescence imaging, followed by
              automated mapping and analysis of activity by an open-source
              software program we term ClearMap. We validate the pipeline first
              by analysis of brain regions activated in response to
              haloperidol. Next, we report new cortical regions downstream of
              whisker-evoked sensory processing during active exploration.
              Last, we combine activity mapping with axon tracing to uncover
              new brain regions differentially activated during parenting
              behavior. This pipeline is widely applicable to different
              experimental paradigms, including animal species for which
              transgenic activity reporters are not readily available.",
  journal  = "Cell",
  volume   =  165,
  number   =  7,
  pages    = "1789--1802",
  month    =  jun,
  year     =  2016,
  language = "en"
}

@ARTICLE{Carlsson2020-lg,
  title     = "Topological methods for data modelling",
  author    = "Carlsson, Gunnar",
  abstract  = "The analysis of large and complex data sets is one of the most
               important problems facing the scientific community, and physics
               in particular. One response to this challenge has been the
               development of topological data analysis (TDA), which models
               data by graphs or networks rather than by linear algebraic
               (matrix) methods or cluster analysis. TDA represents the shape
               of the data (suitably defined) in a combinatorial fashion.
               Methods for measuring shape have been developed within
               mathematics, providing a toolkit referred to as homology. In
               working with data, one can use this kind of modelling to obtain
               an understanding of the overall structure of the data set. There
               is a suite of methods for constructing vector representations of
               various kinds of unstructured data. In this Review, we sketch
               the basics of TDA and provide examples where this kind of
               analysis has been carried out. The rapidly developing field of
               topological data analysis represents data via graphs rather than
               as solutions to equations or as decompositions into clusters.
               This Review discusses the methods and provides examples from
               physics and other sciences.",
  journal   = "Nature Reviews Physics",
  publisher = "Nature Publishing Group",
  pages     = "1--12",
  month     =  nov,
  year      =  2020,
  keywords  = "RNN",
  language  = "en"
}

@UNPUBLISHED{Kalidindi2020-wd,
  title    = "Rotational dynamics in motor cortex are consistent with a
              feedback controller",
  author   = "Kalidindi, Hari Teja and Cross, Kevin P and Lillicrap, Timothy P
              and Omrani, Mohsen and Falotico, Egidio and Sabes, Philip N and
              Scott, Stephen H",
  abstract = "Recent studies hypothesize that motor cortical (MC) dynamics are
              generated largely through its recurrent connections based on
              observations that MC activity exhibits rotational structure.
              However, behavioural and neurophysiological studies suggest that
              MC behaves like a feedback controller where continuous sensory
              feedback and interactions with other brain areas contribute
              substantially to MC processing. We investigated these apparently
              conflicting theories by building recurrent neural networks that
              controlled a model arm and received sensory feedback about the
              limb. Networks were trained to counteract perturbations to the
              limb and to reach towards spatial targets. Network activities and
              sensory feedback signals to the network exhibited rotational
              structure even when the recurrent connections were removed.
              Furthermore, neural recordings in monkeys performing similar
              tasks also exhibited rotational structure not only in MC but also
              in somatosensory cortex. Our results argue that rotational
              structure may reflect dynamics throughout voluntary motor
              circuits involved in online control of motor actions. \#\#\#
              Competing Interest Statement SHS is co-founder and CSO of Kinarm
              which commercializes the robotic technology used in the present
              study.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.11.17.387043",
  month    =  nov,
  year     =  2020,
  keywords = "RNN",
  language = "en"
}

@UNPUBLISHED{Reis2020-bp,
  title    = "Dorsal Periaqueductal gray ensembles represent approach and
              avoidance states",
  author   = "Reis, Fernando Mcv and Lee, Johannes Y and Maesta-Pereira, Sandra
              and Schuette, Peter J and Chakerian, Meghmik and Liu, Jinhan and
              La-Vu, Mimi Q and Tobias, Brooke C and Canteras, Newton and Kao,
              Jonathan C and Adhikari, Avishek",
  abstract = "Animals must balance needs to approach threats for
              risk-assessment and to avoid danger. The dorsal periaqueductal
              gray (dPAG) controls defensive behaviors, but it is unknown how
              it represents states associated with threat approach and
              avoidance. We identified a dPAG threat-avoidance ensemble in mice
              that showed higher activity far from threats such as the open
              arms of the elevated plus maze and a live predator. These cells
              were also more active during threat-avoidance behaviors such as
              escape and freezing, even though these behaviors have
              antagonistic motor output. Conversely, the threat-approach
              ensemble was more active during risk-assessment behaviors and
              near threats. Furthermore, unsupervised methods showed
              approach/avoidance states were encoded with shared activity
              patterns across threats. Lastly, the relative number of cells in
              each ensemble predicted threat-avoidance across mice. Thus, dPAG
              ensembles dynamically encode threat approach and avoidance
              states, providing a flexible mechanism to balance risk-assessment
              and danger avoidance.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.11.19.389486",
  month    =  nov,
  year     =  2020,
  language = "en"
}

@ARTICLE{Machado2015-ig,
  title    = "A quantitative framework for whole-body coordination reveals
              specific deficits in freely walking ataxic mice",
  author   = "Machado, Ana S and Darmohray, Dana M and Fayad, Jo{\~a}o and
              Marques, Hugo G and Carey, Megan R",
  abstract = "The coordination of movement across the body is a fundamental,
              yet poorly understood aspect of motor control. Mutant mice with
              cerebellar circuit defects exhibit characteristic impairments in
              locomotor coordination; however, the fundamental features of this
              gait ataxia have not been effectively isolated. Here we describe
              a novel system (LocoMouse) for analyzing limb, head, and tail
              kinematics of freely walking mice. Analysis of visibly ataxic
              Purkinje cell degeneration (pcd) mice reveals that while
              differences in the forward motion of individual paws are fully
              accounted for by changes in walking speed and body size, more
              complex 3D trajectories and, especially, inter-limb and
              whole-body coordination are specifically impaired. Moreover, the
              coordination deficits in pcd are consistent with a failure to
              predict and compensate for the consequences of movement across
              the body. These results isolate specific impairments in
              whole-body coordination in mice and provide a quantitative
              framework for understanding cerebellar contributions to
              coordinated locomotion.",
  journal  = "Elife",
  volume   =  4,
  month    =  oct,
  year     =  2015,
  keywords = "Purkinje cell; ataxia; cerebellum; locomotion; mouse;
              neuroscience;Locomotion",
  language = "en"
}

@ARTICLE{Russo2018-me,
  title    = "Motor Cortex Embeds Muscle-like Commands in an Untangled
              Population Response",
  author   = "Russo, Abigail A and Bittner, Sean R and Perkins, Sean M and
              Seely, Jeffrey S and London, Brian M and Lara, Antonio H and
              Miri, Andrew and Marshall, Najja J and Kohn, Adam and Jessell,
              Thomas M and Abbott, Laurence F and Cunningham, John P and
              Churchland, Mark M",
  abstract = "Primate motor cortex projects to spinal interneurons and
              motoneurons, suggesting that motor cortex activity may be
              dominated by muscle-like commands. Observations during reaching
              lend support to this view, but evidence remains ambiguous and
              much debated. To provide a different perspective, we employed a
              novel behavioral paradigm that facilitates comparison between
              time-evolving neural and muscle activity. We found that single
              motor cortex neurons displayed many muscle-like properties, but
              the structure of population activity was not muscle-like. Unlike
              muscle activity, neural activity was structured to avoid
              ``tangling'': moments where similar activity patterns led to
              dissimilar future patterns. Avoidance of tangling was present
              across tasks and species. Network models revealed a potential
              reason for this consistent feature: low tangling confers noise
              robustness. Finally, we were able to predict motor cortex
              activity from muscle activity by leveraging the hypothesis that
              muscle-like commands are embedded in additional structure that
              yields low tangling.",
  journal  = "Neuron",
  volume   =  97,
  number   =  4,
  pages    = "953--966.e8",
  month    =  feb,
  year     =  2018,
  keywords = "motor control; motor cortex; movement generation; neural
              dynamics; neural network; pattern generation; rhythmic
              movement;RNN;RNN To read",
  language = "en"
}

@UNPUBLISHED{Russo2019-sw,
  title    = "Neural trajectories in the supplementary motor area and primary
              motor cortex exhibit distinct geometries, compatible with
              different classes of computation",
  author   = "Russo, Abigail A and Khajeh, Ramin and Bittner, Sean R and
              Perkins, Sean M and Cunningham, John P and Abbott, Laurence F and
              Churchland, Mark M",
  abstract = "Abstract The supplementary motor area (SMA) is believed to
              contribute to higher-order aspects of motor control. To examine
              this contribution, we employed a novel cycling task and leveraged
              an emerging strategy: testing whether population trajectories
              possess properties necessary for a hypothesized class of
              computations. We found that, at the single-neuron level, SMA
              exhibited multiple response features absent in M1. We
              hypothesized that these diverse features might contribute, at the
              population level, to avoidance of `population trajectory
              divergence' -- ensuring that two trajectories never followed the
              same path before separating. Trajectory divergence was indeed
              avoided in SMA but not in M1. Network simulations confirmed that
              low trajectory divergence is necessary when guidance of future
              action depends upon internally tracking contextual factors.
              Furthermore, the empirical trajectory geometry -- helical in SMA
              versus elliptical in M1 -- was naturally reproduced by networks
              that did, versus did not, internally track context.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "650002",
  month    =  may,
  year     =  2019,
  keywords = "RNN;RNN To read",
  language = "en"
}

@ARTICLE{Elsayed2017-ru,
  title     = "Structure in neural population recordings: an expected byproduct
               of simpler phenomena?",
  author    = "Elsayed, Gamaleldin F and Cunningham, John P",
  abstract  = "Neuroscientists increasingly analyze the joint activity of
               multineuron recordings to identify population-level structures
               believed to be significant and scientifically novel. Claims of
               significant population structure support hypotheses in many
               brain areas. However, these claims require first investigating
               the possibility that the population structure in question is an
               expected byproduct of simpler features known to exist in data.
               Classically, this critical examination can be either intuited or
               addressed with conventional controls. However, these approaches
               fail when considering population data, raising concerns about
               the scientific merit of population-level studies. Here we
               develop a framework to test the novelty of population-level
               findings against simpler features such as correlations across
               times, neurons and conditions. We apply this framework to test
               two recent population findings in prefrontal and motor cortices,
               providing essential context to those studies. More broadly, the
               methodologies we introduce provide a general neural population
               control for many population-level hypotheses.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  20,
  number    =  9,
  pages     = "1310--1318",
  month     =  sep,
  year      =  2017,
  keywords  = "RNN To read;RNN",
  language  = "en"
}

@ARTICLE{Rivkind2017-pf,
  title    = "Local Dynamics in Trained Recurrent Neural Networks",
  author   = "Rivkind, Alexander and Barak, Omri",
  abstract = "Learning a task induces connectivity changes in neural circuits,
              thereby changing their dynamics. To elucidate task-related neural
              dynamics, we study trained recurrent neural networks. We develop
              a mean field theory for reservoir computing networks trained to
              have multiple fixed point attractors. Our main result is that the
              dynamics of the network's output in the vicinity of attractors is
              governed by a low-order linear ordinary differential equation.
              The stability of the resulting equation can be assessed,
              predicting training success or failure. As a consequence,
              networks of rectified linear units and of sigmoidal
              nonlinearities are shown to have diametrically different
              properties when it comes to learning attractors. Furthermore, a
              characteristic time constant, which remains finite at the edge of
              chaos, offers an explanation of the network's output robustness
              in the presence of variability of the internal neural dynamics.
              Finally, the proposed theory predicts state-dependent frequency
              selectivity in the network response.",
  journal  = "Phys. Rev. Lett.",
  volume   =  118,
  number   =  25,
  pages    = "258101",
  month    =  jun,
  year     =  2017,
  keywords = "RNN",
  language = "en"
}

@ARTICLE{Sussillo2016-zn,
  title         = "{LFADS} - Latent Factor Analysis via Dynamical Systems",
  author        = "Sussillo, David and Jozefowicz, Rafal and Abbott, L F and
                   Pandarinath, Chethan",
  abstract      = "Neuroscience is experiencing a data revolution in which many
                   hundreds or thousands of neurons are recorded
                   simultaneously. Currently, there is little consensus on how
                   such data should be analyzed. Here we introduce LFADS
                   (Latent Factor Analysis via Dynamical Systems), a method to
                   infer latent dynamics from simultaneously recorded,
                   single-trial, high-dimensional neural spiking data. LFADS is
                   a sequential model based on a variational auto-encoder. By
                   making a dynamical systems hypothesis regarding the
                   generation of the observed data, LFADS reduces observed
                   spiking to a set of low-dimensional temporal factors,
                   per-trial initial conditions, and inferred inputs. We
                   compare LFADS to existing methods on synthetic data and show
                   that it significantly out-performs them in inferring neural
                   firing rates and latent dynamics.",
  month         =  aug,
  year          =  2016,
  keywords      = "RNN To read;RNN",
  archivePrefix = "arXiv",
  primaryClass  = "cs.LG",
  eprint        = "1608.06315"
}

@ARTICLE{Saxe2020-mi,
  title    = "If deep learning is the answer, what is the question?",
  author   = "Saxe, Andrew and Nelli, Stephanie and Summerfield, Christopher",
  abstract = "Neuroscience research is undergoing a minor revolution. Recent
              advances in machine learning and artificial intelligence research
              have opened up new ways of thinking about neural computation.
              Many researchers are excited by the possibility that deep neural
              networks may offer theories of perception, cognition and action
              for biological brains. This approach has the potential to
              radically reshape our approach to understanding neural systems,
              because the computations performed by deep networks are learned
              from experience, and not endowed by the researcher. If so, how
              can neuroscientists use deep networks to model and understand
              biological brains? What is the outlook for neuroscientists who
              seek to characterize computations or neural codes, or who wish to
              understand perception, attention, memory and executive functions?
              In this Perspective, our goal is to offer a road map for systems
              neuroscience research in the age of deep learning. We discuss the
              conceptual and methodological challenges of comparing behaviour,
              learning dynamics and neural representations in artificial and
              biological systems, and we highlight new research questions that
              have emerged for neuroscience as a direct consequence of recent
              advances in machine learning.",
  journal  = "Nat. Rev. Neurosci.",
  month    =  nov,
  year     =  2020,
  keywords = "RNN"
}

@ARTICLE{Chon2019-ka,
  title     = "Enhanced and unified anatomical labeling for a common mouse
               brain atlas",
  author    = "Chon, Uree and Vanselow, Daniel J and Cheng, Keith C and Kim,
               Yongsoo",
  abstract  = "Anatomical atlases in standard coordinates are necessary for the
               interpretation and integration of research findings in a common
               spatial context. However, the two most-used mouse brain atlases,
               the Franklin-Paxinos (FP) and the common coordinate framework
               (CCF) from the Allen Institute for Brain Science, have
               accumulated inconsistencies in anatomical delineations and
               nomenclature, creating confusion among neuroscientists. To
               overcome these issues, we adopt here the FP labels into the CCF
               to merge the labels in the single atlas framework. We use cell
               type-specific transgenic mice and an MRI atlas to adjust and
               further segment our labels. Moreover, detailed segmentations are
               added to the dorsal striatum using cortico-striatal connectivity
               data. Lastly, we digitize our anatomical labels based on the
               Allen ontology, create a web-interface for visualization, and
               provide tools for comprehensive comparisons between the CCF and
               FP labels. Our open-source labels signify a key step towards a
               unified mouse brain atlas.",
  journal   = "Nat. Commun.",
  publisher = "nature.com",
  volume    =  10,
  number    =  1,
  pages     = "5067",
  month     =  nov,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Hanwell2015-wl,
  title    = "The Visualization Toolkit ({VTK)}: Rewriting the rendering code
              for modern graphics cards",
  author   = "Hanwell, Marcus D and Martin, Kenneth M and Chaudhary, Aashish
              and Avila, Lisa S",
  abstract = "The Visualization Toolkit (VTK) is an open source, permissively
              licensed, cross-platform toolkit for scientific data processing,
              visualization, and data analysis. It is over two decades old,
              originally developed for a very different graphics card
              architecture. Modern graphics cards feature fully programmable,
              highly parallelized architectures with large core counts. VTK's
              rendering code was rewritten to take advantage of modern graphics
              cards, maintaining most of the toolkit's programming interfaces.
              This offers the opportunity to compare the performance of old and
              new rendering code on the same systems/cards. Significant
              improvements in rendering speeds and memory footprints mean that
              scientific data can be visualized in greater detail than ever
              before. The widespread use of VTK means that these improvements
              will reap significant benefits.",
  journal  = "SoftwareX",
  volume   = "1-2",
  pages    = "9--12",
  month    =  sep,
  year     =  2015,
  keywords = "Visualization; Toolkit; Data analysis; Scientific data"
}

@ARTICLE{Golub2018-il,
  title   = "{FixedPointFinder}: A Tensorflow toolbox for identifying and
             characterizing fixed points in recurrent neural networks",
  author  = "Golub, Matthew D and Sussillo, David",
  journal = "Journal of Open Source Software",
  volume  =  3,
  number  =  31,
  pages   = "1003",
  year    =  2018
}

@ARTICLE{Barak2017-uh,
  title    = "Recurrent neural networks as versatile tools of neuroscience
              research",
  author   = "Barak, Omri",
  abstract = "Recurrent neural networks (RNNs) are a class of computational
              models that are often used as a tool to explain neurobiological
              phenomena, considering anatomical, electrophysiological and
              computational constraints. RNNs can either be designed to
              implement a certain dynamical principle, or they can be trained
              by input-output examples. Recently, there has been large progress
              in utilizing trained RNNs both for computational tasks, and as
              explanations of neural phenomena. I will review how combining
              trained RNNs with reverse engineering can provide an alternative
              framework for modeling in neuroscience, potentially serving as a
              powerful hypothesis generation tool. Despite the recent progress
              and potential benefits, there are many fundamental gaps towards a
              theory of these networks. I will discuss these challenges and
              possible methods to attack them.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  46,
  pages    = "1--6",
  month    =  oct,
  year     =  2017,
  keywords = "RNN",
  language = "en"
}

@ARTICLE{Mastrogiuseppe2018-ss,
  title    = "Linking Connectivity, Dynamics, and Computations in {Low-Rank}
              Recurrent Neural Networks",
  author   = "Mastrogiuseppe, Francesca and Ostojic, Srdjan",
  abstract = "Large-scale neural recordings have established that the
              transformation of sensory stimuli into motor outputs relies on
              low-dimensional dynamics at the population level, while
              individual neurons exhibit complex selectivity. Understanding how
              low-dimensional computations on mixed, distributed
              representations emerge from the structure of the recurrent
              connectivity and inputs to cortical networks is a major
              challenge. Here, we study a class of recurrent network models in
              which the connectivity is a sum of a random part and a minimal,
              low-dimensional structure. We show that, in such networks, the
              dynamics are low dimensional and can be directly inferred from
              connectivity using a geometrical approach. We exploit this
              understanding to determine minimal connectivity required to
              implement specific computations and find that the dynamical range
              and computational capacity quickly increase with the
              dimensionality of the connectivity structure. This framework
              produces testable experimental predictions for the relationship
              between connectivity, low-dimensional dynamics, and computational
              features of recorded neurons.",
  journal  = "Neuron",
  volume   =  99,
  number   =  3,
  pages    = "609--623.e29",
  month    =  aug,
  year     =  2018,
  keywords = "low dimensional dynamics; mixed selectivity; neural computations;
              recurrent neural networks;RNN",
  language = "en"
}

@ARTICLE{Mastrogiuseppe2019-xu,
  title    = "A Geometrical Analysis of Global Stability in Trained Feedback
              Networks",
  author   = "Mastrogiuseppe, Francesca and Ostojic, Srdjan",
  abstract = "Recurrent neural networks have been extensively studied in the
              context of neuroscience and machine learning due to their ability
              to implement complex computations. While substantial progress in
              designing effective learning algorithms has been achieved, a full
              understanding of trained recurrent networks is still lacking.
              Specifically, the mechanisms that allow computations to emerge
              from the underlying recurrent dynamics are largely unknown. Here
              we focus on a simple yet underexplored computational setup: a
              feedback architecture trained to associate a stationary output to
              a stationary input. As a starting point, we derive an approximate
              analytical description of global dynamics in trained networks,
              which assumes uncorrelated connectivity weights in the feedback
              and in the random bulk. The resulting mean-field theory suggests
              that the task admits several classes of solutions, which imply
              different stability properties. Different classes are
              characterized in terms of the geometrical arrangement of the
              readout with respect to the input vectors, defined in the
              high-dimensional space spanned by the network population. We find
              that such an approximate theoretical approach can be used to
              understand how standard training techniques implement the
              input-output task in finite-size feedback networks. In
              particular, our simplified description captures the local and the
              global stability properties of the target solution, and thus
              predicts training performance.",
  journal  = "Neural Comput.",
  volume   =  31,
  number   =  6,
  pages    = "1139--1182",
  month    =  jun,
  year     =  2019,
  keywords = "RNN;RNN To read",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Schuessler2020-ug,
  title     = "The interplay between randomness and structure during learning
               in {RNNs}",
  author    = "Schuessler, F and Mastrogiuseppe, F and Dubreuil, A and {others}",
  abstract  = "Training recurrent neural networks ( RNNs ) on low-dimensional
               tasks has been widely used to model functional biological
               networks. However, the solutions found by learning and the
               effect of initial connectivity are not well understood. Here, we
               examine RNNs trained using …",
  journal   = "Adv. Neural Inf. Process. Syst.",
  publisher = "papers.nips.cc",
  year      =  2020,
  keywords  = "RNN"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Dubreuil2020-fk,
  title     = "Complementary roles of dimensionality and population structure
               in neural computations",
  author    = "Dubreuil, A and Valente, A and Beiran, M and Mastrogiuseppe, F
               and {others}",
  abstract  = "Neural computations are currently investigated using two
               competing approaches: sorting neurons into functional classes,
               or examining the low-dimensional dynamics of collective
               activity. Whether and how these two aspects interact to shape
               computations is currently …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2020,
  keywords  = "RNN;RNN To read"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Schuessler2020-jm,
  title     = "Dynamics of random recurrent networks with correlated low-rank
               structure",
  author    = "Schuessler, F and Dubreuil, A and Mastrogiuseppe, F and {others}",
  abstract  = "A given neural network in the brain is involved in many
               different tasks. This implies that, when considering a specific
               task, the network's connectivity contains a component which is
               related to the task and another component which can be
               considered random. Understanding …",
  journal   = "Physical Review",
  publisher = "APS",
  year      =  2020,
  keywords  = "RNN;RNN To read"
}

@ARTICLE{Beiran2020-tf,
  title         = "Shaping dynamics with multiple populations in low-rank
                   recurrent networks",
  author        = "Beiran, Manuel and Dubreuil, Alexis and Valente, Adrian and
                   Mastrogiuseppe, Francesca and Ostojic, Srdjan",
  abstract      = "An emerging paradigm proposes that neural computations can
                   be understood at the level of dynamical systems that govern
                   low-dimensional trajectories of collective neural activity.
                   How the connectivity structure of a network determines the
                   emergent dynamical system however remains to be clarified.
                   Here we consider a novel class of models, Gaussian-mixture
                   low-rank recurrent networks, in which the rank of the
                   connectivity matrix and the number of statistically-defined
                   populations are independent hyper-parameters. We show that
                   the resulting collective dynamics form a dynamical system,
                   where the rank sets the dimensionality and the population
                   structure shapes the dynamics. In particular, the collective
                   dynamics can be described in terms of a simplified effective
                   circuit of interacting latent variables. While having a
                   single, global population strongly restricts the possible
                   dynamics, we demonstrate that if the number of populations
                   is large enough, a rank $R$ network can approximate any
                   $R$-dimensional dynamical system.",
  month         =  jul,
  year          =  2020,
  keywords      = "RNN",
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.NC",
  eprint        = "2007.02062"
}

@ARTICLE{Maheswaranathan2019-ue,
  title     = "Reverse engineering recurrent networks for sentiment
               classification reveals line attractor dynamics",
  author    = "Maheswaranathan, Niru and Williams, Alex H and Golub, Matthew D
               and Ganguli, Surya and Sussillo, David",
  abstract  = "Recurrent neural networks (RNNs) are a widely used tool for
               modeling sequential data, yet they are often treated as
               inscrutable black boxes. Given a trained recurrent network, we
               would like to reverse engineer it-to obtain a quantitative,
               interpretable description of how it solves a particular task.
               Even for simple tasks, a detailed understanding of how recurrent
               networks work, or a prescription for how to develop such an
               understanding, remains elusive. In this work, we use tools from
               dynamical systems analysis to reverse engineer recurrent
               networks trained to perform sentiment classification, a
               foundational natural language processing task. Given a trained
               network, we find fixed points of the recurrent dynamics and
               linearize the nonlinear system around these fixed points.
               Despite their theoretical capacity to implement complex,
               high-dimensional computations, we find that trained networks
               converge to highly interpretable, low-dimensional
               representations. In particular, the topological structure of the
               fixed points and corresponding linearized dynamics reveal an
               approximate line attractor within the RNN, which we can use to
               quantitatively understand how the RNN solves the sentiment
               analysis task. Finally, we find this mechanism present across
               RNN architectures (including LSTMs, GRUs, and vanilla RNNs)
               trained on multiple datasets, suggesting that our findings are
               not unique to a particular architecture or dataset. Overall,
               these results demonstrate that surprisingly universal and human
               interpretable computations can arise across a range of recurrent
               networks.",
  journal   = "Adv. Neural Inf. Process. Syst.",
  publisher = "papers.nips.cc",
  volume    =  32,
  pages     = "15696--15705",
  month     =  dec,
  year      =  2019,
  keywords  = "RNN To read;RNN",
  language  = "en"
}

@ARTICLE{Chang2019-bd,
  title         = "{AntisymmetricRNN}: A Dynamical System View on Recurrent
                   Neural Networks",
  author        = "Chang, Bo and Chen, Minmin and Haber, Eldad and Chi, Ed H",
  abstract      = "Recurrent neural networks have gained widespread use in
                   modeling sequential data. Learning long-term dependencies
                   using these models remains difficult though, due to
                   exploding or vanishing gradients. In this paper, we draw
                   connections between recurrent networks and ordinary
                   differential equations. A special form of recurrent networks
                   called the AntisymmetricRNN is proposed under this
                   theoretical framework, which is able to capture long-term
                   dependencies thanks to the stability property of its
                   underlying differential equation. Existing approaches to
                   improving RNN trainability often incur significant
                   computation overhead. In comparison, AntisymmetricRNN
                   achieves the same goal by design. We showcase the advantage
                   of this new architecture through extensive simulations and
                   experiments. AntisymmetricRNN exhibits much more predictable
                   dynamics. It outperforms regular LSTM models on tasks
                   requiring long-term memory and matches the performance on
                   tasks where short-term dependencies dominate despite being
                   much simpler.",
  month         =  feb,
  year          =  2019,
  keywords      = "RNN",
  archivePrefix = "arXiv",
  primaryClass  = "stat.ML",
  eprint        = "1902.09689"
}

@UNPUBLISHED{Dahmen2020-so,
  title    = "Strong coupling and local control of dimensionality across brain
              areas",
  author   = "Dahmen, David and Recanatesi, Stefano and Ocker, Gabriel Koch and
              Jia, Xiaoxuan and Helias, Moritz and Shea-Brown, Eric",
  abstract = "The dimensionality of a network's collective activity is the
              number of modes into which it is organized. This quantity is of
              great interest in neural coding: small dimensionality suggests a
              compressed neural code and possibly high robustness and
              generalizability, while high dimensionality suggests expansion of
              input features to enable flexible downstream computation. Here,
              for recurrent neural circuits operating in the ubiquitous
              balanced regime, we show how dimensionality arises
              mechanistically via perhaps the most basic property of neural
              circuits: a single number characterizing the net strength of
              their connectivity. Our results combine novel theoretical
              approaches with new analyses of high-density neuropixels
              recordings and high-throughput synaptic physiology datasets. The
              analysis of electrophysiological recordings identifies bounds on
              the dimensionality of neural responses across brain regions,
              showing that it is on the order of hundreds -- striking a balance
              between high and low-dimensional codes. Furthermore, focusing on
              the visual stream, we show that dimensionality expands from
              primary to deeper visual areas and similarly within an area from
              layer 2/3 to layer 5. We interpret these results via a novel
              theoretical result which links dimensionality to a single measure
              of net connectivity strength. This requires calculations that
              extend beyond traditional mean-field approaches to neural
              networks. Our result suggests that areas across the brain operate
              in a strongly coupled regime where dimensionality is under
              sensitive control by net connectivity strength; moreover, we show
              how this net connectivity strength is regulated by local
              connectivity features, or synaptic motifs. This enables us to
              interpret changes in dimensionality in terms of changes in
              coupling among pairs and triplets of neurons. Analysis of
              large-scale synaptic physiology datasets from both mouse and
              human cortex then reveal the presence of synaptic coupling motifs
              capable of substantially regulating this dimensionality. \#\#\#
              Competing Interest Statement The authors have declared no
              competing interest.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.11.02.365072",
  month    =  nov,
  year     =  2020,
  keywords = "RNN",
  language = "en"
}

@ARTICLE{Arganda-Carreras2018-pm,
  title    = "A Statistically Representative Atlas for Mapping Neuronal
              Circuits in the Drosophila Adult Brain",
  author   = "Arganda-Carreras, Ignacio and Manoliu, Tudor and Mazuras, Nicolas
              and Schulze, Florian and Iglesias, Juan E and B{\"u}hler, Katja
              and Jenett, Arnim and Rouyer, Fran{\c c}ois and Andrey, Philippe",
  abstract = "Imaging the expression patterns of reporter constructs is a
              powerful tool to dissect the neuronal circuits of perception and
              behavior in the adult brain of Drosophila, one of the major
              models for studying brain functions. To date, several Drosophila
              brain templates and digital atlases have been built to
              automatically analyze and compare collections of expression
              pattern images. However, there has been no systematic comparison
              of performances between alternative atlasing strategies and
              registration algorithms. Here, we objectively evaluated the
              performance of different strategies for building adult Drosophila
              brain templates and atlases. In addition, we used
              state-of-the-art registration algorithms to generate a new
              group-wise inter-sex atlas. Our results highlight the benefit of
              statistical atlases over individual ones and show that the newly
              proposed inter-sex atlas outperformed existing solutions for
              automated registration and annotation of expression patterns.
              Over 3,000 images from the Janelia Farm FlyLight collection were
              registered using the proposed strategy. These registered
              expression patterns can be searched and compared with a new
              version of the BrainBaseWeb system and BrainGazer software. We
              illustrate the validity of our methodology and brain atlas with
              registration-based predictions of expression patterns in a subset
              of clock neurons. The described registration framework should
              benefit to brain studies in Drosophila and other insect species.",
  journal  = "Front. Neuroinform.",
  volume   =  12,
  pages    = "13",
  month    =  mar,
  year     =  2018,
  keywords = "Drosophila adult brain; anatomical atlas; atlas-based image
              segmentation; average brain template; brain mapping; confocal
              microscopy; diffeomorphic image registration",
  language = "en"
}

@ARTICLE{Genkin2020-jr,
  title    = "Moving beyond generalization to accurate interpretation of
              flexible models",
  author   = "Genkin, Mikhail and Engel, Tatiana A",
  abstract = "Machine learning optimizes flexible models to predict data. In
              scientific applications, there is a rising interest in
              interpreting these flexible models to derive hypotheses from
              data. However, it is unknown whether good data prediction
              guarantees the accurate interpretation of flexible models. Here,
              we test this connection using a flexible, yet intrinsically
              interpretable framework for modelling neural dynamics. We find
              that many models discovered during optimization predict data
              equally well, yet they fail to match the correct hypothesis. We
              develop an alternative approach that identifies models with
              correct interpretation by comparing model features across data
              samples to separate true features from noise. We illustrate our
              findings using recordings of spiking activity from the visual
              cortex of monkeys performing a fixation task. Our results reveal
              that good predictions cannot substitute for accurate
              interpretation of flexible models and offer a principled approach
              to identify models with correct interpretation.",
  journal  = "Nature Machine Intelligence",
  month    =  oct,
  year     =  2020,
  keywords = "RNN To read;RNN"
}

@UNPUBLISHED{Claudi2020-tb,
  title    = "Brainrender. A python based software for visualisation of
              neuroanatomical and morphological data",
  author   = "Claudi, Federico and Tyson, Adam L and Branco, Tiago",
  abstract = "Abstract Here we present brainrender, an open source python
              package for rendering three-dimensional neuroanatomical data
              aligned to the Allen Mouse Atlas. Brainrender can be used to
              explore, visualise and compare data from publicly available
              datasets (e.g. from the Mouse Light project from Janelia) as well
              as data generated within individual laboratories. Brainrender
              facilitates the exploration of neuroanatomical data with
              three-dimensional renderings, aiding the design and
              interpretation of experiments and the dissemination of anatomical
              findings. Additionally, brainrender can also be used to generate
              high-quality, publication-ready, figures for scientific
              publications.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.02.23.961748",
  month    =  feb,
  year     =  2020,
  language = "en"
}

@MISC{Musy2019-vb,
  title  = "marcomusy/vtkplotter: vtkplotter",
  author = "Musy, Marco and Dalmasso, Giovanni and Sullivan, Bane",
  month  =  feb,
  year   =  2019
}

@UNPUBLISHED{Pachitariu2017-be,
  title    = "Suite2p: beyond 10,000 neurons with standard two-photon
              microscopy",
  author   = "Pachitariu, M and Stringer, C and Dipoppa, M and Schr{\"o}der, S
              and Rossi, L F and Dalgleish, H and Carandini, M and Harris, K D",
  abstract = "Two-photon microscopy of calcium-dependent sensors has enabled
              unprecedented recordings from vast populations of neurons. While
              the sensors and microscopes have matured over several generations
              of development, computational methods to process the resulting
              movies remain inefficient and can give results that are hard to
              interpret. Here we introduce Suite2p: a fast, accurate and
              complete pipeline that registers raw movies, detects active
              cells, extracts their calcium traces and infers their spike
              times. Suite2p runs on standard workstations, operates faster
              than real time, and recovers ~2 times more cells than the
              previous state-of-the-art method. Its low computational load
              allows routine detection of ~10,000 cells simultaneously with
              standard two-photon resonant-scanning microscopes. Recordings at
              this scale promise to reveal the fine structure of activity in
              large populations of neurons or large populations of subcellular
              structures such as synaptic boutons.",
  journal  = "bioRxiv",
  pages    = "30",
  month    =  jul,
  year     =  2017,
  language = "en"
}

@ARTICLE{Mathis2018-cn,
  title     = "{DeepLabCut}: markerless pose estimation of user-defined body
               parts with deep learning",
  author    = "Mathis, Alexander and Mamidanna, Pranav and Cury, Kevin M and
               Abe, Taiga and Murthy, Venkatesh N and Mathis, Mackenzie
               Weygandt and Bethge, Matthias",
  abstract  = "Quantifying behavior is crucial for many applications in
               neuroscience. Videography provides easy methods for the
               observation and recording of animal behavior in diverse
               settings, yet extracting particular aspects of a behavior for
               further analysis can be highly time consuming. In motor control
               studies, humans or other animals are often marked with
               reflective markers to assist with computer-based tracking, but
               markers are intrusive, and the number and location of the
               markers must be determined a priori. Here we present an
               efficient method for markerless pose estimation based on
               transfer learning with deep neural networks that achieves
               excellent results with minimal training data. We demonstrate the
               versatility of this framework by tracking various body parts in
               multiple species across a broad collection of behaviors.
               Remarkably, even when only a small number of frames are labeled
               (~200), the algorithm achieves excellent tracking performance on
               test frames that is comparable to human accuracy.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  21,
  number    =  9,
  pages     = "1281--1289",
  month     =  sep,
  year      =  2018,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Ding2016-vn,
  title    = "Comprehensive cellular-resolution atlas of the adult human brain",
  author   = "Ding, Song-Lin and Royall, Joshua J and Sunkin, Susan M and Ng,
              Lydia and Facer, Benjamin A C and Lesnar, Phil and
              Guillozet-Bongaarts, Angie and McMurray, Bergen and Szafer, Aaron
              and Dolbeare, Tim A and Stevens, Allison and Tirrell, Lee and
              Benner, Thomas and Caldejon, Shiella and Dalley, Rachel A and
              Dee, Nick and Lau, Christopher and Nyhus, Julie and Reding,
              Melissa and Riley, Zackery L and Sandman, David and Shen, Elaine
              and van der Kouwe, Andre and Varjabedian, Ani and Wright,
              Michelle and Z{\"o}llei, Lilla and Dang, Chinh and Knowles, James
              A and Koch, Christof and Phillips, John W and Sestan, Nenad and
              Wohnoutka, Paul and Zielke, H Ronald and Hohmann, John G and
              Jones, Allan R and Bernard, Amy and Hawrylycz, Michael J and Hof,
              Patrick R and Fischl, Bruce and Lein, Ed S",
  abstract = "Detailed anatomical understanding of the human brain is essential
              for unraveling its functional architecture, yet current reference
              atlases have major limitations such as lack of whole-brain
              coverage, relatively low image resolution, and sparse structural
              annotation. We present the first digital human brain atlas to
              incorporate neuroimaging, high-resolution histology, and
              chemoarchitecture across a complete adult female brain,
              consisting of magnetic resonance imaging (MRI),
              diffusion-weighted imaging (DWI), and 1,356 large-format cellular
              resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical
              plates. The atlas is comprehensively annotated for 862
              structures, including 117 white matter tracts and several novel
              cyto- and chemoarchitecturally defined structures, and these
              annotations were transferred onto the matching MRI dataset.
              Neocortical delineations were done for sulci, gyri, and modified
              Brodmann areas to link macroscopic anatomical and microscopic
              cytoarchitectural parcellations. Correlated neuroimaging and
              histological structural delineation allowed fine feature
              identification in MRI data and subsequent structural
              identification in MRI data from other brains. This interactive
              online digital atlas is integrated with existing Allen Institute
              for Brain Science gene expression atlases and is publicly
              accessible as a resource for the neuroscience community. J. Comp.
              Neurol. 524:3127-3481, 2016. \copyright{} 2016 The Authors The
              Journal of Comparative Neurology Published by Wiley Periodicals,
              Inc.",
  journal  = "J. Comp. Neurol.",
  volume   =  524,
  number   =  16,
  pages    = "3127--3481",
  month    =  nov,
  year     =  2016,
  keywords = "AB\_2314904; DWI; MRI; RRIDs: AB\_10000343; SCR\_014329;
              amygdala; brain atlas; brainstem; cerebellum; cerebral cortex;
              cytoarchitecture; hippocampal formation; hypothalamus;
              neurofilament protein; parvalbumin; thalamus",
  language = "en"
}

@UNPUBLISHED{Tyson2020-mq,
  title    = "A deep learning algorithm for {3D} cell detection in whole mouse
              brain image datasets",
  author   = "Tyson, Adam L and Rousseau, Charly V and Niedworok, Christian J
              and Keshavarzi, Sepiedeh and Tsitoura, Chryssanthi and Margrie,
              Troy W",
  abstract = "Understanding the function of the nervous system necessitates
              mapping the spatial distributions of its constituent cells
              defined by function, anatomy or gene expression. Recently,
              developments in tissue preparation and microscopy allow cellular
              populations to be imaged throughout the entire rodent brain.
              However, mapping these neurons manually is prone to bias and is
              often impractically time consuming. Here we present an
              open-source algorithm for fully automated 3D detection of
              neuronal somata in mouse whole-brain microscopy images using
              standard desktop computer hardware. We demonstrate the
              applicability and power of our approach by mapping the brain-wide
              locations of large populations of cells labeled with cytoplasmic
              fluorescent proteins expressed via retrograde trans-synaptic
              viral infection. \#\#\# Competing Interest Statement The authors
              have declared no competing interest.",
  journal  = "Cold Spring Harbor Laboratory",
  pages    = "2020.10.21.348771",
  month    =  oct,
  year     =  2020,
  language = "en"
}

@ARTICLE{Claudi2020-go,
  title    = "{BrainGlobe} Atlas {API}: a common interface for neuroanatomical
              atlases",
  author   = "Claudi, Federico and Petrucco, Luigi and Tyson, Adam and Branco,
              Tiago and Margrie, Troy and Portugues, Ruben",
  abstract = "Software archive",
  journal  = "JOSS",
  volume   =  5,
  number   =  54,
  pages    = "2668",
  month    =  oct,
  year     =  2020
}

@ARTICLE{Kunst2019-dy,
  title    = "A {Cellular-Resolution} Atlas of the Larval Zebrafish Brain",
  author   = "Kunst, Michael and Laurell, Eva and Mokayes, Nouwar and Kramer,
              Anna and Kubo, Fumi and Fernandes, Ant{\'o}nio M and F{\"o}rster,
              Dominique and Dal Maschio, Marco and Baier, Herwig",
  abstract = "Understanding brain-wide neuronal dynamics requires a detailed
              map of the underlying circuit architecture. We built an
              interactive cellular-resolution atlas of the zebrafish brain at 6
              days post-fertilization (dpf) based on the reconstructions of
              over 2,000 individually GFP-labeled neurons. We clustered our
              dataset in ``morphotypes,'' establishing a unique database of
              quantitatively described neuronal morphologies together with
              their spatial coordinates in vivo. Over 100 transgene expression
              patterns were imaged separately and co-registered with the
              single-neuron atlas. By annotating 72 non-overlapping brain
              regions, we generated from our dataset an inter-areal wiring
              diagram of the larval brain, which serves as ground truth for
              synapse-scale, electron microscopic reconstructions.
              Interrogating our atlas by ``virtual tract tracing'' has already
              revealed previously unknown wiring principles in the tectum and
              the cerebellum. In conclusion, we present here an evolving
              computational resource and visualization tool, which will be
              essential to map function to structure in a vertebrate brain.
              VIDEO ABSTRACT.",
  journal  = "Neuron",
  volume   =  103,
  number   =  1,
  pages    = "21--38.e5",
  month    =  jul,
  year     =  2019,
  keywords = "brain networks; cerebellum; connectomics; digital atlas;
              neuroanatomy; single-cell tracing; tectum; tissue clearing",
  language = "en"
}

@ARTICLE{Bates2020-fa,
  title    = "The natverse, a versatile toolbox for combining and analysing
              neuroanatomical data",
  author   = "Bates, Alexander Shakeel and Manton, James D and Jagannathan,
              Sridhar R and Costa, Marta and Schlegel, Philipp and Rohlfing,
              Torsten and Jefferis, Gregory Sxe",
  abstract = "To analyse neuron data at scale, neuroscientists expend
              substantial effort reading documentation, installing dependencies
              and moving between analysis and visualisation environments. To
              facilitate this, we have developed a suite of interoperable
              open-source R packages called the natverse. The natverse allows
              users to read local and remote data, perform popular analyses
              including visualisation and clustering and graph-theoretic
              analysis of neuronal branching. Unlike most tools, the natverse
              enables comparison across many neurons of morphology and
              connectivity after imaging or co-registration within a common
              template space. The natverse also enables transformations between
              different template spaces and imaging modalities. We demonstrate
              tools that integrate the vast majority of Drosophila
              neuroanatomical light microscopy and electron microscopy
              connectomic datasets. The natverse is an easy-to-use environment
              for neuroscientists to solve complex, large-scale analysis
              challenges as well as an open platform to create new code and
              packages to share with the community.",
  journal  = "Elife",
  volume   =  9,
  month    =  apr,
  year     =  2020,
  keywords = "D. melanogaster; analysis software; computational biology;
              connectomics; mouse; neural circuits; neuroanatomy; neuronal
              morphology; neuroscience; open-source; systems biology; zebrafish",
  language = "en"
}

@MISC{Tyson2020-tt,
  title  = "brainreg: automated {3D} brain registration with support for
            multiple species and atlases",
  author = "Tyson, Adam L and Rousseau, Charly V and Margrie, Troy W",
  month  =  aug,
  year   =  2020
}

@ARTICLE{Wang2020-ee,
  title    = "The Allen Mouse Brain Common Coordinate Framework: A {3D}
              Reference Atlas",
  author   = "Wang, Quanxin and Ding, Song-Lin and Li, Yang and Royall, Josh
              and Feng, David and Lesnar, Phil and Graddis, Nile and Naeemi,
              Maitham and Facer, Benjamin and Ho, Anh and Dolbeare, Tim and
              Blanchard, Brandon and Dee, Nick and Wakeman, Wayne and Hirokawa,
              Karla E and Szafer, Aaron and Sunkin, Susan M and Oh, Seung Wook
              and Bernard, Amy and Phillips, John W and Hawrylycz, Michael and
              Koch, Christof and Zeng, Hongkui and Harris, Julie A and Ng,
              Lydia",
  abstract = "Summary Recent large-scale collaborations are generating major
              surveys of cell types and connections in the mouse brain,
              collecting large amounts of data across modalities, spatial
              scales, and brain areas. Successful integration of these data
              requires a standard 3D reference atlas. Here, we present the
              Allen Mouse Brain Common Coordinate Framework (CCFv3) as such a
              resource. We constructed an average template brain at 10 $\mu$m
              voxel resolution by interpolating high resolution in-plane serial
              two-photon tomography images with 100 $\mu$m z-sampling from
              1,675 young adult C57BL/6J mice. Then, using multimodal reference
              data, we parcellated the entire brain directly in 3D, labeling
              every voxel with a brain structure spanning 43 isocortical areas
              and their layers, 329 subcortical gray matter structures, 81
              fiber tracts, and 8 ventricular structures. CCFv3 can be used to
              analyze, visualize, and integrate multimodal and multiscale
              datasets in 3D and is openly accessible
              (https://atlas.brain-map.org/).",
  journal  = "Cell",
  volume   =  181,
  number   =  4,
  pages    = "936--953.e20",
  month    =  may,
  year     =  2020,
  keywords = "average mouse brain; reference atlas; 3D brain atlas; brain
              parcellation; brain anatomy; mouse cortex; common coordinate
              framework; CCFv3; fiber tracts; transgenic mice"
}

@ARTICLE{Kleinman_undated-cx,
  title  = "Recurrent neural network models of multi-area computation
            underlying decision-making",
  author = "Kleinman, Michael and Chandrasekaran, Chandramouli and Kao,
            Jonathan C"
}

@ARTICLE{Maheswaranathan2019-ux,
  title    = "Universality and individuality in neural dynamics across large
              populations of recurrent networks",
  author   = "Maheswaranathan, Niru and Williams, Alex H and Golub, Matthew D
              and Ganguli, Surya and Sussillo, David",
  abstract = "Task-based modeling with recurrent neural networks (RNNs) has
              emerged as a popular way to infer the computational function of
              different brain regions. These models are quantitatively assessed
              by comparing the low-dimensional neural representations of the
              model with the brain, for example using canonical correlation
              analysis (CCA). However, the nature of the detailed
              neurobiological inferences one can draw from such efforts remains
              elusive. For example, to what extent does training neural
              networks to solve common tasks uniquely determine the network
              dynamics, independent of modeling architectural choices? Or
              alternatively, are the learned dynamics highly sensitive to
              different model choices? Knowing the answer to these questions
              has strong implications for whether and how we should use
              task-based RNN modeling to understand brain dynamics. To address
              these foundational questions, we study populations of thousands
              of networks, with commonly used RNN architectures, trained to
              solve neuroscientifically motivated tasks and characterize their
              nonlinear dynamics. We find the geometry of the RNN
              representations can be highly sensitive to different network
              architectures, yielding a cautionary tale for measures of
              similarity that rely on representational geometry, such as CCA.
              Moreover, we find that while the geometry of neural dynamics can
              vary greatly across architectures, the underlying computational
              scaffold-the topological structure of fixed points, transitions
              between them, limit cycles, and linearized dynamics-often appears
              universal across all architectures.",
  journal  = "Adv. Neural Inf. Process. Syst.",
  volume   =  2019,
  pages    = "15629--15641",
  month    =  dec,
  year     =  2019,
  keywords = "RNN",
  language = "en"
}

@ARTICLE{Vyas2020-pw,
  title    = "Computation Through Neural Population Dynamics",
  author   = "Vyas, Saurabh and Golub, Matthew D and Sussillo, David and
              Shenoy, Krishna V",
  abstract = "Significant experimental, computational, and theoretical work has
              identified rich structure within the coordinated activity of
              interconnected neural populations. An emerging challenge now is
              to uncover the nature of the associated computations, how they
              are implemented, and what role they play in driving behavior. We
              term this computation through neural population dynamics. If
              successful, this framework will reveal general motifs of neural
              population activity and quantitatively describe how neural
              population dynamics implement computations necessary for driving
              goal-directed behavior. Here, we start with a mathematical primer
              on dynamical systems theory and analytical tools necessary to
              apply this perspective to experimental data. Next, we highlight
              some recent discoveries resulting from successful application of
              dynamical systems. We focus on studies spanning motor control,
              timing, decision-making, and working memory. Finally, we briefly
              discuss promising recent lines of investigation and future
              directions for the computation through neural population dynamics
              framework.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  43,
  pages    = "249--275",
  month    =  jul,
  year     =  2020,
  keywords = "dynamical systems; neural computation; neural population
              dynamics; state spaces;RNN",
  language = "en"
}

@ARTICLE{Bellardita2015-ut,
  title     = "Phenotypic characterization of speed-associated gait changes in
               mice reveals modular organization of locomotor networks",
  author    = "Bellardita, Carmelo and Kiehn, Ole",
  abstract  = "Studies of locomotion in mice suggest that circuits controlling
               the alternating between left and right limbs may have a modular
               organization with distinct locomotor circuits being recruited at
               different speeds. It is not clear, however, whether such a
               modular organization reflects specific behavioral outcomes
               expressed at different speeds of locomotion. Here, we use
               detailed kinematic analyses to search for signatures of a
               modular organization of locomotor circuits in intact and
               genetically modified mice moving at different speeds of
               locomotion. We show that wild-type mice display three distinct
               gaits: two alternating, walk and trot, and one synchronous,
               bound. Each gait is expressed in distinct ranges of speed with
               phenotypic inter-limb and intra-limb coordination. A fourth
               gait, gallop, closely resembled bound in most of the locomotor
               parameters but expressed diverse inter-limb coordination.
               Genetic ablation of commissural V0V neurons completely removed
               the expression of one alternating gait, trot, but left intact
               walk, gallop, and bound. Ablation of commissural V0V and V0D
               neurons led to a loss of walk, trot, and gallop, leaving bound
               as the default gait. Our study provides a benchmark for studies
               of the neuronal control of locomotion in the full range of
               speeds. It provides evidence that gait expression depends upon
               selection of different modules of neuronal ensembles.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  25,
  number    =  11,
  pages     = "1426--1436",
  month     =  jun,
  year      =  2015,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Carmelo_Bellardita_undated-rj,
  title    = "Phenotypic Characterization of {Speed-Associated} Gait Changes in
              Mice Reveals Modular Organization of Locomotor Networks",
  author   = "Carmelo Bellardita, Ole Kiehn",
  keywords = "Locomotion"
}

@ARTICLE{Vyas2020-cr,
  title    = "Computation Through Neural Population Dynamics",
  author   = "Vyas, Saurabh and Golub, Matthew D and Sussillo, David and
              Shenoy, Krishna V",
  abstract = "Significant experimental, computational, and theoretical work has
              identified rich structure within the coordinated activity of
              interconnected neural populations. An emerging challenge now is
              to uncover the nature of the associated computations, how they
              are implemented, and what role they play in driving behavior. We
              term this computation through neural population dynamics. If
              successful, this framework will reveal general motifs of neural
              population activity and quantitatively describe how neural
              population dynamics implement computations necessary for driving
              goal-directed behavior. Here, we start with a mathematical primer
              on dynamical systems theory and analytical tools necessary to
              apply this perspective to experimental data. Next, we highlight
              some recent discoveries resulting from successful application of
              dynamical systems. We focus on studies spanning motor control,
              timing, decision-making, and working memory. Finally, we briefly
              discuss promising recent lines of investigation and future
              directions for the computation through neural population dynamics
              framework.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  43,
  pages    = "249--275",
  month    =  jul,
  year     =  2020,
  keywords = "dynamical systems; neural computation; neural population
              dynamics; state spaces",
  language = "en"
}

@UNPUBLISHED{De_Cothi2020-kd,
  title    = "Predictive Maps in Rats and Humans for Spatial Navigation",
  author   = "de Cothi, William and Nyberg, Nils and Griesbauer, Eva-Maria and
              Ghaname, Carole and Zisch, Fiona and Fletcher, Lydia and Newton,
              Charlotte and Renaudineau, Sophie and Bendor, Daniel and Grieves,
              Roddy and Duvelle, Eleonore and Barry, Caswell and Spiers, Hugo J",
  abstract = "Much of our understanding of navigation has come from the study
              of rats, humans and simulated artificial agents. To date little
              attempt has been made to integrate these approaches into a common
              framework to understand mechanisms that may be shared across
              mammals and the extent to which different instantiations of
              agents best capture mammalian navigation behaviour. Here, we
              report a comparison of rats, humans and reinforcement learning
              (RL) agents in a novel open-field navigation task (Tartarus Maze)
              requiring dynamic adaptation (shortcuts and detours) to changing
              obstructions in the path to the goal. We find humans and rats are
              remarkably similar in patterns of choice in the task. The
              patterns in their choices, dwell maps and changes over time
              reveal that both species show the greatest similarity to RL
              agents utilising a predictive map: the successor representation.
              Humans also display trajectory features similar to a model-based
              RL agent. Our findings have implications for models seeking to
              explain mammalian navigation in dynamic environments and
              highlight the utility of modelling the behaviour of different
              species in the same frame-work in comparison to RL agents to
              uncover the potential mechanisms used for behaviour. \#\#\#
              Competing Interest Statement The authors have declared no
              competing interest.",
  pages    = "2020.09.26.314815",
  month    =  sep,
  year     =  2020,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Walker2018-qp,
  title    = "A comparison of two types of running wheel in terms of mouse
              preference, health, and welfare",
  author   = "Walker, Michael and Mason, Georgia",
  abstract = "Voluntary wheel running occurs in mice of all strains, sexes, and
              ages. Mice find voluntary wheel running rewarding, and it leads
              to numerous health benefits. For this reason wheels are used both
              to enhance welfare and to create models of exercise. However,
              many designs of running wheel are used. This makes between-study
              comparisons difficult, as this variability could potentially
              affect the amount, pattern, and/or intensity of running
              behaviour, and thence the wheels' effects on welfare and
              exercise-related changes in anatomy and physiology. This study
              therefore evaluated two commercially available models, chosen
              because safe for group-housed mice: Bio Serv\textregistered{}'s
              ``fast-trac'' wheel combo and Ware Manufacturing Inc.'s stainless
              steel mesh 5″ upright wheel. Working with a total of three
              hundred and fifty one female C57BL/6, DBA/2 and BALB/c mice, we
              assessed these wheels' relative utilization by mice when access
              was free; the strength of motivation for each wheel-type when
              access required crossing an electrified grid; and the impact each
              wheel had on mouse well-being (inferred from acoustic startle
              responses and neophobia) and exercise-related anatomical changes
              (BMI; heart and hind limb masses). Mice ran more on the
              ``fast-trac'' wheel regardless of whether both wheel-types were
              available at once, or only if one was present. In terms of
              motivation, subjects required to work to access a single wheel
              worked equally hard for both wheel-types (even if locked and thus
              not useable for running), but if provided with one working wheel
              for free and the other type of wheel (again unlocked) accessible
              via crossing the electrified grid, the ``fast-trac'' wheel
              emerged as more motivating, as the Maximum Price Paid for the
              Ware metal wheel was lower than that paid for the ``fast-trac''
              plastic wheel, at least for C57BL/6s and DBA/2s. No deleterious
              consequences were noted with either wheel in terms of health and
              welfare, but only mice with plastic wheels developed
              significantly larger hearts and hind limbs than control animals
              with locked wheels. Thus, where differences emerged, Bio
              Serv\textregistered{}'s ``fast-trac'' wheel combos appeared to
              better meet the aims of exercise provision than Ware
              Manufacturing's steel upright wheels.",
  journal  = "Physiol. Behav.",
  volume   =  191,
  pages    = "82--90",
  month    =  jul,
  year     =  2018,
  keywords = "Health; Motivation; Mouse; Preference; Welfare; Wheel running",
  language = "en"
}

@ARTICLE{Lemieux2016-fx,
  title    = "{Speed-Dependent} Modulation of the Locomotor Behavior in Adult
              Mice Reveals Attractor and Transitional Gaits",
  author   = "Lemieux, Maxime and Josset, Nicolas and Roussel, Marie and
              Couraud, S{\'e}bastien and Bretzner, Fr{\'e}d{\'e}ric",
  abstract = "Locomotion results from an interplay between biomechanical
              constraints of the muscles attached to the skeleton and the
              neuronal circuits controlling and coordinating muscle activities.
              Quadrupeds exhibit a wide range of locomotor gaits. Given our
              advances in the genetic identification of spinal and supraspinal
              circuits important to locomotion in the mouse, it is now
              important to get a better understanding of the full repertoire of
              gaits in the freely walking mouse. To assess this range, young
              adult C57BL/6J mice were trained to walk and run on a treadmill
              at different locomotor speeds. Instead of using the classical
              paradigm defining gaits according to their footfall pattern, we
              combined the inter-limb coupling and the duty cycle of the stance
              phase, thus identifying several types of gaits: lateral walk,
              trot, out-of-phase walk, rotary gallop, transverse gallop, hop,
              half-bound, and full-bound. Out-of-phase walk, trot, and
              full-bound were robust and appeared to function as attractor
              gaits (i.e., a state to which the network flows and stabilizes)
              at low, intermediate, and high speeds respectively. In contrast,
              lateral walk, hop, transverse gallop, rotary gallop, and
              half-bound were more transient and therefore considered
              transitional gaits (i.e., a labile state of the network from
              which it flows to the attractor state). Surprisingly, lateral
              walk was less frequently observed. Using graph analysis, we
              demonstrated that transitions between gaits were predictable, not
              random. In summary, the wild-type mouse exhibits a wider
              repertoire of locomotor gaits than expected. Future locomotor
              studies should benefit from this paradigm in assessing transgenic
              mice or wild-type mice with neurotraumatic injury or
              neurodegenerative disease affecting gait.",
  journal  = "Front. Neurosci.",
  volume   =  10,
  pages    = "42",
  month    =  feb,
  year     =  2016,
  keywords = "graph analysis; kinematic; locomotor gaits; mouse; speed;
              steady-state;Locomotion",
  language = "en"
}

@ARTICLE{Herbin2006-mc,
  title    = "How does a mouse increase its velocity? A model for investigation
              in the control of locomotion",
  author   = "Herbin, Marc and Gasc, Jean-Pierre and Renous, Sabine",
  abstract = "We analysed treadmill locomotion of the adult SWISS-OF1 mice over
              a large range of velocities. The use of a high-speed video camera
              combined with cinefluoroscopic equipment allowed us to quantify
              in detail the various space and time parameters of limb
              kinematics. We find that velocity adjustments depend upon whether
              animal used a symmetrical or non-symmetrical gait. In symmetrical
              gaits, the increase of velocity generally results equally from an
              increase in the stride frequency and the stride length. On the
              other hand, in non-symmetrical gaits, the increase in velocity is
              achieved differently according to the level of velocity used. As
              speed increases, velocity increases first as a consequence of
              increased stride frequency, then as in symmetrical gaits, by an
              equal increase in both variables, and finally at high speed,
              velocity increases through increased stride length. In both
              symmetrical and non-symmetrical gaits, stance and swing-time
              shortening contributed to the increase of the stride frequency,
              with stance time decrease being the major contributor. The
              pattern of locomotion obtained in the present study may be used
              as a model mouse system for studying locomotor deficits resulting
              from specific mutations in the nervous system. To cite this
              article: M. Herbin et al., C. R. Palevol 5 (2006). R{\'e}sum{\'e}
              Comment la souris augmente-elle sa vitesse ? Un mod{\`e}le pour
              la recherche sur le contr{\^o}le moteur de la locomotion. La
              locomotion sur tapis roulant de la souche de souris SWISS-OF1 a
              {\'e}t{\'e} analys{\'e}e {\`a} travers une large gamme de
              vitesses. L'utilisation de la vid{\'e}oradiographie {\`a} grande
              vitesse a permis de quantifier de fa{\c c}on tr{\`e}s
              d{\'e}taill{\'e}e tous les param{\`e}tres de la cin{\'e}matique
              du membre de r{\'e}f{\'e}rence. Les r{\'e}sultats ainsi obtenus
              montrent que la fr{\'e}quence et l'enjamb{\'e}e n'interviennent
              pas de la m{\^e}me fa{\c c}on dans l'augmentation de la vitesse,
              selon l'allure utilis{\'e}e. Lorsque l'animal est en allure
              sym{\'e}trique, l'augmentation de la vitesse est
              g{\'e}n{\'e}ralement obtenue par une {\'e}gale augmentation de la
              fr{\'e}quence et de l'enjamb{\'e}e. En revanche, si la souris
              utilise une allure non sym{\'e}trique, l'augmentation de la
              vitesse est obtenue diff{\'e}remment selon la valeur de cette
              derni{\`e}re. L'augmentation de la vitesse est d'abord surtout
              assur{\'e}e par une augmentation de la fr{\'e}quence, puis par
              l'augmentation {\'e}gale des deux variables et enfin surtout par
              l'augmentation de l'enjamb{\'e}e. L'augmentation de la
              fr{\'e}quence est, en revanche, surtout assur{\'e}e par une
              diminution de la dur{\'e}e du pos{\'e} et cela, quelle que soit
              l'allure utilis{\'e}e. Cette mod{\'e}lisation de la locomotion
              normale de la souris pourra {\^e}tre utilis{\'e}e comme
              r{\'e}f{\'e}rentiel pour les {\'e}tudes portant sur les
              d{\'e}ficits moteurs de certaines souches de souris mutantes ou
              transg{\'e}niques. Pour citer cet article : M. Herbin et al., C.
              R. Palevol 5 (2006).",
  journal  = "C. R. Palevol",
  volume   =  5,
  number   =  3,
  pages    = "531--540",
  month    =  mar,
  year     =  2006,
  keywords = "Stride frequency; Stride length; Treadmill; Locomotion;
              SWISS-OF1; Fr{\'e}quence; Enjamb{\'e}e; Tapis roulant;
              Locomotion; SWISS-OF1;Locomotion"
}

@ARTICLE{Walter2003-pb,
  title    = "Kinematics of 90 degrees running turns in wild mice",
  author   = "Walter, Rebecca M",
  abstract = "Turning is a requirement for locomotion on the variable terrain
              that most terrestrial animals inhabit and is a deciding factor in
              many predator-prey interactions. Despite this, the kinematics and
              mechanics of quadrupedal turns are not well understood. To gain
              insight to the turning kinematics of small quadrupedal mammals,
              six adult wild mice were videotaped at 250 Hz from below as they
              performed 90 degrees running turns. Four markers placed along the
              sagittal axis were digitized to allow observation of lateral
              bending and body rotation throughout the turn. Ground contact
              periods of the fore- and hindlimbs were also noted for each
              frame. During turning, mice increased their ground contact time,
              but did not change their stride frequency relative to straight
              running at maximum speed. Postcranial body rotation preceded
              deflection in heading, and did not occur in one continuous
              motion, but rather in bouts of 15-53 degrees. These bouts were
              synchronized with the stride cycle, such that the majority of
              rotation occurred during the second half of forelimb support and
              the first half of hindlimb support. In this phase of the stride
              cycle, the trunk was sagittally flexed and rotational inertia was
              65\% of that during maximal extension. By synchronizing body
              rotation with this portion of the stride cycle, mice can achieve
              a given angular acceleration with much lower applied torque.
              Compared with humans running along curved trajectories, mice
              maintained relatively higher speeds at proportionately smaller
              radii. A possible explanation for this difference lies in the
              more crouched limb posture of mice, which increases the
              mechanical advantage for horizontal ground force production. The
              occurrence of body rotation prior to deflection in heading may
              facilitate acceleration in the new direction by making use of the
              relatively greater force production inherent in the parasagittal
              limb posture of mice.",
  journal  = "J. Exp. Biol.",
  volume   =  206,
  number   = "Pt 10",
  pages    = "1739--1749",
  month    =  may,
  year     =  2003,
  language = "en"
}

@ARTICLE{Herbin2004-ma,
  title    = "Symmetrical and asymmetrical gaits in the mouse: patterns to
              increase velocity",
  author   = "Herbin, Marc and Gasc, Jean-Pierre and Renous, Sabine",
  abstract = "The gaits of the adult SWISS mice during treadmill locomotion at
              velocities ranging from 15 to 85 cm s(-1) have been analysed
              using a high-speed video camera combined with cinefluoroscopic
              equipment. The sequences of locomotion were analysed to determine
              the various space and time parameters of limb kinematics. We
              found that velocity adjustments are accounted for differently by
              the stride frequency and the stride length if the animal showed a
              symmetrical or an asymmetrical gait. In symmetrical gaits, the
              increase of velocity is provided by an equal increase in the
              stride length and the stride frequency. In asymmetrical gaits,
              the increase in velocity is mainly assured by an increase in the
              stride frequency in velocities ranging from 15 to 29 cm s(-1).
              Above 68 cm s(-1), velocity increase is achieved by stride length
              increase. In velocities ranging from 29 to 68 cm s(-1), the
              contribution of both variables is equal as in symmetrical gaits.
              Both stance time and swing time shortening contributed to the
              increase of the stride frequency in both gaits, though with a
              major contribution from stance time decrease. The pattern of
              locomotion obtained in a normal mouse should be used as a
              template for studying locomotor control deficits after lesions or
              in different mutations affecting the nervous system.",
  journal  = "J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol.",
  volume   =  190,
  number   =  11,
  pages    = "895--906",
  month    =  nov,
  year     =  2004,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Josset2018-js,
  title    = "Distinct Contributions of Mesencephalic Locomotor Region Nuclei
              to Locomotor Control in the Freely Behaving Mouse",
  author   = "Josset, Nicolas and Roussel, Marie and Lemieux, Maxime and
              Lafrance-Zoubga, David and Rastqar, Ali and Bretzner, Frederic",
  abstract = "The mesencephalic locomotor region (MLR) has been initially
              identified as a supraspinal center capable of initiating and
              modulating locomotion. Whereas its functional contribution to
              locomotion has been widely documented throughout the phylogeny
              from the lamprey to humans, there is still debate about its exact
              organization. Combining kinematic and electrophysiological
              recordings in mouse genetics, our study reveals that
              glutamatergic neurons of the cuneiform nucleus initiate
              locomotion and induce running gaits, whereas glutamatergic and
              cholinergic neurons of the pedunculopontine nucleus modulate
              locomotor pattern and rhythm, contributing to slow-walking gaits.
              By initiating, modulating, and accelerating locomotion, our study
              identifies and characterizes distinct neuronal populations of
              this functional region important to locomotor command.",
  journal  = "Curr. Biol.",
  volume   =  28,
  number   =  6,
  pages    = "884--901.e3",
  month    =  mar,
  year     =  2018,
  keywords = "cuneiform nucleus; electrophysiology; glutamatergic and
              cholinergic neurons; kinematic analysis; locomotor command;
              locomotor pattern rhythm and gait; mesencephalic locomotor
              region; optogenetic tools; pedunculopontine nucleus;Locomotion",
  language = "en"
}

@ARTICLE{Herbin2007-us,
  title    = "Gait parameters of treadmill versus overground locomotion in
              mouse",
  author   = "Herbin, Marc and Hackert, R{\'e}mi and Gasc, Jean-Pierre and
              Renous, Sabine",
  abstract = "Many studies of interest in motor behaviour and motor impairment
              in mice use equally treadmill or track as a routine test.
              However, the literature in mammals shows a wide difference of
              results between the kinematics of treadmill and overground
              locomotion. To study these discrepancies, we analyzed the
              locomotion of adult SWISS-OF1 mice over a large range of
              velocities using treadmill and overground track. The use of a
              high-speed video camera combined with cinefluoroscopic equipment
              allowed us to quantify in detail the various space and time
              parameters of limb kinematics. The results show that mice
              maintain the same gait pattern in both conditions. However, they
              also demonstrate that during treadmill exercise mice always
              exhibit higher stride frequency and consequently lower stride
              length. The relationship of the stance time and the swing time
              against the stride frequency are still the same in both
              conditions. We conclude that the conflict related to the
              discrepancy between the proprioceptive, vestibular, and visual
              inputs contribute to an increase in the stride frequency during
              the treadmill locomotion.",
  journal  = "Behav. Brain Res.",
  volume   =  181,
  number   =  2,
  pages    = "173--179",
  month    =  aug,
  year     =  2007,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Ahmad_Abu_Hatab2013-st,
  title   = "Dynamic Modelling of {Differential-Drive} Mobile Robots using
             Lagrange and {Newton-Euler} Methodologies: A Unified Framework",
  author  = "Ahmad Abu Hatab, Rached Dhaouadi",
  journal = "Adv Robot Autom",
  volume  =  02,
  number  =  02,
  year    =  2013
}

@MISC{noauthor_undated-dh,
  title = "Two wheeled robot thesis chapter from some gui"
}

@ARTICLE{Muryy_undated-jw,
  title  = "Route selection in non-Euclidean virtual environments",
  author = "Muryy, Alexander and Glennerster, Andrew"
}

@ARTICLE{Bermudez-Contreras2020-wk,
  title    = "The Neuroscience of Spatial Navigation and the Relationship to
              Artificial Intelligence",
  author   = "Bermudez-Contreras, Edgar and Clark, Benjamin J and Wilber, Aaron",
  abstract = "Recent advances in artificial intelligence (AI) and neuroscience
              are impressive. In AI, this includes the development of computer
              programs that can beat a grandmaster at GO or outperform human
              radiologists at cancer detection. A great deal of these
              technological developments are directly related to progress in
              artificial neural networks---initially inspired by our knowledge
              about how the brain carries out computation. In parallel,
              neuroscience has also experienced significant advances in
              understanding the brain. For example, in the field of spatial
              navigation, knowledge about the mechanisms and brain regions
              involved in neural computations of cognitive maps---an internal
              representation of space---recently received the Nobel Prize in
              medicine. Much of the recent progress in neuroscience has partly
              been due to the development of technology used to record from
              very large populations of neurons in multiple regions of the
              brain with exquisite temporal and spatial resolution in behaving
              animals. With the advent of the vast quantities of data that
              these techniques allow us to collect there has been an increased
              interest in the intersection between AI and neuroscience, many of
              these intersections involve using AI as a novel tool to explore
              and analyze these large data sets. However, given the common
              initial motivation point---to understand the brain---these
              disciplines could be more strongly linked. Currently much of this
              potential synergy is not being realized. We propose that spatial
              navigation is an excellent area in which these two disciplines
              can converge to help advance what we know about the brain. In
              this review, we first summarize progress in the neuroscience of
              spatial navigation and reinforcement learning. We then turn our
              attention to discuss how spatial navigation has been modeled
              using descriptive, mechanistic, and normative approaches and the
              use of AI in such models. Next, we discuss how AI can advance
              neuroscience, how neuroscience can advance AI, and the
              limitations of these approaches. We finally conclude by
              highlighting promising lines of research in which spatial
              navigation can be the point of intersection between neuroscience
              and AI and how this can contribute to the advancement of the
              understanding of intelligent behavior.",
  journal  = "Front. Comput. Neurosci.",
  volume   =  14,
  pages    = "63",
  year     =  2020
}

@ARTICLE{Chapuis1987-yd,
  title    = "The role of exploratory experience in a shortcut task by golden
              hamsters (Mesocricetus auratus)",
  author   = "Chapuis, N and Durup, M and Thinus-Blanc, C",
  abstract = "The aim of this experiment was to examine the role of exploratory
              experience on the ability to take a shortcut. In the first phase,
              two subspaces, X and Y, each consisting of two baited tables
              related by a runway, were separately explored by hamsters. In the
              second phase, the experimental group explored a connecting
              pathway between X and Y. The animals were finally submitted to a
              shortcut test during 2 days: in this test, in order to go from X
              to Y, they could choose between the longer familiar pathway and
              two shorter new pathways. In comparison with a control group,
              which did not undergo the second phase, the experimental group
              displayed a significant preference for the shortcut that did not
              cross the linking path with which they had had experience or
              either of the two distant portions whose linkage the animals had
              experienced. These results suggest that, in this simple
              situation, additional experience of a linking element between two
              separated subspaces has a beneficial effect on the setting up of
              spatial relationships between them, and perhaps on the
              representation of the whole situation.",
  journal  = "Anim. Learn. Behav.",
  volume   =  15,
  number   =  2,
  pages    = "174--178",
  month    =  jun,
  year     =  1987
}

@UNPUBLISHED{Arshadi2020-my,
  title    = "{SNT}: A Unifying Toolbox for Quantification of Neuronal Anatomy",
  author   = "Arshadi, Cameron and Eddison, Mark and Gunther, Ulrik A and
              Harrington, Kyle I and Ferreira, Tiago A",
  abstract = "Quantification of neuronal morphology is essential for
              understanding neuronal connectivity and many software tools have
              been developed for neuronal reconstruction and morphometry.
              However, such tools remain domain-specific, tethered to specific
              imaging modalities, and were not designed to accommodate the rich
              metadata generated by recent whole-brain cellular connectomics.
              To address these limitations, we created SNT: a unifying
              framework for neuronal morphometry and analysis of single-cell
              connectomics for the widely used Fiji and ImageJ platforms. We
              demonstrate that SNT -that replaces the popular Simple Neurite
              Tracer software- can be used to tackle important problems in
              contemporary neuroscience, validate its utility, and illustrate
              how it establishes an end-to-end platform for tracing,
              proof-editing, visualization, quantification, and modeling of
              neuroanatomy. With an open and scriptable architecture, a large
              user base, and thorough community-based documentation, SNT is an
              accessible and scalable resource for the broad neuroscience
              community that synergizes well with existing software. \#\#\#
              Competing Interest Statement The authors have declared no
              competing interest.",
  journal  = "bioRxiv",
  pages    = "2020.07.13.179325",
  month    =  jul,
  year     =  2020,
  language = "en"
}

@UNPUBLISHED{Chen2020-uy,
  title    = "Between-subject prediction reveals a shared representational
              geometry in the rodent hippocampus",
  author   = "Chen, Hung-Tu and Manning, Jeremy R and van der Meer, Matthijs A
              A",
  abstract = "Summary How a memory system encodes related experiences has
              consequences for what operations the system supports. For
              instance, independent coding enables retention of potentially
              important idiosyncratic details by reducing interference, but
              makes it difficult to generalize across experiences. Strikingly,
              the rodent hippocampus constructs statistically independent
              representations across environments (``global remapping'') and
              assigns individual neuron firing fields to locations within an
              environment in an apparently random fashion, processes thought to
              contribute to the role of the hippocampus in episodic memory.
              This random mapping implies that it should be challenging to
              predict hippocampal encoding of a given experience in a one
              subject based on the encoding of that same experience in another
              subject. Contrary to this prediction, we find that by
              constructing a common representational space across rats
              (``hyperalignment''), we can consistently predict data of
              ``right'' trials (R) on a T-maze in a target rat based on 1) the
              ``left'' trials (L) of the target rat, and 2) the relationship
              between L and R trials from a different source rat. These
              cross-subject predictions outperformed a number of control
              mappings, such as those based on permuted data that broke the
              relationship between L and R activity for individual neurons, and
              those based solely on within-subject prediction. This work
              constitutes proof-of-principle for successful cross-subject
              prediction of ensemble activity patterns in the hippocampus. This
              novel approach provides new insights in understanding how
              different experiences are structured, and suggests further work
              identifying what aspects of experience encoding are shared vs.
              unique to an individual.",
  journal  = "bioRxiv",
  pages    = "2020.01.27.922062",
  month    =  jan,
  year     =  2020,
  language = "en"
}

@ARTICLE{Cheng2005-pv,
  title    = "Is there a geometric module for spatial orientation? Squaring
              theory and evidence",
  author   = "Cheng, Ken and Newcombe, Nora S",
  abstract = "There is evidence, beginning with Cheng (1986), that mobile
              animals may use the geometry of surrounding areas to reorient
              following disorientation. Gallistel (1990) proposed that geometry
              is used to compute the major or minor axes of space and suggested
              that such information might form an encapsulated cognitive
              module. Research reviewed here, conducted on a wide variety of
              species since the initial discovery of the use of geometry and
              the formulation of the modularity claim, has supported some
              aspects of the approach, while casting doubt on others. Three
              possible processing models are presented that vary in the way in
              which (and the extent to which) they instantiate the modularity
              claim. The extant data do not permit us to discriminate among
              them. We propose a modified concept of modularity for which an
              empirical program of research is more tractable.",
  journal  = "Psychon. Bull. Rev.",
  volume   =  12,
  number   =  1,
  pages    = "1--23",
  month    =  feb,
  year     =  2005,
  language = "en"
}

@ARTICLE{Toledo2020-he,
  title     = "Cognitive map--based navigation in wild bats revealed by a new
               high-throughput tracking system",
  author    = "Toledo, Sivan and Shohami, David and Schiffner, Ingo and Lourie,
               Emmanuel and Orchan, Yotam and Bartan, Yoav and Nathan, Ran",
  abstract  = "The presence of a cognitive map is essential to our ability to
               navigate through areas we know because it facilitates the use of
               spatial knowledge to derive new routes. Whether such maps exist
               in nonhuman animals has been debated, largely because of the
               difficulty of demonstrating qualifying components of the map
               outside of a laboratory. In two studies on Egyptian fruit bats,
               Harten et al. and Toledo et al. together show that this
               species's navigational strategies meet the requirements for the
               use of a cognitive map of their environment, confirming that
               this skill occurs outside of humans (see the Perspective by
               Fenton). Science , this issue p. [194][1], p. [188][2]; see also
               p. [142][3] Seven decades of research on the ``cognitive map,''
               the allocentric representation of space, have yielded key
               neurobiological insights, yet field evidence from free-ranging
               wild animals is still lacking. Using a system capable of
               tracking dozens of animals simultaneously at high accuracy and
               resolution, we assembled a large dataset of 172 foraging
               Egyptian fruit bats comprising >18 million localizations
               collected over 3449 bat-nights across 4 years. Detailed track
               analysis, combined with translocation experiments and exhaustive
               mapping of fruit trees, revealed that wild bats seldom exhibit
               random search but instead repeatedly forage in goal-directed,
               long, and straight flights that include frequent shortcuts.
               Alternative, non--map-based strategies were ruled out by
               simulations, time-lag embedding, and other trajectory analyses.
               Our results are consistent with expectations from cognitive
               map--like navigation and support previous neurobiological
               evidence from captive bats. [1]:
               /lookup/doi/10.1126/science.aay3354 [2]:
               /lookup/doi/10.1126/science.aax6904 [3]:
               /lookup/doi/10.1126/science.abd1213",
  journal   = "Science",
  publisher = "American Association for the Advancement of Science",
  volume    =  369,
  number    =  6500,
  pages     = "188--193",
  month     =  jul,
  year      =  2020,
  language  = "en"
}

@ARTICLE{Mugan2020-bu,
  title    = "Spatial planning with long visual range benefits escape from
              visual predators in complex naturalistic environments",
  author   = "Mugan, Ugurcan and MacIver, Malcolm A",
  abstract = "It is uncontroversial that land animals have more elaborated
              cognitive abilities than their aquatic counterparts such as fish.
              Yet there is no apparent a-priori reason for this. A key
              cognitive faculty is planning. We show that in visually guided
              predator-prey interactions, planning provides a significant
              advantage, but only on land. During animal evolution, the
              water-to-land transition resulted in a massive increase in visual
              range. Simulations of behavior identify a specific type of
              terrestrial habitat, clustered open and closed areas
              (savanna-like), where the advantage of planning peaks. Our
              computational experiments demonstrate how this patchy terrestrial
              structure, in combination with enhanced visual range, can reveal
              and hide agents as a function of their movement and create a
              selective benefit for imagining, evaluating, and selecting among
              possible future scenarios-in short, for planning. The vertebrate
              invasion of land may have been an important step in their
              cognitive evolution.",
  journal  = "Nat. Commun.",
  volume   =  11,
  number   =  1,
  pages    = "3057",
  month    =  jun,
  year     =  2020,
  language = "en"
}

@ARTICLE{Dodd2000-uu,
  title     = "Use of cues by Lipophrys pholis L. (Teleostei, Blenniidae) in
               learning the position of a refuge",
  author    = "Dodd, J and Gibson, R N and Hughes, R N",
  abstract  = "The ability of Lipophrys pholis to remember the position of a
               refuge was tested in an artificial habitat under the influence
               of different visual clues. L. pholis learned the position of the
               refuge in the presence of a clue consisting only of a small
               black screen. They responded to this clue by moving towards it
               and pressing themselves up against it. Lego towers and a white
               screen clue did not provoke such a response. In a further
               experiment L. pholis continued to respond to the black screen in
               this way when the screen was moved to another location further
               from the refuge. After 12 days L. pholis learned to use the
               black screen in its new position as an indirect clue and
               navigate to the refuge directly without first approaching the
               black screen. These results suggested that when placed in a
               novel habitat the immediate reaction of L. pholis is to move
               quickly towards the first dark area they see but, with
               experience, they can use the position of large objects around
               them to navigate quickly and efficiently to a refuge.",
  journal   = "Behav. Processes",
  publisher = "Elsevier",
  volume    =  49,
  number    =  2,
  pages     = "69--75",
  month     =  apr,
  year      =  2000,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Markel1994-dh,
  title     = "An adaptive value of spatial learning and memory in the blackeye
               goby, Coryphopterus nicholsi",
  author    = "Markel, Russell W",
  abstract  = "The adaptive value of spatial learning and memory has been
               demonstrated in birds and mammals (eg Shettleworth \& Krebs
               1983; Clarke et al. 1993), but few investigations have found
               evidence of similar learning abilities in fish. The goa{\l} of
               this project was to demonstrate spatial learning and memory in
               blackeye gobies, Coryphopterus nicholsi in a context in which it
               may be adaptive, namely predator evasion. Fish can learn spatial
               relationships among rel-evant features of their environments
               (Aronson 1951, 1971; Roitblat …",
  journal   = "Anim. Behav.",
  publisher = "Elsevier",
  volume    =  47,
  number    =  6,
  pages     = "1462--1464",
  month     =  jun,
  year      =  1994
}

@ARTICLE{Burt_de_Perera2008-ki,
  title     = "Rapid learning of shelter position in an intertidal fish, the
               shanny Lipophrys pholis {L}",
  author    = "Burt de Perera, T and Guilford, T C",
  abstract  = "The homing ability of an intertidal fish, the shanny Lipophrys
               pholis, was investigated using two experiments that were based
               on the shanny?s natural propensity to home to a refuge. A
               displacement experiment demonstrated that the fish were able to
               accurately locate the previous position of a refuge once the
               shelter itself had been removed so that it could not be used as
               a cue to directly signal the goal location. This shows that the
               shanny can encode information about its familiar surroundings
               into a spatial map and use this information to home. A second
               experiment in which the cues internal and external to the
               experimental tank were put in conflict with one another
               suggested that the shanny can encode cues that are both intra-
               and external-tank cues in its representation of space, but that
               there is individual variation in the type of cues that are used,
               or memorized.",
  journal   = "J. Fish Biol.",
  publisher = "Wiley Online Library",
  volume    =  72,
  number    =  6,
  pages     = "1386--1392",
  month     =  apr,
  year      =  2008
}

@INCOLLECTION{Chapuis1987-dz,
  title     = "Detour and Shortcut Abilities in Several Species of Mammals",
  booktitle = "Cognitive Processes and Spatial Orientation in Animal and Man:
               Volume {I} Experimental Animal Psychology and Ethology",
  author    = "Chapuis, Nicole",
  editor    = "Ellen, Paul and Thinus-Blanc, Catherine",
  abstract  = "This study is concerned with two properties of cognitive
               mapping. The first is plasticity, by which I mean the ability of
               an animal to reorganize its previous experience of a given
               situation. Thus, for example, when modifications are introduced
               into a familiar spatial task, some animals can find original
               solutions; they do not become lost and they can still reach the
               goal. The second property is optimalization. It entails the
               choice and the planning of the best adapted solution: for
               example, taking the most direct of several possible ways to
               reach a goal.",
  publisher = "Springer Netherlands",
  pages     = "97--106",
  year      =  1987,
  address   = "Dordrecht"
}

@ARTICLE{Collett1982-hv,
  title   = "Do Toads Plan Routes ? A Study of the Detour Behaviour of Bufo
             viridis",
  author  = "Collett, T S",
  journal = "J. Comp. Physiol.",
  volume  =  146,
  pages   = "261--271",
  year    =  1982
}

@UNPUBLISHED{Metz2017-xq,
  title    = "Evolution and genetics of precocious burrowing behavior in
              Peromyscus mice",
  author   = "Metz, Hillery C and Bedford, Nicole L and Pan, Linda and
              Hoekstra, Hopi E",
  abstract = "Summary A central challenge in biology is to understand how
              innate behaviors evolve between closely related species. One way
              to elucidate how differences arise is to compare the development
              of behavior in species with distinct adult traits. Here, we
              report that Peromyscus polionotus is strikingly precocious with
              regard to burrowing behavior, but not other behaviors, compared
              to its sister species P. maniculatus. In P. polionotus, burrows
              were excavated as early as 17 days of age, while P. maniculatus
              did not build burrows until 10 days later. Moreover, the
              well-known differences in burrow architecture between adults of
              these species---P. polionotus adults excavate long burrows with
              an escape tunnel, while P. maniculatus dig short, single-tunnel
              burrows---were intact in juvenile burrowers. To test whether this
              juvenile behavior is influenced by early-life environment, pups
              of both species were reciprocally cross-fostered. Fostering did
              not alter the characteristic burrowing behavior of either
              species, suggesting these differences are genetic. In backcross
              F2 hybrids, we show that precocious burrowing and adult tunnel
              length are genetically correlated, and that a single P.
              polionotus allele in a genomic region linked to adult tunnel
              length is predictive of precocious burrow construction. The
              co-inheritance of developmental and adult traits indicates the
              same genetic region---either a single gene with pleiotropic
              effects, or closely linked genes--- acts on distinct aspects of
              the same behavior across life stages. Such genetic variants
              likely affect behavioral drive (i.e. motivation) to burrow, and
              thereby affect both the development and adult expression of
              burrowing behavior.Highlights Juvenile P. polionotus construct
              burrows precociously compared to its sister species P.
              maniculatusCross-fostering does not alter species-specific
              burrowing behaviorA QTL linked to adult tunnel length predicts
              developmental onset of burrow construction in hybridsPleiotropic
              genetic variant(s) may affect behavioral drive across life stages",
  journal  = "bioRxiv",
  pages    = "150243",
  month    =  jun,
  year     =  2017,
  language = "en"
}

@ARTICLE{Jackson2020-te,
  title    = "Many Paths to the Same Goal: Balancing Exploration and
              Exploitation during Probabilistic Route Planning",
  author   = "Jackson, Brian J and Fatima, Gusti Lulu and Oh, Sujean and Gire,
              David H",
  abstract = "During self-guided behaviors, animals identify constraints of the
              problems they face and adaptively employ appropriate strategies
              (Marsh, 2002). In the case of foraging, animals must balance
              sensory-guided exploration of an environment with memory-guided
              exploitation of known resource locations. Here, we show that
              animals adaptively shift cognitive resources between sensory and
              memory systems during foraging to optimize route planning under
              uncertainty. We demonstrate this using a new, laboratory-based
              discovery method to define the strategies used to solve a
              difficult route optimization scenario, the probabilistic
              ``traveling salesman'' problem (Raman and Gill, 2017; Fuentes et
              al., 2018; Mukherjee et al., 2019). Using this system, we
              precisely manipulated the strength of prior information as well
              as the complexity of the problem. We find that rats are capable
              of efficiently solving this route-planning problem, even under
              conditions with unreliable prior information and a large space of
              possible solutions. Through analysis of animals' trajectories, we
              show that they shift the balance between exploiting known
              locations and searching for new locations of rewards based on the
              predictability of reward locations. When compared with a Bayesian
              search, we found that animal performance is consistent with an
              approach that adaptively allocates cognitive resources between
              sensory processing and memory, enhancing sensory acuity and
              reducing memory load under conditions in which prior information
              is unreliable. Our findings establish new approaches to
              understand neural substrates of natural behavior as well as the
              rational development of biologically inspired approaches for
              complex real-world optimization.",
  journal  = "eNeuro",
  volume   =  7,
  number   =  3,
  month    =  jun,
  year     =  2020,
  keywords = "Bayesian; foraging; navigation",
  language = "en"
}

@MISC{Juszczak2016-fk,
  title    = "Detour Behavior of Mice Trained with Transparent, Semitransparent
              and Opaque Barriers",
  author   = "Juszczak, Grzegorz R and Miller, Michal",
  editor   = "Burne, Thomas H J",
  abstract = "Detour tasks are commonly used to study problem solving skills
              and inhibitory control in canids and primates. However, there is
              no comparable detour test designed for rodents despite its
              significance for studying the development of executive skills.
              Furthermore, mice offer research opportunities that are not
              currently possible to achieve when primates are used. Therefore,
              the aim of the study was to translate the classic detour task to
              mice and to compare obtained data with key findings obtained
              previously in other mammals. The experiment was performed with
              V-shaped barriers and was based on the water escape paradigm. The
              study showed that an apparently simple task requiring mice to
              move around a small barrier constituted in fact a challenge that
              was strongly affected by the visibility of the target. The most
              difficult task involved a completely transparent barrier, which
              forced the mice to resolve a conflict between vision and tactile
              perception. The performance depended both on the inhibitory
              skills and on previous experiences. Additionally, all mice
              displayed a preference for one side of the barrier and most of
              them relied on the egocentric strategy. Obtained results show for
              the first time that the behavior of mice subjected to the detour
              task is comparable to the behavior of other mammals tested
              previously with free-standing barriers. This detailed
              characterization of the detour behavior of mice constitutes the
              first step toward the substitution of rodents for primates in
              laboratory experiments employing the detour task.",
  month    =  sep,
  year     =  2016
}

@ARTICLE{Uribe-Marino2012-pw,
  title    = "Anti-aversive effects of cannabidiol on innate fear-induced
              behaviors evoked by an ethological model of panic attacks based
              on a prey vs the wild snake Epicrates cenchria crassus
              confrontation paradigm",
  author   = "Uribe-Mari{\~n}o, Andr{\'e}s and Francisco, Audrey and
              Castiblanco-Urbina, Maria Ang{\'e}lica and Twardowschy, Andr{\'e}
              and Salgado-Rohner, Carlos Jos{\'e} and Crippa, Jos{\'e}
              Alexandre S and Hallak, Jaime Eduardo Cec{\'\i}lio and Zuardi,
              Ant{\^o}nio Waldo and Coimbra, Norberto Cysne",
  abstract = "Several pharmacological targets have been proposed as modulators
              of panic-like reactions. However, interest should be given to
              other potential therapeutic neurochemical agents. Recent
              attention has been given to the potential anxiolytic properties
              of cannabidiol, because of its complex actions on the
              endocannabinoid system together with its effects on other
              neurotransmitter systems. The aim of this study was to
              investigate the effects of cannabidiol on innate fear-related
              behaviors evoked by a prey vs predator paradigm. Male Swiss mice
              were submitted to habituation in an arena containing a burrow and
              subsequently pre-treated with intraperitoneal administrations of
              vehicle or cannabidiol. A constrictor snake was placed inside the
              arena, and defensive and non-defensive behaviors were recorded.
              Cannabidiol caused a clear anti-aversive effect, decreasing
              explosive escape and defensive immobility behaviors outside and
              inside the burrow. These results show that cannabidiol modulates
              defensive behaviors evoked by the presence of threatening
              stimuli, even in a potentially safe environment following a fear
              response, suggesting a panicolytic effect.",
  journal  = "Neuropsychopharmacology",
  volume   =  37,
  number   =  2,
  pages    = "412--421",
  month    =  jan,
  year     =  2012,
  language = "en"
}

@ARTICLE{Kabadayi2018-pq,
  title    = "The detour paradigm in animal cognition",
  author   = "Kabadayi, Can and Bobrowicz, Katarzyna and Osvath, Mathias",
  abstract = "In this paper, we review one of the oldest paradigms used in
              animal cognition: the detour paradigm. The paradigm presents the
              subject with a situation where a direct route to the goal is
              blocked and a detour must be made to reach it. Often being an
              ecologically valid and a versatile tool, the detour paradigm has
              been used to study diverse cognitive skills like insight, social
              learning, inhibitory control and route planning. Due to the
              relative ease of administrating detour tasks, the paradigm has
              lately been used in large-scale comparative studies in order to
              investigate the evolution of inhibitory control. Here we review
              the detour paradigm and some of its cognitive requirements, we
              identify various ecological and contextual factors that might
              affect detour performance, we also discuss developmental and
              neurological underpinnings of detour behaviors, and we suggest
              some methodological approaches to make species comparisons more
              robust.",
  journal  = "Anim. Cogn.",
  volume   =  21,
  number   =  1,
  pages    = "21--35",
  month    =  jan,
  year     =  2018,
  keywords = "Comparative psychology; Detour behavior; Inhibitory control;
              Route planning",
  language = "en"
}

@UNPUBLISHED{Alonso2020-is,
  title    = "The {HexMaze}: A previous knowledge and schema task for mice",
  author   = "Alonso, Alejandra and Bokeria, Levan and van der Meij, Jacqueline
              and Samanta, Anumita and Eichler, Ronny and Spooner, Patrick and
              Lobato, Irene Navarro and Genzel, Lisa",
  abstract = "Abstract New information is rarely learned in isolation, instead
              most of what we experience can be incorporated into or uses
              previous knowledge networks in some form. However, most rodent
              laboratory tasks assume the animal to be na{\"\i}ve with no
              previous experience influencing the results. Previous knowledge
              in form of a schema can facilitate knowledge acquisition and
              accelerate systems consolidation: memories become more rapidly
              hippocampal independent and instead rely more on the prefrontal
              cortex. Here, we developed a new spatial navigation task where
              food locations are learned in a large, gangway maze -- the
              HexMaze. Analysing performance across sessions as well as on
              specific trials, we can show simple memory effects as well as
              multiple effects of previous knowledge accelerating both online
              learning and performance increases over offline periods.
              Importantly, we are the first to show that schema build-up is
              dependent on how much time passes, not how often the animal is
              trained.",
  journal  = "bioRxiv",
  pages    = "441048",
  month    =  mar,
  year     =  2020,
  language = "en"
}

@ARTICLE{Hein2018-el,
  title    = "Conserved behavioral circuits govern high-speed decision-making
              in wild fish shoals",
  author   = "Hein, Andrew M and Gil, Michael A and Twomey, Colin R and Couzin,
              Iain D and Levin, Simon A",
  abstract = "To evade their predators, animals must quickly detect potential
              threats, gauge risk, and mount a response. Putative neural
              circuits responsible for these tasks have been isolated in
              laboratory studies. However, it is unclear whether and how these
              circuits combine to generate the flexible, dynamic sequences of
              evasion behavior exhibited by wild, freely moving animals. Here,
              we report that evasion behavior of wild fish on a coral reef is
              generated through a sequence of well-defined decision rules that
              convert visual sensory input into behavioral actions. Using an
              automated system to present visual threat stimuli to fish in
              situ, we show that individuals initiate escape maneuvers in
              response to the perceived size and expansion rate of an oncoming
              threat using a decision rule that matches dynamics of known
              loom-sensitive neural circuits. After initiating an evasion
              maneuver, fish adjust their trajectories using a control rule
              based on visual feedback to steer away from the threat and toward
              shelter. These decision rules accurately describe evasion
              behavior of fish from phylogenetically distant families,
              illustrating the conserved nature of escape decision-making. Our
              results reveal how the flexible behavioral responses required for
              survival can emerge from relatively simple, conserved
              decision-making mechanisms.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  115,
  number   =  48,
  pages    = "12224--12228",
  month    =  nov,
  year     =  2018,
  keywords = "decision-making; evasion; neural circuit; neuroethology;
              predator--prey interactions",
  language = "en"
}

@ARTICLE{Carandini2012-xx,
  title    = "From circuits to behavior: a bridge too far?",
  author   = "Carandini, Matteo",
  abstract = "Neuroscience seeks to understand how neural circuits lead to
              behavior. However, the gap between circuits and behavior is too
              wide. An intermediate level is one of neural computations, which
              occur in individual neurons and populations of neurons. Some
              computations seem to be canonical: repeated and combined in
              different ways across the brain. To understand neural
              computations, we must record from a myriad of neurons in multiple
              brain regions. Understanding computation guides research in the
              underlying circuits and provides a language for theories of
              behavior.",
  journal  = "Nat. Neurosci.",
  volume   =  15,
  number   =  4,
  pages    = "507--509",
  month    =  mar,
  year     =  2012,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Fiker2020-kd,
  title    = "Visual Gait Lab: A user-friendly approach to gait analysis",
  author   = "Fiker, Robert and Kim, Linda H and Molina, Leonardo A and
              Chomiak, Taylor and Whelan, Patrick J",
  abstract = "BACKGROUND: Gait analysis forms a critical part of many lab
              workflows, ranging from those interested in preclinical
              neurological models to others who use locomotion as part of a
              standard battery of tests. Unfortunately, while paw detection can
              be semi-automated, it becomes generally a time-consuming process
              with error corrections. Improvement in paw tracking would aid in
              better gait analysis performance and experience. NEW METHOD: Here
              we show the use of Visual Gait Lab (VGL), a high-level software
              with an intuitive, easy to use interface, that is built on
              DeepLabCut™. VGL is optimized to generate gait metrics and allows
              for quick manual error corrections. VGL comes with a single
              executable, streamlining setup on Windows systems. We demonstrate
              the use of VGL to analyze gait. RESULTS: Training and evaluation
              of VGL were conducted using 200 frames (80/20 train-test split)
              of video from mice walking on a treadmill. The trained network
              was then used to visually track paw placements to compute gait
              metrics. These are processed and presented on the screen where
              the user can rapidly identify and correct errors. COMPARISON WITH
              EXISTING METHODS: Gait analysis remains cumbersome, even with
              commercial software due to paw detection errors. DeepLabCut™ is
              an alternative that can improve visual tracking but is not
              optimized for gait analysis functionality. CONCLUSIONS: VGL
              allows for gait analysis to be performed in a rapid, unbiased
              manner, with a set-up that can be easily implemented and executed
              by those without a background in computer programming.",
  journal  = "J. Neurosci. Methods",
  volume   =  341,
  pages    = "108775",
  month    =  may,
  year     =  2020,
  keywords = "DeepLabCut™; Gait analysis; Gait tracking system; Motor control;
              Mouse locomotion",
  language = "en"
}

@ARTICLE{Lecca2020-xk,
  title   = "Heterogeneous Habenular Neuronal Ensembles during Selection of
             Defensive Behaviors",
  author  = "Lecca, Salvatore and Namboodiri, Vijay M K and Restivo, Leonardo
             and Gervasi, Nicolas and Pillolla, Giuliano and Stuber, Garret D
             and Mameli, Manuel",
  journal = "Cell Rep.",
  volume  =  31,
  number  =  10,
  pages   = "107752",
  month   =  jun,
  year    =  2020
}

@ARTICLE{De_Oca2007-jy,
  title    = "Brief flight to a familiar enclosure in response to a conditional
              stimulus in rats",
  author   = "de Oca, Beatrice M and Minor, Thomas R and Fanselow, Michael S",
  abstract = "The authors observed brief, directed movement to a familiar
              enclosure in rats to determine whether this behavior is part of a
              rat's defensive repertoire when exposed to a conditional-fear
              stimulus. In Experiment 1, upon exposure to the compound
              conditional-fear stimulus of tone and light, only rats that
              received paired presentations of the conditional stimuli and
              shock fled into a small, familiar enclosure where they then
              froze. Rats that had received unpaired presentations did not
              enter the enclosure in significant amounts when later tested. In
              Experiment 2, the authors observed rats' freezing and use of
              either a familiar or an unfamiliar enclosure when tested with a
              conditional-fear stimulus. Rats tested with a familiar enclosure
              entered it more quickly than did rats without prior exposure to
              the enclosure. Freezing was greatest when both training and
              testing environments were similar with respect to access to the
              enclosure. The results of these 2 experiments support the idea
              that brief, directed flight in rats is a component of the
              postencounter stage of predatory imminence (M. S. Fanselow \& L.
              S. Lester, 1988) and is compatible with freezing.",
  journal  = "J. Gen. Psychol.",
  volume   =  134,
  number   =  2,
  pages    = "153--172",
  month    =  apr,
  year     =  2007,
  language = "en"
}

@ARTICLE{Hein2020-gg,
  title     = "An Algorithmic Approach to Natural Behavior",
  author    = "Hein, Andrew M and Altshuler, Douglas L and Cade, David E and
               Liao, James C and Martin, Benjamin T and Taylor, Graham K",
  abstract  = "SummaryUncovering the mechanisms and implications of natural
               behavior is a goal that unites many fields of biology. Yet, the
               diversity, flexibility, and multi-scale nature of these
               behaviors often make understanding elusive. Here, we review
               studies of animal pursuit and evasion --- two special classes of
               behavior where theory-driven experiments and new modeling
               techniques are beginning to uncover the general control
               principles underlying natural behavior. A key finding of these
               studies is that intricate sequences of pursuit and evasion
               behavior can often be constructed through simple, repeatable
               rules that link sensory input to motor output: we refer to these
               rules as behavioral algorithms. Identifying and mathematically
               characterizing these algorithms has led to important insights,
               including the discovery of guidance rules that attacking
               predators use to intercept mobile prey, and coordinated neural
               and biomechanical mechanisms that animals use to avoid impending
               collisions. Here, we argue that algorithms provide a good
               starting point for studies of natural behavior more generally.
               Rather than beginning at the neural or ecological levels of
               organization, we advocate starting in the middle, where the
               algorithms that link sensory input to behavioral output can
               provide a solid foundation from which to explore both the
               implementation and the ecological outcomes of behavior. We
               review insights that have been gained through such an
               algorithmic approach to pursuit and evasion behaviors. From
               these, we synthesize theoretical principles and lay out key
               modeling tools needed to apply an algorithmic approach to the
               study of other complex natural behaviors.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  30,
  number    =  11,
  pages     = "R663--R675",
  month     =  jun,
  year      =  2020,
  language  = "en"
}

@ARTICLE{Kafkafi2005-es,
  title    = "Texture of locomotor path: a replicable characterization of a
              complex behavioral phenotype",
  author   = "Kafkafi, N and Elmer, G I",
  abstract = "A database of mouse locomotor path in spatial tests can be used
              to search in silico for behavioral measures that better
              discriminate between genotypes and are more replicable across
              laboratories. In this study, software for the exploration of
              exploration (SEE) was used to search a large database for a novel
              behavioral measure that would characterize complex movement
              paths. The database included mouse open-field behavior assessed
              in 3 laboratories, 7 inbred strains, several pharmacological
              treatments and hundreds of animals. The new behavioral measure,
              ``path texture'', was characterized using the local curvature of
              the path (the change of direction per unit distance, in
              degrees/cm) across several spatial scales, starting from scales
              smaller than the animal's body length and up to the scale of the
              arena size. Path texture analysis differs from fractal dimension
              analysis in that it does not assume self-similarity across
              scales. Path texture was found to discriminate inbred strains
              with relatively high broad-sense heritability (43\%-71\%) and
              high replicability across laboratories. Even genotypes that had
              similar path curvatures in some scales usually differed in other
              scales, and self-similarity across scales was not displayed by
              all genotypes. Amphetamine decreased the path curvature of
              C57BL/6 mice in small and medium scales, while having no effect
              on DBA/2J mice. Diazepam dose-dependently decreased the curvature
              of C57BL/6 mice across all scales, while 2 anxiogenic drugs,
              FG-7142 and pentylenetetrazole, increased it. Path texture thus
              has high potential for behavioral phenotyping and the study of
              drug effects in the mouse.",
  journal  = "Genes Brain Behav.",
  volume   =  4,
  number   =  7,
  pages    = "431--443",
  month    =  oct,
  year     =  2005,
  language = "en"
}

@MISC{Dvorkin2010-js,
  title    = "Knots: Attractive Places with High Path Tortuosity in Mouse Open
              Field Exploration",
  author   = "Dvorkin, Anna and Szechtman, Henry and Golani, Ilan",
  editor   = "Bourne, Philip E",
  abstract = "When introduced into a novel environment, mammals establish in it
              a preferred place marked by the highest number of visits and
              highest cumulative time spent in it. Examination of exploratory
              behavior in reference to this ``home base'' highlights important
              features of its organization. It might therefore be fruitful to
              search for other types of marked places in mouse exploratory
              behavior and examine their influence on overall
              behavior.Examination of path curvatures of mice exploring a large
              empty arena revealed the presence of circumscribed locales marked
              by the performance of tortuous paths full of twists and turns. We
              term these places knots, and the behavior performed in
              them-knot-scribbling. There is typically no more than one knot
              per session; it has distinct boundaries and it is maintained both
              within and across sessions. Knots are mostly situated in the
              place of introduction into the arena, here away from walls. Knots
              are not characterized by the features of a home base, except for
              a high speed during inbound and a low speed during outbound
              paths. The establishment of knots is enhanced by injecting the
              mouse with saline and placing it in an exposed portion of the
              arena, suggesting that stress and the arousal associated with it
              consolidate a long-term contingency between a particular locale
              and knot-scribbling.In an environment devoid of proximal cues
              mice mark a locale associated with arousal by twisting and
              turning in it. This creates a self-generated, often centrally
              located landmark. The tortuosity of the path traced during the
              behavior implies almost concurrent multiple views of the
              environment. Knot-scribbling could therefore function as a way to
              obtain an overview of the entire environment, allowing
              re-calibration of the mouse's locale map and compass directions.
              The rich vestibular input generated by scribbling could improve
              the interpretation of the visual scene.",
  month    =  jan,
  year     =  2010
}

@MISC{Valente2007-qx,
  title    = "Analysis of the Trajectory of Drosophila melanogaster in a
              Circular Open Field Arena",
  author   = "Valente, Dan and Golani, Ilan and Mitra, Partha P",
  editor   = "Scalas, Enrico",
  abstract = "BACKGROUND Obtaining a complete phenotypic characterization of a
              freely moving organism is a difficult task, yet such a
              description is desired in many neuroethological studies. Many
              metrics currently used in the literature to describe locomotor
              and exploratory behavior are typically based on average
              quantities or subjectively chosen spatial and temporal
              thresholds. All of these measures are relatively coarse-grained
              in the time domain. It is advantageous, however, to employ
              metrics based on the entire trajectory that an organism takes
              while exploring its environment. METHODOLOGY/PRINCIPAL FINDINGS
              To characterize the locomotor behavior of Drosophila
              melanogaster, we used a video tracking system to record the
              trajectory of a single fly walking in a circular open field
              arena. The fly was tracked for two hours. Here, we present
              techniques with which to analyze the motion of the fly in this
              paradigm, and we discuss the methods of calculation. The measures
              we introduce are based on spatial and temporal probability
              distributions and utilize the entire time-series trajectory of
              the fly, thus emphasizing the dynamic nature of locomotor
              behavior. Marginal and joint probability distributions of speed,
              position, segment duration, path curvature, and reorientation
              angle are examined and related to the observed behavior.
              CONCLUSIONS/SIGNIFICANCE The measures discussed in this paper
              provide a detailed profile of the behavior of a single fly and
              highlight the interaction of the fly with the environment. Such
              measures may serve as useful tools in any behavioral study in
              which the movement of a fly is an important variable and can be
              incorporated easily into many setups, facilitating
              high-throughput phenotypic characterization.",
  month    =  oct,
  year     =  2007
}

@ARTICLE{Benjamini2010-cs,
  title    = "Ten ways to improve the quality of descriptions of whole-animal
              movement",
  author   = "Benjamini, Yoav and Lipkind, Dina and Horev, Guy and Fonio, Ehud
              and Kafkafi, Neri and Golani, Ilan",
  abstract = "The demand for replicability of behavioral results across
              laboratories is viewed as a burden in behavior genetics. We
              demonstrate how it can become an asset offering a quantitative
              criterion that guides the design of better ways to describe
              behavior. Passing the high benchmark dictated by the
              replicability demand requires less stressful and less restraining
              experimental setups, less noisy data, individually customized
              cutoff points between the building blocks of movement, and less
              variable yet discriminative dynamic representations that would
              capture more faithfully the nature of the behavior, unmasking
              similarities and differences and revealing novel animal-centered
              measures. Here we review ten tools that enhance replicability
              without compromising discrimination. While we demonstrate the
              usefulness of these tools in the context of inbred mouse
              exploratory behavior they can readily be used in any study
              involving a high-resolution analysis of spatial behavior. Viewing
              replicability as a design concept and using the ten
              methodological improvements may prove useful in many fields not
              necessarily related to spatial behavior.",
  journal  = "Neurosci. Biobehav. Rev.",
  volume   =  34,
  number   =  8,
  pages    = "1351--1365",
  month    =  jul,
  year     =  2010,
  language = "en"
}

@ARTICLE{Eilam1989-uk,
  title     = "Home base behavior of rats (Rattus norvegicus) exploring a novel
               environment",
  author    = "Eilam, D and Golani, I",
  abstract  = "When rats are placed in a novel environment, they alternate
               between progression and stopping: in the course of a session
               they stop briefly in many places, but in one or two places they
               also stop for very long periods. The place in which they stay
               for the longest cumulative time is defined as the rat's home
               base. In this place the incidences of grooming and of rearing
               are high and often the highest. In addition, the number of
               visits to the home base is typically the highest. Some rats
               establish a secondary base with similar properties to those of
               the main home base. The location of the base influences the mode
               of progression throughout the environment: progression away from
               base is slower and includes more stops than progression back. It
               is suggested that this paradigm may be used for the analysis of
               the spatial organization of locomotor behavior in neuroscience
               research.",
  journal   = "Behav. Brain Res.",
  publisher = "tau.ac.il",
  volume    =  34,
  number    =  3,
  pages     = "199--211",
  month     =  sep,
  year      =  1989,
  language  = "en"
}

@ARTICLE{Kimchi2001-oj,
  title     = "Spatial learning and memory in the blind mole-rat in comparison
               with the laboratory rat and Levant vole",
  author    = "Kimchi, Tali and Terkel, Joseph",
  abstract  = "Studies dealing with spatial orientation in mammals have mostly
               dealt with surface-dwelling species. We studied the ability of a
               subterranean rodent to orient in space and compared it with two
               species of rodents that spend most of their lives above ground.
               The solitary blind mole-rat, Spalax ehrenbergi, inhabits an
               extensive, branching tunnel system that it digs itself and in
               which it spends its entire life. We examined its ability to
               learn and remember a winding path towards a goal in a multiple
               labyrinth and compared it with Levant voles, Microtus guentheri,
               and laboratory rats, Rattus norvegicus. The mole-rats learned
               significantly faster than the rats and voles. Furthermore, their
               ability to remember the maze was significantly better than that
               of the rats after 2, 7, 30 and 60 days from the end of the
               learning experiment and significantly better than the voles
               after 120 days. The mole-rats still retained ca. 45\% of their
               optimal performance at the end of the learning experiment after
               4 months compared with 20\% for the voles after 4 months and
               less than 20\% for the rats after 2 months. Despite having lost
               its vision, the mole-rat was thus more able to orient in a
               complex maze than the surface-dwelling vole and laboratory rat.
               We suggest that the mole-rat compensates for the sensory
               limitations imposed by the subterranean niche and for its loss
               of vision by relying on the Earth's magnetic field and internal
               cues to steer its course efficiently. We discuss the possible
               mechanisms of orientation. Copyright 2001 The Association for
               the Study of Animal Behaviour.",
  journal   = "Anim. Behav.",
  publisher = "Elsevier",
  volume    =  61,
  number    =  1,
  pages     = "171--180",
  month     =  jan,
  year      =  2001,
  language  = "en"
}

@ARTICLE{Kimchi2003-xz,
  title     = "Detours by the blind mole-rat follow assessment of location and
               physical properties of underground obstacles",
  author    = "Kimchi, Tali and Terkel, Joseph",
  abstract  = "Orientation by an animal inhabiting an underground environment
               must be extremely efficient if it is to contend effectively with
               the high energetic costs of excavating soil for a tunnel system.
               We examined, in the field, the ability of a fossorial rodent,
               the blind mole-rat, Spalax ehrenbergi, to detour different types
               of obstacles blocking its tunnel and rejoin the disconnected
               tunnel section. To create obstacles, we dug ditches, which we
               either left open or filled with stone or wood. Most (77\%)
               mole-rats reconnected the two parts of their tunnel and
               accurately returned to their orginal path by digging a parallel
               bypass tunnel around the obstacle at a distance of 10--20cm from
               the open ditch boundaries or 3--8cm from the filled ditch
               boundaries. When the ditch was placed asymmetrically across the
               tunnel, the mole-rats detoured around the shorter side. These
               findings demonstrate that mole-rats seem to be able to assess
               the nature of an obstacle ahead and their own distance from the
               obstacle boundaries, as well as the relative location of the far
               section of disconnected tunnel. We suggest that mole-rats mainly
               use reverberating self-produced seismic vibrations as a
               mechanism to determine the size, nature and location of the
               obstacle, as well as internal self-generated references to
               determine their location relative to the disconnected tunnel
               section. Copyright 2003 The Association for the Study of Animal
               Behaviour. Published by Elsevier Ltd. All rights reserved.",
  journal   = "Anim. Behav.",
  publisher = "Elsevier",
  volume    =  66,
  number    =  5,
  pages     = "885--891",
  month     =  nov,
  year      =  2003
}

@ARTICLE{Hennig1976-es,
  title    = "The Effect of Distance Between Predator and Prey and the
              Opportunity to Escape on Tonic Immobility in Anolis Carolinensis",
  author   = "Hennig, Charles W and Dunlap, William P and Gallup, Gordon G",
  abstract = "The idea that tonic immobility (TI) may be a reaction to
              predation has received increasing support in recent years. It
              follows, from this view, that distance between predator and prey
              and opportunity for escape should have predictable effects on
              immobility. The first experiment showed that the presence of
              large bushes, as an explicit escape manipulation, reduced
              immobility durations in anoles (Anolis carolinensis) in
              comparison to what occurred when they were immobilized in an open
              area, with the effect being most evident the closer the predator
              was to the prey. In the second experiment it was shown that close
              proximity between anoles and the experimenter produced longer
              durations of immobility in an open area, while a third experiment
              showed that with bushes nearby this relationship was reversed;
              that is, shorter durations of TI with anoles in close proximity
              to the experimenter.",
  journal  = "Psychol. Rec.",
  volume   =  26,
  number   =  3,
  pages    = "312--320",
  month    =  jul,
  year     =  1976
}

@ARTICLE{Eaton1991-cg,
  title     = "How stimulus direction determines the trajectory of the
               Mauthner-initiated escape response in a teleost fish",
  author    = "Eaton, R C and Emberley, D S",
  abstract  = "Fishes use the Mauthner-initiated C-start for short-latency
               evasion of predators. C-starts consist of a sudden turn (stage
               1) and a rapid acceleration (stage 2). We analyzed high-speed
               cin{\'e} films of goldfish C-starts elicited by dropping a ball
               into the water. It was previously thought that stage 1 angle
               does not vary concomitantly with the angle of the threatening
               stimulus relative to the position of the fish. We found,
               however, a significant inverse relationship between the
               direction of the impact of the ball and the angle turned by the
               end of stage 1. When starting near a wall, or when its usual
               trajectory was blocked by a wall, the fish used an escape route
               that was not predictable from the stimulus angle. The fish did
               not appear to correct its trajectory if it began to turn towards
               the ball. This behavioral evidence supports the previous notion
               that the underlying neural command is ballistic and does not use
               sensory information from the stimulus once the movement begins.
               If this is so, the fish probably utilizes information on
               obstacle location in the interval leading up to the trigger
               stimulus.",
  journal   = "J. Exp. Biol.",
  publisher = "jeb.biologists.org",
  volume    =  161,
  pages     = "469--487",
  month     =  nov,
  year      =  1991,
  language  = "en"
}

@ARTICLE{Herberholz2012-ib,
  title    = "Decision Making and Behavioral Choice during Predator Avoidance",
  author   = "Herberholz, Jens and Marquart, Gregory D",
  abstract = "One of the most important decisions animals have to make is how
              to respond to an attack from a potential predator. The response
              must be prompt and appropriate to ensure survival. Invertebrates
              have been important models in studying the underlying
              neurobiology of the escape response due to their accessible
              nervous systems and easily quantifiable behavioral output.
              Moreover, invertebrates provide opportunities for investigating
              these processes at a level of analysis not available in most
              other organisms. Recently, there has been a renewed focus in
              understanding how value-based calculations are made on the level
              of the nervous system, i.e., when decisions are made under
              conflicting circumstances, and the most desirable choice must be
              selected by weighing the costs and benefits for each behavioral
              choice. This article reviews samples from the current literature
              on anti-predator decision making in invertebrates, from single
              neurons to complex behaviors. Recent progress in understanding
              the mechanisms underlying value-based behavioral decisions is
              also discussed.",
  journal  = "Front. Neurosci.",
  volume   =  6,
  pages    = "125",
  month    =  aug,
  year     =  2012,
  keywords = "behavioral choice; decision making; escape; neural circuits;
              predation",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@MISC{Eason2019-sm,
  title    = "Squirrels Do the Math: Flight Trajectories in Eastern Gray
              Squirrels (Sciurus carolinensis)",
  author   = "Eason, Perri K and Nason, Lindsay D and Alexander, Jr., James E",
  abstract = "Animals are under strong selective pressures to make correct
              decisions when attempting to escape an approaching predator, and
              not surprisingly many studies have shown that animals adjust
              their flight initiation behavior in response to risk. However, we
              have a poor understanding of animals' capability to select an
              appropriate flight trajectory. We investigated whether eastern
              gray squirrels would adjust their flight trajectory based on the
              relative locations of the squirrel, the approaching threat, and
              potential refuges. We used a person running toward a focal
              squirrel (N = 122) as the threat and considered the three trees
              nearest the squirrel and taller than 8 m to be potential refuges.
              Squirrels were strongly affected by the angle () formed by the
              locations of person, squirrel, and the three nearest trees. A
              squirrel was less likely to run to the nearest tree (Tree 1) when
              1 was relatively acute, but also less likely to run to Tree 1
              when 2 was obtuse, making Tree 2 a more attractive refuge. A
              squirrel was more likely to run to Tree 1 if it was close and if
              Tree 2 was relatively far. Subtle differences in the effects of
              1 versus 2 on squirrel refuge choice support the idea that
              squirrels prefer a nearby refuge. Squirrels were more likely to
              select Trees 2 and 3 rather than Tree 1 only when 2 was obtuse
              (105). In contrast, most squirrels chose to run to Tree 1 when
              1 was greater than 65; thus squirrels were more likely to
              choose Tree 1 even when doing so required running at least partly
              toward the approaching threat. The decisions made by focal
              squirrels provide evidence that this species' assessment of risk
              is highly nuanced. A great deal of variation has been reported in
              responses to predators within species. While part of the
              variation may be due to strategic unpredictability on the part of
              the prey, part of it may also be due to differences in flight
              trajectory and refuge preferences that have not been well
              studied.",
  month    =  mar,
  year     =  2019
}

@ARTICLE{Fellini2011-wd,
  title     = "Geometric information is required for allothetic navigation in
               mice",
  author    = "Fellini, Laetitia and Morellini, Fabio",
  abstract  = "In tasks for allothetic navigation, animals should orientate by
               means of distal cues. We have previously shown that mice use
               several forms of information to navigate, among which geometry,
               i.e. the shape of the environment, seems to play an important
               role. Here we investigated whether geometric features of the
               environment are necessary for allothetic navigation in mice.
               Mice were trained to navigate in a circular water maze by means
               of four distal landmarks distributed either symmetrically
               (symmetry group) or asymmetrically (asymmetry group) around the
               maze. Thus, mice could locate a hidden platform by either
               differentiating the landmarks based on their intrinsic features
               (symmetry group) or in addition by geometric information, i.e.
               based on the relative distances between landmarks (asymmetry
               group). Data indicated that place learning occurred only in the
               asymmetry group. The results support the idea that mice navigate
               by using the relational properties between distal landmarks and
               that geometric information is required for proper allothetic
               navigation in this species.",
  journal   = "Behav. Brain Res.",
  publisher = "Elsevier",
  volume    =  222,
  number    =  2,
  pages     = "380--384",
  month     =  sep,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Roberts2007-ec,
  title    = "Rats take correct novel routes and shortcuts in an enclosed maze",
  author   = "Roberts, William A and Cruz, Catherine and Tremblay, Joseph",
  abstract = "In 3 experiments, rats were allowed to travel selected routes
              along the internal alleys of a cross-maze that led from one
              distinctive end box to another. The maze and procedures used were
              designed to control the rats' ability to use intrinsic and
              extrinsic cues to their location in the maze; thus, only the
              internal geometry of the maze could be learned and used to travel
              between one end box and another. After an initial exploration
              phase, rats were given novel routes and shortcut tests that
              involved peripheral alleys not before traveled. Rats chose the
              correct novel path or shortcut significantly above chance on some
              tests in Experiments 1 and 2 and significantly better than a
              control group in Experiment 3. The findings suggest that rats
              were able to compute novel routes and shortcuts within the maze
              on the basis of limited experience with the internal geometry of
              the maze.",
  journal  = "J. Exp. Psychol. Anim. Behav. Process.",
  volume   =  33,
  number   =  2,
  pages    = "79--91",
  month    =  apr,
  year     =  2007,
  language = "en"
}

@ARTICLE{Grieves2013-ji,
  title     = "Cognitive maps and spatial inference in animals: Rats fail to
               take a novel shortcut, but can take a previously experienced one",
  author    = "Grieves, Roderick M and Dudchenko, Paul A",
  abstract  = "Previous work has shown that children are able to make a spatial
               inference about adjacent locations that have only been
               experienced indirectly (Hazen, Lockman, \& Pick, 1978). We
               sought to replicate this finding in rats, on a conceptually
               analogous task. In a first experiment, rats (n=8) were given 110
               training trials on a task in which they entered a series of four
               square environments via connecting alleyways. Following
               training, we conducted a probe session in which the original
               training route was blocked and three novel routes were
               introduced, one of which led directly to the food reward.
               Surprisingly, rats failed to choose this shortcut route over the
               alternative routes. In a second experiment, following additional
               training with a series of platforms that were visible from one
               another, rats again failed to take a shortcut when given the
               opportunity to do so. In a third experiment with naive rats
               (n=11), a shortcut was chosen, but only by rats that were given
               unrewarded preexposure to the shortcut route. These tests
               suggest that, despite their dedicated neural representations of
               location and direction, rats lack the capacity for a novel
               spatial inference. For rats, the use of a shortcut requires
               learning.",
  journal   = "Learn. Motiv.",
  publisher = "Elsevier",
  volume    =  44,
  number    =  2,
  pages     = "81--92",
  month     =  may,
  year      =  2013,
  keywords  = "Tolman; Maier; Cognitive map; Shortcutting; Intramaze landmarks;
               Extramaze landmarks; Spatial inference"
}

@ARTICLE{Morellini2013-qr,
  title    = "Spatial memory tasks in rodents: what do they model?",
  author   = "Morellini, Fabio",
  abstract = "The analysis of spatial learning and memory in rodents is
              commonly used to investigate the mechanisms underlying certain
              forms of human cognition and to model their dysfunction in
              neuropsychiatric and neurodegenerative diseases. Proper
              interpretation of rodent behavior in terms of spatial memory and
              as a model of human cognitive functions is only possible if
              various navigation strategies and factors controlling the
              performance of the animal in a spatial task are taken into
              consideration. The aim of this review is to describe the
              experimental approaches that are being used for the study of
              spatial memory in rats and mice and the way that they can be
              interpreted in terms of general memory functions. After an
              introduction to the classification of memory into various
              categories and respective underlying neuroanatomical substrates,
              I explain the concept of spatial memory and its measurement in
              rats and mice by analysis of their navigation strategies.
              Subsequently, I describe the most common paradigms for spatial
              memory assessment with specific focus on methodological issues
              relevant for the correct interpretation of the results in terms
              of cognitive function. Finally, I present recent advances in the
              use of spatial memory tasks to investigate episodic-like memory
              in mice.",
  journal  = "Cell Tissue Res.",
  volume   =  354,
  number   =  1,
  pages    = "273--286",
  month    =  oct,
  year     =  2013,
  language = "en"
}

@MISC{noauthor_undated-ot,
  title        = "The travelling sales Rat",
  howpublished = "\url{https://iopscience.iop.org/article/10.1088/1741-2560/8/6/065010/pdf?casa_token=9NbJ5AY4fAcAAAAA:wtKCXaD6lR9nIMBH4wCuthuuSp_UhnchIGvU7UldVIyT_Za-XIUFdiascZx3rgBaslD4Py_dQw}",
  note         = "Accessed: 2020-6-4"
}

@ARTICLE{Munteanu2016-dx,
  title    = "Take the long way home: Behaviour of a neotropical frog,
              Allobates femoralis, in a detour task",
  author   = "Munteanu, Alexandru Marian and Starnberger, Iris and Pa{\v
              s}ukonis, Andrius and Bugnyar, Thomas and H{\"o}dl, Walter and
              Fitch, William Tecumseh",
  abstract = "Detour behaviour, an individual's ability to reach its goal by
              taking an indirect route, has been used to test spatial cognitive
              abilities across a variety of taxa. Although many amphibians show
              a strong homing ability, there is currently little evidence of
              amphibian spatial cognitive flexibility. We tested whether a
              territorial frog, Allobates femoralis, can flexibly adjust its
              homing path when faced with an obstacle. We displaced male frogs
              from their calling sites into the centre of circular arenas and
              recorded their escape routes. In the first experiment we provided
              an arena with equally high walls. In the second experiment we
              doubled the height of the homeward facing wall. Finally, we
              provided a tube as a shortcut through the high wall. In the
              equal-height arena, most frogs chose to escape via the quadrant
              facing their former calling site. However, when challenged with
              different heights, nearly all frogs chose the low wall, directing
              their movements away from the calling site. In the ``escape
              tunnel'' experiment most frogs still chose the low wall. Our
              results show that displaced A. femoralis males can flexibly
              adjust their homing path and avoid (presumably energetically
              costly) obstacles, providing experimental evidence of spatial
              cognitive flexibility in an amphibian.",
  journal  = "Behav. Processes",
  volume   =  126,
  pages    = "71--75",
  month    =  may,
  year     =  2016,
  keywords = "Amphibian behaviour; Dendrobatidae; Homing; Obstacle avoidance;
              Spatial cognitive flexibility",
  language = "en"
}

@ARTICLE{Nesterova2009-em,
  title    = "Simple and integrated detours: field tests with Columbian ground
              squirrels",
  author   = "Nesterova, Anna Pavlovna and Hansen, Frank",
  abstract = "An internal representation of space offers flexibility to animals
              during orientation and allows execution of short cuts and
              detours. We tested the ability of 19 free-ranging Columbian
              ground squirrels (Spermophilus columbianus) to perform integrated
              detours that required travelling under- and aboveground.
              Squirrels were individually tested on their territories (2 tests)
              and in an arena (7 tests). During tests, animals could reach food
              by running aboveground and then through tunnels. For the
              territory tests, natural tunnels were available. For the arena
              tests, animals used artificial tunnels within a fenced-in part of
              the meadow. For the last arena test, tubes were placed
              aboveground replicating the underground structure. In this test
              animals were asked to make a simple detour, when the full path to
              the goal was visible. On their territories, 41\% of squirrels
              performed detours. All animals reached the food in the arena.
              When choosing an arena detour, squirrels based their decision on
              the proximity of the burrow as well as on whether it led to food.
              On the last arena test, more squirrels performed correct detours
              on the first attempt compared to other tests. The results suggest
              that ground squirrels can perform simple and integrated detours,
              but animals perform better if the full path is visible.",
  journal  = "Anim. Cogn.",
  volume   =  12,
  number   =  5,
  pages    = "655--670",
  month    =  sep,
  year     =  2009,
  language = "en"
}

@ARTICLE{Floreano2010-wg,
  title    = "Evolution of adaptive behaviour in robots by means of Darwinian
              selection",
  author   = "Floreano, Dario and Keller, Laurent",
  journal  = "PLoS Biol.",
  volume   =  8,
  number   =  1,
  pages    = "e1000292",
  month    =  jan,
  year     =  2010,
  language = "en"
}

@ARTICLE{Cooper1999-nv,
  title     = "Escape behavior by prey blocked from entering the nearest refuge",
  author    = "{Cooper} and {Jr.} and William, E",
  abstract  = "Current models of optimal antipredation behavior do not apply to
               prey blocked by a predator from access to the primary refuge
               because the predator is closer than the optimal approach
               distance and flight toward the refuge would increase risk. If
               other alternative refuges are available, the prey should flee
               toward the best alternative one. I studied the effect of an
               approaching human simulated predator interposed between prey and
               refuge on the use of alternative refuges and on
               flight-initiation distance in the keeled earless lizard,
               Holbrookia propinqua. When the predator approached on a line
               between a lizard and its closest refuge, the lizard invariably
               fled to or toward an alternative refuge. Lizards were
               significantly more likely to use alternative refuges than
               lizards approached on a line connecting the closest refuge,
               prey, and predator, but with the lizard between the predator and
               the refuge. Flight-initiation distance was significantly greater
               for lizards having free access to the closest refuge than for
               those blocked from it, perhaps because of the time required to
               assess the new risk posed by blockage of the closest refuge, to
               select the best alternative refuge, or to wait for the predator
               to commit to a closing pattern before choosing the best flight
               option.",
  journal   = "Can. J. Zool.",
  publisher = "NRC Research Press",
  volume    =  77,
  number    =  4,
  pages     = "671--674",
  month     =  sep,
  year      =  1999
}

@ARTICLE{Kopena2015-jl,
  title     = "Escape strategy of Schreiber's green lizards (Lacerta
               schreiberi) is determined by environment but not season or sex",
  author    = "Kopena, Ren{\'a}ta and Herczeg, G{\'a}bor and L{\'o}pez, Pilar
               and Mart{\'\i}n, Jos{\'e}",
  abstract  = "Antipredator escape behaviour varies with several
               well-established sources of variation ranging from the physical
               environment to reproductive status. However, the relative roles
               of these sources are rarely assessed together. We measured (i)
               the distance to the nearest refuge that Schreiber's green
               lizards, Lacerta schreiberi, maintained before an attack (refuge
               distance) and (ii) the distance lizards allowed a simulated
               predator to approach before fleeing (flight initiation distance,
               FID). Refuge distance was unaffected by studied variables.
               However, FID was positively related to refuge distance on
               grassy, but not on rocky substrates. Furthermore, refuge
               distance and escape angle interacted in a substrate-independent
               manner: lizards allowed predators close when refuges were close
               or when lizards had to flee towards the predator. In contrast,
               neither mating season nor sex affected FID. We suggest that the
               escape strategy of L. schreiberi is determined more by the
               physical environment than by sex or reproductive condition.",
  journal   = "Behaviour",
  publisher = "Brill",
  volume    =  152,
  number    =  11,
  pages     = "1527--1542",
  month     =  jan,
  year      =  2015,
  keywords  = "Biology \& Environmental Sciences; Biology; Journal",
  language  = "en"
}

@ARTICLE{Mattingly2005-qc,
  title    = "The choice of arboreal escape paths and its consequences for the
              locomotor behaviour of four species of Anolis lizards",
  author   = "Mattingly, W Brett and Jayne, Bruce C",
  abstract = "The direction and speed of escape locomotion can affect the
              ability of an animal to evade a predator, and variation in
              habitat structure often affects speed. Consequently, the escape
              paths chosen by animals may affect their performance and
              subsequent survival. Arboreal locomotion is well suited for
              gaining insight into the choice of escape routes because of the
              discrete paths formed by branches. Decreased branch diameter and
              increased angles between branches can significantly decrease
              locomotor speeds, but no previous study has determined whether
              arboreal lizards selectively choose alternative paths. We
              quantified choice of escape paths and locomotor performance of
              four syntopic species of arboreal Anolis lizards in their natural
              habitat and in the laboratory. In the field, species with shorter
              limbs occurred more commonly on narrow perches than did
              long-limbed species, but all species favoured escape paths with
              larger-diameter perches and straighter interperch angles. Thus,
              short-limbed species used narrower perches than long-limbed
              species merely as a result of what they encountered, rather than
              as a result of a biased choice at branching points. In natural
              vegetation, choosing branches with the largest diameter often
              results in the straightest path. However, in the laboratory, most
              lizards preferred large-diameter perches with a sharp turn to
              continuing a straight path onto a small-diameter perch. Although
              an overriding preference for larger perch diameter may optimize
              escape speed within a single perch, a maladaptive side-effect
              could be a compromise of the overall rate of gaining distance
              from starting points in paths with turns.",
  journal  = "Anim. Behav.",
  volume   =  70,
  number   =  6,
  pages    = "1239--1250",
  month    =  dec,
  year     =  2005
}

@ARTICLE{Tajima2019-xa,
  title     = "Optimal policy for multi-alternative decisions",
  author    = "Tajima, Satohiro and Drugowitsch, Jan and Patel, Nisheet and
               Pouget, Alexandre",
  abstract  = "Everyday decisions frequently require choosing among multiple
               alternatives. Yet the optimal policy for such decisions is
               unknown. Here we derive the normative policy for general
               multi-alternative decisions. This strategy requires evidence
               accumulation to nonlinear, time-dependent bounds that trigger
               choices. A geometric symmetry in those boundaries allows the
               optimal strategy to be implemented by a simple neural circuit
               involving normalization with fixed decision bounds and an
               urgency signal. The model captures several key features of the
               response of decision-making neurons as well as the increase in
               reaction time as a function of the number of alternatives, known
               as Hick's law. In addition, we show that in the presence of
               divisive normalization and internal variability, our model can
               account for several so-called 'irrational' behaviors, such as
               the similarity effect as well as the violation of both the
               independence of irrelevant alternatives principle and the
               regularity principle.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  22,
  number    =  9,
  pages     = "1503--1511",
  month     =  sep,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Cooper1997-wy,
  title     = "Escape by a refuging prey, the broad-headed skink (Eumeces
               laticeps)",
  author    = "Cooper, Jr., William E",
  abstract  = "Factors influencing escape to refuge by the broad-headed skink
               (Eumeces laticeps) were examined by multiple regression and
               correlation of quantitative escape variables and distance and
               direction to refuge. I simulated a predator by walking toward a
               lizard and recorded aspects of escape. Approach distance
               (distance from me when escape began) increased with distance and
               angle to refuge, suggesting that the skinks assessed that risk
               increased with relative times required for prey and predator to
               reach the refuge. Distance fled was affected jointly by distance
               from the predator when escape began and distance to refuge; it
               increased with distance to refuge. It also increased with the
               angle between the predator's path and refuge due to declining
               distance from the predator per unit distance fled. Direction to
               the nearest refuge and direction fled were nearly identical.
               Distance and direction to refuge should strongly affect escape
               behaviour in prey that are active some distance from refuges but
               rely on them to avoid predation. These relationships may be
               weaker or absent in anachoric species (those nearly continuously
               occupying refuges) and those remaining close to refuges, as well
               as in species relying more on speed and fleeing for long
               distances than on refuges.",
  journal   = "Can. J. Zool.",
  publisher = "NRC Research Press",
  volume    =  75,
  number    =  6,
  pages     = "943--947",
  month     =  jun,
  year      =  1997
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Domenici2010-ma,
  title     = "Context-dependent variability in the components of fish escape
               response: integrating locomotor performance and behavior",
  author    = "Domenici, Paolo",
  abstract  = "Escape responses are used by most fish species in order to avoid
               predation. Escape responses include a number of behavioral and
               kinematic components, such as responsiveness, reaction distance,
               escape latency, directionality, and distance‐derived
               performance. All of these components can contribute to escape
               success. Work on the context‐dependent variability has focused
               on reaction distance, and suggests that this component is
               largely determined by the relative cost and benefits of escaping
               (economic …",
  journal   = "J. Exp. Zool. A Ecol. Genet. Physiol.",
  publisher = "Wiley Online Library",
  volume    =  313,
  number    =  2,
  pages     = "59--79",
  year      =  2010
}

@ARTICLE{Husak2006-yq,
  title     = "Does survival depend on how fast you can run or how fast you do
               run?",
  author    = "Husak, J F",
  abstract  = "Summary 1 Natural selection is generally thought to operate on
               organisms? maximal abilities to perform ecological tasks in
               nature (i.e. whole-animal performance). However, selection may
               instead operate on the manner in which that performance trait is
               used (i.e. ?ecological performance?). 2 I tested whether
               survival of adult Collared Lizards (Crotaphytus collaris)
               depended on maximal sprint speed capacity or on the speed at
               which they actually performed two important ecological tasks:
               chasing a prey item and escaping a predator. 3 Maximal sprint
               speed did not significantly predict annual survival as
               determined by daily censuses of the site the following season,
               nor did speed while foraging, but speed while escaping a
               predator did. Survival also was positively related to the
               proportion of maximal capacity used while escaping. 4 These
               results suggest that selection may operate on ecological
               performance that is constrained, but not necessarily determined,
               by maximal performance capacity, suggesting that researchers
               should consider how organisms utilize maximal performance in
               nature when testing for a performance?survival relationship.",
  journal   = "Funct. Ecol.",
  publisher = "Wiley Online Library",
  volume    =  20,
  number    =  6,
  pages     = "1080--1086",
  month     =  dec,
  year      =  2006
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Barthas2017-zs,
  title     = "Secondary motor cortex: where `sensory'meets `motor'in the
               rodent frontal cortex",
  author    = "Barthas, Florent and Kwan, Alex C",
  abstract  = "In rodents, the medial aspect of the secondary motor cortex (M2)
               is known by other names, including medial agranular cortex
               (AGm), medial precentral cortex (PrCm), and frontal orienting
               field (FOF). As a subdivision of the medial prefrontal cortex
               (mPFC), M2 can be defined by a distinct set of afferent and
               efferent connections, microstimulation responses, and lesion
               outcomes. However, the behavioral role of M2 remains mysterious.
               Here, we focus on evidence from rodent studies, highlighting
               recent findings of early and context …",
  journal   = "Trends Neurosci.",
  publisher = "Elsevier",
  volume    =  40,
  number    =  3,
  pages     = "181--193",
  year      =  2017,
  keywords  = "To Read"
}

@ARTICLE{Tchernichovski1995-qv,
  title    = "A phase plane representation of rat exploratory behavior",
  author   = "Tchernichovski, O and Golani, I",
  abstract = "Rat spontaneous spatial behavior is considered to be stochastic
              and is therefore commonly analyzed in terms of cumulative
              measures. Here, we suggest a method which generates a
              moment-to-moment representation of this behavior. It has been
              proposed earlier that rat spatial behavior can be partitioned
              into natural units termed excursions (round trips) performed from
              a reference place termed the rat's home base. We offer a phase
              plane representation of excursions (plotting the rat's momentary
              location against its momentary velocity). The results reveal a
              geometrical pattern, typical of young age and early exposure. It
              consists of low velocity and intermittent progression while
              moving away from the home base (upstream segment), and high
              velocity while moving back to it (downstream segment). The
              asymmetry between the two segments defines a field of
              significance in the rat's operational world. This field undergoes
              regular transformations, revealing thereby the rat's strategy of
              occupancy of the environment. The presented dynamics could
              provide a framework for the interpretation of concurrent neural
              events associated with navigation and spatial memory.",
  journal  = "J. Neurosci. Methods",
  volume   =  62,
  number   = "1-2",
  pages    = "21--27",
  month    =  nov,
  year     =  1995,
  language = "en"
}

@MISC{noauthor_undated-wh,
  title = "{PIC88.pdf}"
}

@ARTICLE{Egnor2017-sl,
  title    = "Spatial Memory: Mice Quickly Learn a Safe Haven",
  author   = "Egnor, S E Roian",
  abstract = "New work on innate escape behavior shows that mice spontaneously
              form a spatially precise memory of the location of shelter, which
              is laid down quickly and updated continuously.",
  journal  = "Curr. Biol.",
  volume   =  27,
  number   =  10,
  pages    = "R388--R390",
  month    =  may,
  year     =  2017,
  language = "en"
}

@ARTICLE{Li2018-zt,
  title    = "Modulation of Innate Defensive Responses by Locus
              {Coeruleus-Superior} Colliculus Circuit",
  author   = "Li, Lei and Wang, Liping",
  abstract = "Among key survival circuits, defensive response circuits are one
              of the most intensively studied. A consensus is emerging that
              multiple, independent circuitries are involved in different
              conditioned and unconditioned defensive responses. Investigating
              these well-conserved defensive responses would help us to
              decipher the basic working mechanism of the brain at a circuitry
              level and thus shed light on new diagnoses and treatments for
              neural diseases and disorders. We showed that the visually evoked
              innate defensive response was modulated by a locus
              coeruleus-superior colliculus (LC-SC) projection. Our work
              demonstrates that as conserved and instinctive as the survival
              circuits are, they are flexible and subject to fine-tuned
              modulation by experience or internal states of the animals. Here,
              we provide more data to further discuss the possible downstream
              mechanisms of the LC-SC pathway for this important modulation of
              the defensive response, the wide range of flight latency between
              individual flight responses, and the interpretations of our data
              with additional statistical analysis.",
  journal  = "J. Exp. Neurosci.",
  volume   =  12,
  pages    = "1179069518792035",
  month    =  aug,
  year     =  2018,
  keywords = "Locus coeruleus; defensive circuitry; looming; modulation;
              norepinephrine; stress; superior colliculus",
  language = "en"
}

@ARTICLE{Gentry1964-sw,
  title     = "Homing in the {Old-Field} Mouse",
  author    = "Gentry, John B",
  abstract  = "Abstract. Homing was successful in 31 of 39 old-field mice
               (Peromyscus polionotus) released from the center of a 9-acre
               plowed field 340 to 640 feet from trap",
  journal   = "J. Mammal.",
  publisher = "Oxford Academic",
  volume    =  45,
  number    =  2,
  pages     = "276--283",
  month     =  may,
  year      =  1964
}

@UNPUBLISHED{Seidenbecher2019-im,
  title    = "Foraging fruit flies mix navigational and learning-based
              decision-making strategies",
  author   = "Seidenbecher, Sophie E and Sanders, Joshua I and von Philipsborn,
              Anne C and Kvitsiani, Duda",
  abstract = "Abstract Animals often navigate environments that are uncertain,
              volatile and complex, making it challenging to locate reliable
              food sources. Therefore, it is not surprising that many species
              evolved multiple, parallel and complementary foraging strategies
              to survive. Current research on animal behavior is largely driven
              by a reductionist approach and attempts to study one particular
              aspect of behavior in isolation. This is justified by the huge
              success of past and current research in understanding neural
              circuit mechanisms of behaviors. But focusing on only one aspect
              of behaviors obscures their inherent multidimensional nature. To
              fill this gap we aimed to identify and characterize distinct
              behavioral modules using a simple reward foraging assay. For this
              we developed a single-animal, trial-based probabilistic foraging
              task, where freely walking fruit flies experience optogenetic
              sugar-receptor neuron stimulation. By carefully analyzing the
              walking trajectories of flies, we were able to dissect the
              animals foraging decisions into multiple underlying systems. We
              show that flies perform local searches, cue-based navigation and
              learn task relevant contingencies. Using probabilistic reward
              delivery allowed us to bid several competing reinforcement
              learning (RL) models against each other. We discover that flies
              accumulate chosen option values, forget unchosen option values
              and seek novelty. We further show that distinct behavioral
              modules -learning and navigation-based systems-cooperate,
              suggesting that reinforcement learning in flies operates on
              dimensionality reduced representations. We therefore argue that
              animals will apply combinations of multiple behavioral strategies
              to generate foraging decisions.",
  journal  = "bioRxiv",
  pages    = "842096",
  month    =  nov,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Kaplan2017-ez,
  title    = "Planning and navigation as active inference",
  author   = "Kaplan, Raphael and Friston, Karl J",
  abstract = "Abstract This paper introduces an active inference formulation of
              planning and navigation. It illustrates how the
              exploitation--exploration dilemma is dissolved by acting to
              minimise uncertainty (i.e., expected surprise or free energy). We
              use simulations of a maze problem to illustrate how agents can
              solve quite complicated problems using context sensitive prior
              preferences to form subgoals. Our focus is on how epistemic
              behaviour -- driven by novelty and the imperative to reduce
              uncertainty about the world -- contextualises pragmatic or
              goal-directed behaviour. Using simulations, we illustrate the
              underlying process theory with synthetic behavioural and
              electrophysiological responses during exploration of a maze and
              subsequent navigation to a target location. An interesting
              phenomenon that emerged from the simulations was a putative
              distinction between `place cells' -- that fire when a subgoal is
              reached -- and `path cells' -- that fire until a subgoal is
              reached.",
  journal  = "bioRxiv",
  pages    = "230599",
  month    =  dec,
  year     =  2017,
  language = "en"
}

@UNPUBLISHED{Sutton2018-vu,
  title    = "Born to run? Quantifying the balance of prior bias and new
              information in prey escape decisions",
  author   = "Sutton, Nicholas M and O'Dwyer, James P",
  abstract = "Abstract Animal behaviors can often be challenging to model and
              predict, though optimality theory has improved our ability to do
              so. While many qualitative predictions of behavior exist,
              accurate quantitative models, tested by empirical data, are often
              lacking. This is likely due to variation in biases across
              individuals and variation in the way new information is gathered
              and used. We propose a modeling framework based on a novel
              interpretation of Bayes' theorem to integrate optimization of
              energetic constraints with both prior biases and specific sources
              of new information gathered by individuals. We present methods
              for inferring distributions of prior biases within populations
              rather than assuming known priors, as is common in Bayesian
              approaches to modelling behavior, and for evaluating the goodness
              of fit of overall model descriptions. We apply this framework to
              predict optimal escape during predator-prey encounters, based on
              prior biases and variation in what information prey use. Using
              this approach we collected and analyzed data characterizing
              white-tailed deer (Odocoileus virginianus) escape behavior in
              response to human approaches. We found that distance to predator
              alone was not sufficient for predicting deer flight response, and
              have shown that the inclusion of additional information is
              necessary. Additionally, we compared differences in the inferred
              distributions of prior biases across different populations and
              discuss the possible role of human activity in influencing these
              distributions.",
  journal  = "bioRxiv",
  pages    = "297218",
  month    =  apr,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Vale2020-yy,
  title    = "A cortico-collicular circuit for accurate orientation to shelter
              during escape",
  author   = "Vale, Ruben and Campagner, Dario and Iordanidou, Panagiota and
              Arocas, Oriol Pav{\'o}n and Tan, Yu Lin and Vanessa Stempel, A
              and Keshavarzi, Sepideh and Petersen, Rasmus S and Margrie, Troy
              W and Branco, Tiago",
  abstract = "When faced with predatorial threats, escaping towards shelter is
              an adaptive action that offers long-term protection against the
              attacker. From crustaceans to mammals, animals rely on knowledge
              of safe locations in the environment to rapidly execute
              shelter-directed escape actions[1][1]--[3][2]. While previous
              work has identified neural mechanisms of instinctive
              escape[4][3]--[9][4], it is not known how the escape circuit
              incorporates spatial information to execute rapid and accurate
              flights to safety. Here we show that mouse retrosplenial cortex
              (RSP) and superior colliculus (SC) form a monosynaptic circuit
              that continuously encodes the shelter direction. Inactivation of
              SC-projecting RSP neurons decreases SC shelter-direction tuning
              while preserving SC motor function. Moreover, specific
              inactivation of RSP input onto SC neurons disrupts orientation
              and subsequent escapes to shelter, but not orientation accuracy
              to a sensory cue. We conclude that the RSC-SC circuit supports an
              egocentric representation of shelter direction and is necessary
              for optimal shelter-directed escapes. This cortical-subcortical
              interface may be a general blueprint for increasing the
              sophistication and flexibility of instinctive behaviours. \#\#\#
              Competing Interest Statement The authors have declared no
              competing interest. [1]: \#ref-1 [2]: \#ref-3 [3]: \#ref-4 [4]:
              \#ref-9",
  journal  = "bioRxiv",
  pages    = "2020.05.26.117598",
  month    =  may,
  year     =  2020,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@UNPUBLISHED{Kawabata2020-yt,
  title    = "Geometrical model explains multiple preferred escape trajectories
              of fish",
  author   = "Kawabata, Yuuki and Akada, Hideyuki and Shimatani, Ken-Ichiro and
              Nishihara, Gregory N and Kimura, Hibiki and Nozomi, Nishiumi and
              Domenici, Paolo",
  abstract = "Abstract To evade predators, many prey perform rapid escape
              movements. The resulting escape trajectory (ET) -- measured as
              the angle of escape direction relative to the predator's approach
              path -- plays a major role in avoiding predation. Previous
              geometrical models predict a single ET; however, many animals
              (fish and other animal taxa) show highly variable ETs with
              multiple preferred directions. Although such a high ET
              variability may confer unpredictability, preventing predators
              from adopting counter-strategies, the reasons why animals prefer
              specific multiple ETs remain unclear. Here, we constructed a
              novel geometrical model in which Tdiff (the time difference
              between the prey entering the safety zone and the predator
              reaching that entry point) is expected to be maximized. We tested
              this prediction by analyzing the escape responses of Pagrus major
              attacked by a dummy predator. At each initial body orientation of
              the prey relative to the predator, our model predicts a
              multimodal ET with an optimal ET at the maximum Tdiff (Tdiff,1)
              and a suboptimal ET at a second local maximum of Tdiff (Tdiff,2).
              Our experiments show that when Tdiff, 1--Tdiff, 2 is negligible,
              the prey uses optimal or suboptimal ETs to a similar extent, in
              line with the idea of unpredictability. The experimentally
              observed ET distribution is consistent with the model, showing
              two large peaks at 110--130° and 170--180° away from the
              predator. Because various animal taxa show multiple preferred ETs
              similar to those observed here, this behavioral phenotype may
              result from convergent evolution that combines maximal Tdiff with
              a high level of unpredictability.Significance Statement Animals
              from many taxa escape from suddenly approaching threats, such as
              ambush predators, by using multiple preferred escape
              trajectories. However, the reason why these multiple preferred
              escape trajectories are used is still unknown. By fitting a newly
              constructed model to the empirical escape response data, we show
              that the seemingly complex multiple preferred escape trajectories
              can arise from a simple geometrical rule which maximizes the time
              difference between when the prey enters the safety zone and when
              the predator reaches that entry point. Our results open new
              avenues of investigation for understanding how animals choose
              their escape trajectories from behavioral and neurosensory
              perspectives.",
  journal  = "bioRxiv",
  pages    = "2020.04.27.049833",
  month    =  apr,
  year     =  2020,
  language = "en"
}

@ARTICLE{Olson2020-lm,
  title     = "Secondary Motor Cortex Transforms Spatial Information into
               Planned Action during Navigation",
  author    = "Olson, Jacob M and Li, Jamie K and Montgomery, Sarah E and Nitz,
               Douglas A",
  abstract  = "Fluid navigation requires constant updating of planned movements
               to adapt to evolving obstacles and goals. For that reason, a
               neural substrate for navigation demands spatial and
               environmental information and the ability to effect actions
               through efferents. The secondary motor cortex (M2) is a prime
               candidate for this role given its interconnectivity with
               association cortices that encode spatial relationships and its
               projection to the primary motor cortex. Here, we report that M2
               neurons robustly encode both planned and current left/right
               turning actions across multiple turn locations in a multi-route
               navigational task. Comparisons within a common statistical
               framework reveal that M2 neurons differentiate contextual
               factors, including environmental position, route, action
               sequence, orientation, and choice availability. Despite
               significant modulation by environmental factors, action
               planning, and execution are the dominant output signals of M2
               neurons. These results identify the M2 as a structure
               integrating spatial information toward the updating of planned
               movements.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  30,
  number    =  10,
  pages     = "1845--1854.e4",
  month     =  may,
  year      =  2020,
  keywords  = "M2; action; allocentric; cortical circuits; decision making;
               egocentric; in vivo electrophysiology; navigation; parietal
               cortex; retrosplenial cortex; systems neuroscience;Locomotion",
  language  = "en"
}

@ARTICLE{Jordan2008-dx,
  title     = "Descending command systems for the initiation of locomotion in
               mammals",
  author    = "Jordan, Larry M and Liu, Jun and Hedlund, Peter B and Akay,
               Turgay and Pearson, Keir G",
  abstract  = "Neurons in the brainstem implicated in the initiation of
               locomotion include glutamatergic, noradrenergic (NA),
               dopaminergic (DA), and serotonergic (5-HT) neurons giving rise
               to descending tracts. Glutamate antagonists block mesencephalic
               locomotor region-induced and spontaneous locomotion, and
               glutamatergic agonists induce locomotion in spinal animals. NA
               and 5-HT inputs to the spinal cord originate in the brainstem,
               while the descending dopaminergic pathway originates in the
               hypothalamus. Agonists acting at NA, DA or 5-HT receptors
               facilitate or induce locomotion in spinal animals. 5-HT neurons
               located in the parapyramidal region (PPR) produce locomotion
               when stimulated in the isolated neonatal rat brainstem-spinal
               cord preparation, and they constitute the first anatomically
               discrete group of spinally-projecting neurons demonstrated to be
               involved in the initiation of locomotion in mammals. Neurons in
               the PPR are activated during treadmill locomotion in adult rats.
               Locomotion evoked from the PPR is mediated by 5-HT(7) and
               5-HT(2A) receptors, and 5-HT(7) antagonists block locomotion in
               cat, rat and mouse preparations, but have little effect in mice
               lacking 5-HT(7) receptors. 5-HT induced activity in 5-HT(7)
               knockout mice is rhythmic, but coordination among flexor and
               extensor motor nuclei and left and right sides of the spinal
               cord is disrupted. In the adult wild-type mouse, 5-HT(7)
               receptor antagonists impair locomotion, producing patterns of
               activity resembling those induced by 5-HT in 5-HT(7) knockout
               mice. 5-HT(7) receptor antagonists have a reduced effect on
               locomotion in adult 5-HT(7) receptor knockout mice. We conclude
               that the PPR is the source of a descending 5-HT command pathway
               that activates the CPG via 5-HT(7) and 5-HT(2A) receptors.
               Further experiments are necessary to define the putative
               glutamatergic, DA, and NA command pathways.",
  journal   = "Brain Res. Rev.",
  publisher = "Elsevier",
  volume    =  57,
  number    =  1,
  pages     = "183--191",
  month     =  jan,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Kaneshige2018-cg,
  title     = "A Descending Circuit Derived From the Superior Colliculus
               Modulates Vibrissal Movements",
  author    = "Kaneshige, Miki and Shibata, Ken-Ichi and Matsubayashi, Jun and
               Mitani, Akira and Furuta, Takahiro",
  abstract  = "The superior colliculus (SC) is an essential structure for the
               control of eye movements. In rodents, the SC is also considered
               to play an important role in whisking behavior, in which animals
               actively move their vibrissae (mechanosensors) to gather tactile
               information about the space around them during exploration. We
               investigated how the SC contributes to vibrissal movement
               control. We found that when the SC was unilaterally lesioned,
               the resting position of the vibrissae shifted backward on the
               side contralateral to the lesion. The unilateral SC lesion also
               induced an increase in the whisking amplitude on the
               contralateral side. To explore the anatomical basis for SC
               involvement in vibrissal movement control, we then
               quantitatively evaluated axonal projections from the SC to the
               brainstem using neuronal labeling with a virus vector. Neurons
               of the SC mainly sent axons to the contralateral side in the
               lower brainstem. We found that the facial nucleus received input
               directly from the SC, and that the descending projections from
               the SC also reached the intermediate reticular formation and
               pre-B{\"o}tzinger complex, which are both considered to contain
               neural oscillators generating rhythmic movements of the
               vibrissae. Together, these results indicate the existence of a
               neural circuit in which the SC modulates vibrissal movements
               mainly on the contralateral side, via direct connections to
               motoneurons, and via indirect connections including the central
               pattern generators.",
  journal   = "Front. Neural Circuits",
  publisher = "frontiersin.org",
  volume    =  12,
  pages     = "100",
  month     =  nov,
  year      =  2018,
  keywords  = "CPGs; anterograde tracing; kinematic analysis; premotor neurons;
               rat; whisker",
  language  = "en"
}

@ARTICLE{Ryczko2013-pw,
  title     = "The multifunctional mesencephalic locomotor region",
  author    = "Ryczko, Dimitri and Dubuc, R{\'e}jean",
  abstract  = "In 1966, Shik, Severin and Orlovskii discovered that electrical
               stimulation of a region at the junction between the midbrain and
               hindbrain elicited controlled walking and running in the cat.
               The region was named Mesencephalic Locomotor Region (MLR). Since
               then, this locomotor center was shown to control locomotion in
               various vertebrate species, including the lamprey, salamander,
               stingray, rat, guinea-pig, rabbit or monkey. In human subjects
               asked to imagine they are walking, there is an increased
               activity in brainstem nuclei corresponding to the MLR (i.e.
               pedunculopontine, cuneiform and subcuneiform nuclei). Clinicians
               are now stimulating (deep brain stimulation) structures
               considered to be part of the MLR to alleviate locomotor symptoms
               of patients with Parkinson's disease. However, the anatomical
               constituents of the MLR still remain a matter of debate,
               especially relative to the pedunculopontine, cuneiform and
               subcuneiform nuclei. Furthermore, recent studies in lampreys
               have revealed that the MLR is more complex than a simple relay
               in a serial descending pathway activating the spinal locomotor
               circuits. It has multiple functions. Our goal is to review the
               current knowledge relative to the anatomical constituents of the
               MLR, and its physiological role, from lamprey to man. We will
               discuss these results in the context of the recent clinical
               studies involving stimulation of the MLR in patients with
               Parkinson's disease.",
  journal   = "Curr. Pharm. Des.",
  publisher = "ingentaconnect.com",
  volume    =  19,
  number    =  24,
  pages     = "4448--4470",
  year      =  2013,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Basso2017-nd,
  title     = "Circuits for Action and Cognition: A View from the Superior
               Colliculus",
  author    = "Basso, Michele A and May, Paul J",
  abstract  = "The superior colliculus is one of the most well-studied
               structures in the brain, and with each new report, its proposed
               role in behavior seems to increase in complexity. Forty years of
               evidence show that the colliculus is critical for reorienting an
               organism toward objects of interest. In monkeys, this involves
               saccadic eye movements. Recent work in the monkey colliculus and
               in the homologous optic tectum of the bird extends our
               understanding of the role of the colliculus in higher mental
               functions, such as attention and decision making. In this
               review, we highlight some of these recent results, as well as
               those capitalizing on circuit-based methodologies using
               transgenic mice models, to understand the contribution of the
               colliculus to attention and decision making. The wealth of
               information we have about the colliculus, together with new
               tools, provides a unique opportunity to obtain a detailed
               accounting of the neurons, circuits, and computations that
               underlie complex behavior.",
  journal   = "Annu Rev Vis Sci",
  publisher = "annualreviews.org",
  volume    =  3,
  pages     = "197--226",
  month     =  sep,
  year      =  2017,
  keywords  = "attention; decision making; movement; normalization; orienting;
               population coding; saccades; vision",
  language  = "en"
}

@ARTICLE{Wolf2015-dq,
  title     = "An integrative role for the superior colliculus in selecting
               targets for movements",
  author    = "Wolf, Andrew B and Lintz, Mario J and Costabile, Jamie D and
               Thompson, John A and Stubblefield, Elizabeth A and Felsen, Gidon",
  abstract  = "A fundamental goal of systems neuroscience is to understand the
               neural mechanisms underlying decision making. The midbrain
               superior colliculus (SC) is known to be central to the selection
               of one among many potential spatial targets for movements, which
               represents an important form of decision making that is
               tractable to rigorous experimental investigation. In this
               review, we first discuss data from mammalian models-including
               primates, cats, and rodents-that inform our understanding of how
               neural activity in the SC underlies the selection of targets for
               movements. We then examine the anatomy and physiology of inputs
               to the SC from three key regions that are themselves implicated
               in motor decisions-the basal ganglia, parabrachial region, and
               neocortex-and discuss how they may influence SC activity related
               to target selection. Finally, we discuss the potential for
               methodological advances to further our understanding of the
               neural bases of target selection. Our overarching goal is to
               synthesize what is known about how the SC and its inputs act
               together to mediate the selection of targets for movements, to
               highlight open questions about this process, and to spur future
               studies addressing these questions.",
  journal   = "J. Neurophysiol.",
  publisher = "physiology.org",
  volume    =  114,
  number    =  4,
  pages     = "2118--2131",
  month     =  oct,
  year      =  2015,
  keywords  = "decision making; laterodorsal tegmental nucleus; motor planning;
               pedunculopontine tegmental nucleus; substantia nigra",
  language  = "en"
}

@ARTICLE{Grillner2008-ev,
  title     = "Neural bases of goal-directed locomotion in vertebrates---An
               overview",
  author    = "Grillner, Sten and Wall{\'e}n, Peter and Saitoh, Kazuya and
               Kozlov, Alexander and Robertson, Brita",
  abstract  = "The different neural control systems involved in goal-directed
               vertebrate locomotion are reviewed. They include not only the
               central pattern generator networks in the spinal cord that
               generate the basic locomotor synergy and the brainstem command
               systems for locomotion but also the control systems for steering
               and control of body orientation (posture) and finally the neural
               structures responsible for determining which motor programs
               should be turned on in a given instant. The role of the basal
               ganglia is considered in this context. The review summarizes the
               available information from a general vertebrate perspective, but
               specific examples are often derived from the lamprey, which
               provides the most detailed information when considering cellular
               and network perspectives.",
  journal   = "Brain Res. Rev.",
  publisher = "Elsevier",
  volume    =  57,
  number    =  1,
  pages     = "2--12",
  month     =  jan,
  year      =  2008,
  keywords  = "Basal ganglia; Lamprey; Central pattern generator; Tectum; Brain
               stem--spinal cord; Modeling"
}

@ARTICLE{Drew2004-kl,
  title     = "Cortical and brainstem control of locomotion",
  author    = "Drew, Trevor and Prentice, Stephen and Schepens,
               B{\'e}n{\'e}dicte",
  abstract  = "While a basic locomotor rhythm is centrally generated by spinal
               circuits, descending pathways are critical for ensuring
               appropriate anticipatory modifications of gait to accommodate
               uneven terrain. Neurons in the motor cortex command the changes
               in muscle activity required to modify limb trajectory when
               stepping over obstacles. Simultaneously, neurons in the
               brainstem reticular formation ensure that these modifications
               are superimposed on an appropriate base of postural support.
               Recent experiments suggest that the same neurons in the same
               structures also provide similar information during reaching
               movements. It is suggested that, during both locomotion and
               reaching movements, the final expression of descending signals
               is influenced by the state and excitability of the spinal
               circuits upon which they impinge.",
  journal   = "Prog. Brain Res.",
  publisher = "Elsevier",
  volume    =  143,
  pages     = "251--261",
  year      =  2004,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Warren2019-lv,
  title    = "{Non-Euclidean} navigation",
  author   = "Warren, William H",
  abstract = "A basic set of navigation strategies supports navigational tasks
              ranging from homing to novel detours and shortcuts. To perform
              these last two tasks, it is generally thought that humans,
              mammals and perhaps some insects possess Euclidean cognitive
              maps, constructed on the basis of input from the path integration
              system. In this article, I review the rationale and behavioral
              evidence for this metric cognitive map hypothesis, and find it
              unpersuasive: in practice, there is little evidence for truly
              novel shortcuts in animals, and human performance is highly
              unreliable and biased by environmental features. I develop the
              alternative hypothesis that spatial knowledge is better
              characterized as a labeled graph: a network of paths between
              places augmented with local metric information. What
              distinguishes such a cognitive graph from a metric cognitive map
              is that this local information is not embedded in a global
              coordinate system, so spatial knowledge is often geometrically
              inconsistent. Human path integration appears to be better suited
              to piecewise measurements of path lengths and turn angles than to
              building a consistent map. In a series of experiments in
              immersive virtual reality, we tested human navigation in
              non-Euclidean environments and found that shortcuts manifest
              large violations of the metric postulates. The results are
              contrary to the Euclidean map hypothesis and support the
              cognitive graph hypothesis. Apparently Euclidean behavior, such
              as taking novel detours and approximate shortcuts, can be
              explained by the adaptive use of non-Euclidean strategies.",
  journal  = "J. Exp. Biol.",
  volume   =  222,
  number   = "Pt Suppl 1",
  month    =  feb,
  year     =  2019,
  keywords = "Cognitive graph; Cognitive map; Path integration; Spatial
              cognition; Wayfinding",
  language = "en"
}

@ARTICLE{Ericson2020-rz,
  title    = "Probing the invariant structure of spatial knowledge: Support for
              the cognitive graph hypothesis",
  author   = "Ericson, Jonathan D and Warren, William H",
  abstract = "We tested four hypotheses about the structure of spatial
              knowledge used for navigation: (1) the Euclidean hypothesis, a
              geometrically consistent map; (2) the Neighborhood hypothesis,
              adjacency relations between spatial regions, based on visible
              boundaries; (3) the Cognitive Graph hypothesis, a network of
              paths between places, labeled with approximate local distances
              and angles; and (4) the Constancy hypothesis, whatever geometric
              properties are invariant during learning. In two experiments,
              different groups of participants learned three virtual hedge
              mazes, which varied specific geometric properties (Euclidean
              Control Maze, Elastic Maze with stretching paths, Swap Maze with
              alternating paths to the same place). Spatial knowledge was then
              tested using three navigation tasks (metric shortcuts on empty
              ground plane, neighborhood shortcuts with visible boundaries,
              route task in corridors). They yielded the following results: (a)
              Metric shortcuts were insensitive to detectable shifts in target
              location, inconsistent with the Euclidean hypothesis. (b)
              Neighborhood shortcuts were constrained by visible boundaries in
              the Elastic Maze, but not in the Swap Maze, contrary to the
              Neighborhood and Constancy hypotheses. (c) The route task
              indicated that a graph of the maze was acquired in all
              environments, including knowledge of local path lengths. We
              conclude that primary spatial knowledge is consistent with the
              Cognitive Graph hypothesis. Neighborhoods are derived from the
              graph, and local distance and angle information is not embedded
              in a geometrically consistent map.",
  journal  = "Cognition",
  volume   =  200,
  pages    = "104276",
  month    =  may,
  year     =  2020,
  keywords = "Cognitive graph; Cognitive map; Human navigation; Spatial
              cognition",
  language = "en"
}

@UNPUBLISHED{Duan2019-cb,
  title    = "A cortico-collicular pathway for motor planning in a
              memory-dependent perceptual decision task",
  author   = "Duan, Chunyu A and Pan, Yuxin and Ma, Guofen and Zhou, Taotao and
              Zhang, Siyu and Xu, Ning-Long",
  abstract = "ABSTRACT Survival in a dynamic environment requires animals to
              plan future actions based on past sensory evidence. However, the
              neural circuit mechanism underlying this crucial brain function,
              referred to as motor planning, remains unclear. Here, we employ
              projection-specific imaging and perturbation methods to
              investigate the direct pathway linking two key nodes in the motor
              planning network, the secondary motor cortex (M2) and the
              midbrain superior colliculus (SC), in mice performing a
              memory-dependent perceptual decision task. We find dynamic coding
              of choice information in SC-projecting M2 neurons during motor
              planning and execution, and disruption of this information by
              inhibiting M2 terminals in SC selectively impaired decision
              maintenance. Furthermore, cell-type-specific optogenetic circuit
              mapping shows that M2 terminals modulate both excitatory and
              inhibitory SC neurons with balanced synaptic strength. Together,
              our results reveal the dynamic recruitment of the
              premotor-collicular pathway as a circuit mechanism for motor
              planning.",
  journal  = "bioRxiv",
  pages    = "709170",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Adam2020-zd,
  title    = "Cortico-subthalamic projections send brief stop signals to halt
              visually-guided locomotion",
  author   = "Adam, Elie M and Johns, Taylor and Sur, Mriganka",
  abstract = "Summary Goal-directed locomotion necessitates control signals
              that propagate from higher-order areas to regulate spinal
              mechanisms. The cortico-subthalamic hyperdirect pathway offers a
              short route for cortical information to reach locomotor centers
              in the brainstem. We developed a task where head-fixed mice run
              to a visual landmark, then stop and wait to collect reward, and
              examined the role of secondary motor cortex (M2) projections to
              the subthalamic nucleus (STN) in controlling locomotion. Our
              modeled behavioral strategy indicates a switching point in
              behavior, suggesting a critical neuronal control signal at stop
              locations. Optogenetic activation of M2 axons in STN leads the
              animal to stop prematurely. By imaging M2 neurons projecting to
              STN, we find neurons that are active at the onset of stops, when
              executed at the landmark but not spontaneously elsewhere. Our
              results suggest that the M2-STN pathway can be recruited during
              visually-guided locomotion to rapidly and precisely control the
              mesencephalic locomotor region through the basal ganglia.",
  journal  = "bioRxiv",
  pages    = "2020.02.05.936443",
  month    =  feb,
  year     =  2020,
  language = "en"
}

@UNPUBLISHED{Storchi2020-em,
  title    = "Beyond locomotion: in the mouse the mapping between sensations
              and behaviours unfolds in a higher dimensional space",
  author   = "Storchi, Riccardo and Milosavljevic, Nina and Allen, Annette E
              and Cootes, Timothy F and Lucas, Robert J",
  abstract = "Abstract The ability of specific sensory stimuli to evoke
              spontaneous behavioural responses in the mouse represents a
              powerful approach to study how the mammalian brain processes
              sensory information and selects appropriate motor actions. For
              visually and auditory guided behaviours the relevant action has
              been empirically identified as a change in locomotion state.
              However, the extent to which locomotion alone captures the
              diversity of those behaviours and their sensory specificity is
              unknown.To tackle this problem we developed a method to obtain a
              faithful 3D reconstruction of the mouse body that enabled us to
              quantify a wide variety of movements and changes in postures.
              This higher dimensional description of behaviour revealed that
              responses to different sensory inputs is more stimulus-specific
              than indicated by locomotion data alone. Thus, equivalent
              locomotion patterns evoked by different stimuli (e.g. looming and
              sound evoking locomotion arrest) could be well separated along
              other dimensions. The enhanced stimulus-specificity was explained
              by a surprising diversity of behavioural responses. A clustering
              analysis revealed that distinct combinations of motor actions and
              postures, giving rise to at least 7 different behaviours, were
              required to account for stimulus-specificity. Moreover, each
              stimulus evoked more than one behaviour revealing a robust
              one-to-many mapping between sensations and behaviours that could
              not be detected from locomotion data.Our results challenge the
              current view of visually and auditory guided behaviours as purely
              locomotion-based actions (e.g. freeze, escape) and indicate that
              behavioural diversity and sensory specificity unfold in a higher
              dimensional space spanning multiple motor actions.",
  journal  = "bioRxiv",
  pages    = "2020.02.24.961565",
  month    =  mar,
  year     =  2020,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Cregg2020-ie,
  title    = "Brainstem neurons that command mammalian locomotor asymmetries",
  author   = "Cregg, Jared M and Leiras, Roberto and Montalant, Alexia and
              Wanken, Paulina and Wickersham, Ian R and Kiehn, Ole",
  abstract = "Descending command neurons instruct spinal networks to execute
              basic locomotor functions, such as gait and speed. The command
              functions for gait and speed are symmetric, implying that a
              separate unknown system directs asymmetric movements, including
              the ability to move left or right. In the present study, we
              report that Chx10-lineage reticulospinal neurons act to control
              the direction of locomotor movements in mammals. Chx10 neurons
              exhibit mainly ipsilateral projection, and their selective
              unilateral activation causes ipsilateral turning movements in
              freely moving mice. Unilateral inhibition of Chx10 neurons causes
              contralateral turning movements. Paired left--right motor
              recordings identified distinct mechanisms for directional
              movements mediated via limb and axial spinal circuits. Finally,
              we identify sensorimotor brain regions that project on to Chx10
              reticulospinal neurons, and demonstrate that their unilateral
              activation can impart left--right directional commands. Together
              these data identify the descending motor system that commands
              left--right locomotor asymmetries in mammals.",
  journal  = "Nat. Neurosci.",
  month    =  may,
  year     =  2020
}

@ARTICLE{Wang2020-lz,
  title     = "The Allen Mouse Brain Common Coordinate Framework: A {3D}
               Reference Atlas",
  author    = "Wang, Quanxin and Ding, Song-Lin and Li, Yang and Royall, Josh
               and Feng, David and Lesnar, Phil and Graddis, Nile and Naeemi,
               Maitham and Facer, Benjamin and Ho, Anh and Dolbeare, Tim and
               Blanchard, Brandon and Dee, Nick and Wakeman, Wayne and
               Hirokawa, Karla E and Szafer, Aaron and Sunkin, Susan M and Oh,
               Seung Wook and Bernard, Amy and Phillips, John W and Hawrylycz,
               Michael and Koch, Christof and Zeng, Hongkui and Harris, Julie A
               and Ng, Lydia",
  abstract  = "SummaryRecent large-scale collaborations are generating major
               surveys of cell types and connections in the mouse brain,
               collecting large amounts of data across modalities, spatial
               scales, and brain areas. Successful integration of these data
               requires a standard 3D reference atlas. Here, we present the
               Allen Mouse Brain Common Coordinate Framework (CCFv3) as such a
               resource. We constructed an average template brain at 10 $\mu$m
               voxel resolution by interpolating high resolution in-plane
               serial two-photon tomography images with 100 $\mu$m z-sampling
               from 1,675 young adult C57BL/6J mice. Then, using multimodal
               reference data, we parcellated the entire brain directly in 3D,
               labeling every voxel with a brain structure spanning 43
               isocortical areas and their layers, 329 subcortical gray matter
               structures, 81 fiber tracts, and 8 ventricular structures. CCFv3
               can be used to analyze, visualize, and integrate multimodal and
               multiscale datasets in 3D and is openly accessible
               (https://atlas.brain-map.org/).",
  journal   = "Cell",
  publisher = "Elsevier",
  volume    =  0,
  number    =  0,
  month     =  may,
  year      =  2020,
  keywords  = "average mouse brain; reference atlas; 3D brain atlas; brain
               parcellation; brain anatomy; mouse cortex; common coordinate
               framework; CCFv3; fiber tracts; transgenic mice",
  language  = "en"
}

@ARTICLE{Taube2007-if,
  title     = "The head direction signal: origins and sensory-motor integration",
  author    = "Taube, Jeffrey S",
  abstract  = "Navigation first requires accurate perception of one's spatial
               orientation within the environment, which consists of knowledge
               about location and directional heading. Cells within several
               limbic system areas of the mammalian brain discharge
               allocentrically as a function of the animal's directional
               heading, independent of the animal's location and ongoing
               behavior. These cells are referred to as head direction (HD)
               cells and are believed to encode the animal's perceived
               directional heading with respect to its environment. Although HD
               cells are found in several areas, the principal circuit for
               generating this signal originates in the dorsal tegmental
               nucleus and projects serially, with some reciprocal connections,
               to the lateral mammillary nucleus --> anterodorsal thalamus -->
               PoS, and terminates in the entorhinal cortex. HD cells receive
               multimodal information about landmarks and self-generated
               movements. Vestibular information appears critical for
               generating the directional signal, but motor/proprioceptive and
               landmark information are important for updating it.",
  journal   = "Annu. Rev. Neurosci.",
  publisher = "annualreviews.org",
  volume    =  30,
  pages     = "181--207",
  year      =  2007,
  language  = "en"
}

@ARTICLE{Crane_undated-dr,
  title  = "{D} {ISCRETE} {D} {IFFERENTIAL} {G} {EOMETRY}: A {N} A {PPLIED} {I}
            {NTRODUCTION}",
  author = "Crane, Keenan"
}

@ARTICLE{lx_undated-hq,
  title  = "{'$HWK\ODWLRQ$WODVRIWKHRXVH\%UDLQDWLQJOH\&HOOHVROXWLRQ}",
  author = "/lx, +dqtlqj and =krx, -Lqjwldq and /xr, Krqj\textbackslashxdq and
            \%duwohww, \$qqd and \$ogulgjh, \$qguhz"
}

@INCOLLECTION{Sorscher2019-xx,
  title     = "A unified theory for the origin of grid cells through the lens
               of pattern formation",
  booktitle = "Advances in Neural Information Processing Systems 32",
  author    = "Sorscher, Ben and Mel, Gabriel and Ganguli, Surya and Ocko,
               Samuel",
  editor    = "Wallach, H and Larochelle, H and Beygelzimer, A and
               d\textbackslashtextquotesingle Alch{\'e}-Buc, F and Fox, E and
               Garnett, R",
  publisher = "Curran Associates, Inc.",
  pages     = "10003--10013",
  year      =  2019
}

@ARTICLE{Pnevmatikakis2017-qi,
  title    = "{NoRMCorre}: An online algorithm for piecewise rigid motion
              correction of calcium imaging data",
  author   = "Pnevmatikakis, Eftychios A and Giovannucci, Andrea",
  abstract = "BACKGROUND: Motion correction is a challenging pre-processing
              problem that arises early in the analysis pipeline of calcium
              imaging data sequences. The motion artifacts in two-photon
              microscopy recordings can be non-rigid, arising from the finite
              time of raster scanning and non-uniform deformations of the brain
              medium. NEW METHOD: We introduce an algorithm for fast Non-Rigid
              Motion Correction (NoRMCorre) based on template matching.
              NoRMCorre operates by splitting the field of view (FOV) into
              overlapping spatial patches along all directions. The patches are
              registered at a sub-pixel resolution for rigid translation
              against a regularly updated template. The estimated alignments
              are subsequently up-sampled to create a smooth motion field for
              each frame that can efficiently approximate non-rigid artifacts
              in a piecewise-rigid manner. EXISTING METHODS: Existing
              approaches either do not scale well in terms of computational
              performance or are targeted to non-rigid artifacts arising just
              from the finite speed of raster scanning, and thus cannot correct
              for non-rigid motion observable in datasets from a large FOV.
              RESULTS: NoRMCorre can be run in an online mode resulting in
              comparable to or even faster than real time motion registration
              of streaming data. We evaluate its performance with simple yet
              intuitive metrics and compare against other non-rigid
              registration methods on simulated data and in vivo two-photon
              calcium imaging datasets. Open source Matlab and Python code is
              also made available. CONCLUSIONS: The proposed method and
              accompanying code can be useful for solving large scale image
              registration problems in calcium imaging, especially in the
              presence of non-rigid deformations.",
  journal  = "J. Neurosci. Methods",
  volume   =  291,
  pages    = "83--94",
  month    =  nov,
  year     =  2017,
  keywords = "Calcium imaging; Image registration; Motion correction",
  language = "en"
}

@UNPUBLISHED{Tran2020-yg,
  title    = "Automated curation of {CNMF-E-extracted} {ROI} spatial footprints
              and calcium traces using open-source {AutoML} tools",
  author   = "Tran, L M and Mocle, A J and Ramsaran, A I and Jacob, A D and
              Frankland, P W and Josselyn, S A",
  abstract = "In vivo 1-photon calcium imaging is an increasingly prevalent
              method in behavioural neuroscience. Numerous analysis pipelines
              have been developed to improve the reliability and scalability of
              pre-processing and ROI extraction for these large calcium imaging
              datasets. Despite these advancements in pre-processing methods,
              manual curation of the extracted spatial footprints and calcium
              traces of neurons remains important for quality control. Here, we
              propose an additional semi-automated curation step for sorting
              spatial footprints and calcium traces from putative neurons
              extracted using the popular CNMF-E algorithm. We used the
              automated machine learning tools TPOT and AutoSklearn to generate
              classifiers to curate the extracted ROIs trained on a subset of
              human-labeled data. AutoSklearn produced the best performing
              classifier, achieving an F1 score > 92\% on the ground truth test
              dataset. This automated approach is a useful strategy for
              filtering ROIs with relatively few labeled data points, and can
              be easily added to pre-existing pipelines currently using CNMF-E
              for ROI extraction.",
  journal  = "bioRxiv",
  pages    = "2020.03.13.991216",
  month    =  mar,
  year     =  2020,
  language = "en"
}

@ARTICLE{Zhou2018-fo,
  title    = "Efficient and accurate extraction of in vivo calcium signals from
              microendoscopic video data",
  author   = "Zhou, Pengcheng and Resendez, Shanna L and Rodriguez-Romaguera,
              Jose and Jimenez, Jessica C and Neufeld, Shay Q and Giovannucci,
              Andrea and Friedrich, Johannes and Pnevmatikakis, Eftychios A and
              Stuber, Garret D and Hen, Rene and Kheirbek, Mazen A and
              Sabatini, Bernardo L and Kass, Robert E and Paninski, Liam",
  abstract = "In vivo calcium imaging through microendoscopic lenses enables
              imaging of previously inaccessible neuronal populations deep
              within the brains of freely moving animals. However, it is
              computationally challenging to extract single-neuronal activity
              from microendoscopic data, because of the very large background
              fluctuations and high spatial overlaps intrinsic to this
              recording modality. Here, we describe a new constrained matrix
              factorization approach to accurately separate the background and
              then demix and denoise the neuronal signals of interest. We
              compared the proposed method against previous independent
              components analysis and constrained nonnegative matrix
              factorization approaches. On both simulated and experimental data
              recorded from mice, our method substantially improved the quality
              of extracted cellular signals and detected more well-isolated
              neural signals, especially in noisy data regimes. These advances
              can in turn significantly enhance the statistical power of
              downstream analyses, and ultimately improve scientific
              conclusions derived from microendoscopic data.",
  journal  = "Elife",
  volume   =  7,
  month    =  feb,
  year     =  2018,
  keywords = "calcium imaging; microendoscope; mouse; neuroscience; source
              extraction",
  language = "en"
}

@ARTICLE{Weir_undated-oc,
  title  = "A molecular filter for the cnidarian stinging response",
  author = "Weir, Keiko and Dupre, Christophe and van Giesen, Lena and Lee, Amy
            S Y and Bellono, Nicholas W"
}

@ARTICLE{Dolensek2020-dn,
  title    = "Facial expressions of emotion states and their neuronal
              correlates in mice",
  author   = "Dolensek, Nejc and Gehrlach, Daniel A and Klein, Alexandra S and
              Gogolla, Nadine",
  abstract = "Understanding the neurobiological underpinnings of emotion relies
              on objective readouts of the emotional state of an individual,
              which remains a major challenge especially in animal models. We
              found that mice exhibit stereotyped facial expressions in
              response to emotionally salient events, as well as upon targeted
              manipulations in emotion-relevant neuronal circuits. Facial
              expressions were classified into distinct categories using
              machine learning and reflected the changing intrinsic value of
              the same sensory stimulus encountered under different homeostatic
              or affective conditions. Facial expressions revealed emotion
              features such as intensity, valence, and persistence. Two-photon
              imaging uncovered insular cortical neuron activity that
              correlated with specific facial expressions and may encode
              distinct emotions. Facial expressions thus provide a means to
              infer emotion states and their neuronal correlates in mice.",
  journal  = "Science",
  volume   =  368,
  number   =  6486,
  pages    = "89--94",
  month    =  apr,
  year     =  2020,
  language = "en"
}

@UNPUBLISHED{Rayshubskiy2020-ad,
  title    = "Neural control of steering in walking Drosophila",
  author   = "Rayshubskiy, Aleksandr and Holtz, Stephen L and D'Alessandro,
              Isabel and Li, Anna A and Vanderbeck, Quinn X and Haber, Isabel S
              and Gibb, Peter W and Wilson, Rachel I",
  abstract = "During navigation, the brain must continuously integrate external
              guidance cues with internal spatial maps to update steering
              commands. However, it has been difficult to link spatial maps
              with motor control. Here we identify 9descending steering9
              neurons in the Drosophila brain that lie two synapses downstream
              from the brain9s heading direction map in the central complex.
              These steering neurons predict behavioral turns caused by
              microstimulation of the spatial map. Moreover, these neurons
              receive 9direct9 sensory input that bypasses the central complex,
              and they predict steering evoked by multimodal stimuli.
              Unilateral activation of these neurons can promote turning, while
              bilateral silencing interferes with body and leg movements. In
              short, these neurons combine internal maps with external cues to
              predict and influence steering. They represent a key link between
              cognitive maps, which use an abstract coordinate frame, and motor
              commands, which use a body-centric coordinate frame.",
  journal  = "bioRxiv",
  pages    = "2020.04.04.024703",
  month    =  apr,
  year     =  2020,
  language = "en"
}

@ARTICLE{Branco_undated-ez,
  title  = "The Neural Basis of Escape Behavior in Vertebrates",
  author = "Branco, Tiago and Redgrave, Peter"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Hsu2019-jc,
  title     = "{B-SOiD}: An Open Source Unsupervised Algorithm for Discovery of
               Spontaneous Behaviors",
  author    = "Hsu, A I and Yttri, E A",
  abstract  = "The motivation, control, and selection of actions comprising
               naturalistic behaviors remains a tantalizing but difficult field
               of study. Detailed and unbiased quantification is critical.
               Interpreting the positions of animals and their limbs can be
               useful in studying behavior, and significant recent advances
               have made this step straightforward. However, body position
               alone does not provide a grasp of the dynamic range of
               naturalistic behaviors. Behavioral Segmentation of Open-field In
               DeepLabCut, or B-SOiD (`` B-side''), is an unsupervised …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2019
}

@ARTICLE{Andalman2019-zi,
  title     = "Neuronal Dynamics Regulating Brain and Behavioral State
               Transitions",
  author    = "Andalman, Aaron S and Burns, Vanessa M and Lovett-Barron,
               Matthew and Broxton, Michael and Poole, Ben and Yang, Samuel J
               and Grosenick, Logan and Lerner, Talia N and Chen, Ritchie and
               Benster, Tyler and Mourrain, Philippe and Levoy, Marc and Rajan,
               Kanaka and Deisseroth, Karl",
  abstract  = "Prolonged behavioral challenges can cause animals to switch from
               active to passive coping strategies to manage effort-expenditure
               during stress; such normally adaptive behavioral state
               transitions can become maladaptive in psychiatric disorders such
               as depression. The underlying neuronal dynamics and brainwide
               interactions important for passive coping have remained unclear.
               Here, we develop a paradigm to study these behavioral state
               transitions at cellular-resolution across the entire vertebrate
               brain. Using brainwide imaging in zebrafish, we observed that
               the transition to passive coping is manifested by progressive
               activation of neurons in the ventral (lateral) habenula.
               Activation of these ventral-habenula neurons suppressed
               downstream neurons in the serotonergic raphe nucleus and caused
               behavioral passivity, whereas inhibition of these neurons
               prevented passivity. Data-driven recurrent neural network
               modeling pointed to altered intra-habenula interactions as a
               contributory mechanism. These results demonstrate ongoing
               encoding of experience features in the habenula, which guides
               recruitment of downstream networks and imposes a passive coping
               behavioral strategy.",
  journal   = "Cell",
  publisher = "Elsevier",
  volume    =  177,
  number    =  4,
  pages     = "970--985.e20",
  month     =  may,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Tombaz2020-tl,
  title    = "Action representation in the mouse parieto-frontal network",
  author   = "Tombaz, Tuce and Dunn, Benjamin A and Hovde, Karoline and Cubero,
              Ryan John and Mimica, Bartul and Mamidanna, Pranav and Roudi,
              Yasser and Whitlock, Jonathan R",
  abstract = "The posterior parietal cortex (PPC) and frontal motor areas
              comprise a cortical network supporting goal-directed behaviour,
              with functions including sensorimotor transformations and
              decision making. In primates, this network links performed and
              observed actions via mirror neurons, which fire both when
              individuals perform an action and when they observe the same
              action performed by a conspecific. Mirror neurons are believed to
              be important for social learning, but it is not known whether
              mirror-like neurons occur in similar networks in other social
              species, such as rodents, or if they can be measured in such
              models using paradigms where observers passively view a
              demonstrator. Therefore, we imaged Ca2+ responses in PPC and
              secondary motor cortex (M2) while mice performed and observed
              pellet-reaching and wheel-running tasks, and found that cell
              populations in both areas robustly encoded several naturalistic
              behaviours. However, neural responses to the same set of observed
              actions were absent, although we verified that observer mice were
              attentive to performers and that PPC neurons responded reliably
              to visual cues. Statistical modelling also indicated that
              executed actions outperformed observed actions in predicting
              neural responses. These results raise the possibility that
              sensorimotor action recognition in rodents could take place
              outside of the parieto-frontal circuit, and underscore that
              detecting socially-driven neural coding depends critically on the
              species and behavioural paradigm used.",
  journal  = "Sci. Rep.",
  volume   =  10,
  number   =  1,
  pages    = "5559",
  month    =  mar,
  year     =  2020,
  language = "en"
}

@UNPUBLISHED{Benavidez2020-oh,
  title    = "The mouse cortico-tectal projectome",
  author   = "Benavidez, Nora L and Bienkowski, Michael S and Khanjani, Neda
              and Bowman, Ian and Fayzullina, Marina and Garcia, Luis and Gao,
              Lei and Korobkova, Laura and Gou, Lin and Cotter, Kaelan and
              Becerra, Marlene and Aquino, Sarvia and Cao, Chunru and Foster,
              Nicholas N and Song, Monica Y and Zhang, Bin and Yamashita, Seita
              and Zhu, Muye and Lo, Darrick and Boesen, Tyler and Zingg, Brian
              and Santarelli, Anthony and Wickersham, Ian R and Ascoli, Giorgio
              A and Hintiryan, Houri and Dong, Hong-Wei",
  abstract = "The superior colliculus (SC) is a midbrain structure that
              receives diverse and robust cortical inputs to drive a range of
              cognitive and sensorimotor behaviors. However, it remains unclear
              how descending cortical inputs arising from higher-order
              associative areas coordinate with SC sensorimotor networks to
              influence its outputs. In this study, we constructed a
              comprehensive map of all cortico-tectal projections and
              identified four collicular zones with differential cortical
              inputs: medial (SC.m), centromedial (SC.cm), centrolateral
              (SC.cl) and lateral (SC.l). Computational analyses revealed that
              cortico-tectal projections are organized as multiple subnetworks
              that are consistent with previously identified cortico-cortical
              and cortico-striatal subnetworks. Furthermore, we delineated the
              brain-wide input/output organization of each collicular zone and
              described a subset of their constituent neuronal cell types based
              on distinct connectional and morphological features. Altogether,
              this work provides a novel structural foundation for the
              integrative role of the SC in controlling cognition, orientation,
              and other sensorimotor behaviors.",
  journal  = "bioRxiv",
  pages    = "2020.03.24.006775",
  month    =  mar,
  year     =  2020,
  language = "en"
}

@INPROCEEDINGS{Pascanu2013-zg,
  title      = "On the difficulty of training recurrent neural networks",
  booktitle  = "International Conference on Machine Learning",
  author     = "Pascanu, Razvan and Mikolov, Tomas and Bengio, Yoshua",
  abstract   = "There are two widely known issues with properly training
                recurrent neural networks, the vanishing and the exploding
                gradient problems detailed in Bengio et al. (1994). In this
                paper we attempt to i...",
  publisher  = "jmlr.org",
  pages      = "1310--1318",
  month      =  feb,
  year       =  2013,
  language   = "en",
  conference = "International Conference on Machine Learning"
}

@ARTICLE{Remington2018-aw,
  title    = "A Dynamical Systems Perspective on Flexible Motor Timing",
  author   = "Remington, Evan D and Egger, Seth W and Narain, Devika and Wang,
              Jing and Jazayeri, Mehrdad",
  abstract = "A hallmark of higher brain function is the ability to rapidly and
              flexibly adjust behavioral responses based on internal and
              external cues. Here, we examine the computational principles that
              allow decisions and actions to unfold flexibly in time. We adopt
              a dynamical systems perspective and outline how temporal
              flexibility in such a system can be achieved through
              manipulations of inputs and initial conditions. We then review
              evidence from experiments in nonhuman primates that support this
              interpretation. Finally, we explore the broader utility and
              limitations of the dynamical systems perspective as a general
              framework for addressing open questions related to the temporal
              control of movements, as well as in the domains of learning and
              sequence generation.",
  journal  = "Trends Cogn. Sci.",
  volume   =  22,
  number   =  10,
  pages    = "938--952",
  month    =  oct,
  year     =  2018,
  keywords = "dynamical systems; flexible timing; learning; movement planning;
              movement sequences; sensorimotor control",
  language = "en"
}

@ARTICLE{Remington2018-tc,
  title    = "Flexible Sensorimotor Computations through Rapid Reconfiguration
              of Cortical Dynamics",
  author   = "Remington, Evan D and Narain, Devika and Hosseini, Eghbal A and
              Jazayeri, Mehrdad",
  abstract = "Neural mechanisms that support flexible sensorimotor computations
              are not well understood. In a dynamical system whose state is
              determined by interactions among neurons, computations can be
              rapidly reconfigured by controlling the system's inputs and
              initial conditions. To investigate whether the brain employs such
              control mechanisms, we recorded from the dorsomedial frontal
              cortex of monkeys trained to measure and produce time intervals
              in two sensorimotor contexts. The geometry of neural trajectories
              during the production epoch was consistent with a mechanism
              wherein the measured interval and sensorimotor context exerted
              control over cortical dynamics by adjusting the system's initial
              condition and input, respectively. These adjustments, in turn,
              set the speed at which activity evolved in the production epoch,
              allowing the animal to flexibly produce different time intervals.
              These results provide evidence that the language of dynamical
              systems can be used to parsimoniously link brain activity to
              sensorimotor computations.",
  journal  = "Neuron",
  volume   =  98,
  number   =  5,
  pages    = "1005--1019.e5",
  month    =  jun,
  year     =  2018,
  keywords = "Dynamical Systems; cognitive flexibility; electrophysiology;
              frontal cortex; motor planning; population coding; recurrent
              neural networks; sensorimotor coordination; timing",
  language = "en"
}

@ARTICLE{Wang2018-gi,
  title    = "Flexible timing by temporal scaling of cortical responses",
  author   = "Wang, Jing and Narain, Devika and Hosseini, Eghbal A and
              Jazayeri, Mehrdad",
  abstract = "Musicians can perform at different tempos, speakers can control
              the cadence of their speech, and children can flexibly vary their
              temporal expectations of events. To understand the neural basis
              of such flexibility, we recorded from the medial frontal cortex
              of nonhuman primates trained to produce different time intervals
              with different effectors. Neural responses were heterogeneous,
              nonlinear, and complex, and they exhibited a remarkable form of
              temporal invariance: firing rate profiles were temporally scaled
              to match the produced intervals. Recording from downstream
              neurons in the caudate and from thalamic neurons projecting to
              the medial frontal cortex indicated that this phenomenon
              originates within cortical networks. Recurrent neural network
              models trained to perform the task revealed that temporal scaling
              emerges from nonlinearities in the network and that the degree of
              scaling is controlled by the strength of external input. These
              findings demonstrate a simple and general mechanism for
              conferring temporal flexibility upon sensorimotor and cognitive
              functions.",
  journal  = "Nat. Neurosci.",
  volume   =  21,
  number   =  1,
  pages    = "102--110",
  month    =  jan,
  year     =  2018,
  keywords = "RNN To read;RNN",
  language = "en"
}

@ARTICLE{Song2016-cr,
  title    = "Training {Excitatory-Inhibitory} Recurrent Neural Networks for
              Cognitive Tasks: A Simple and Flexible Framework",
  author   = "Song, H Francis and Yang, Guangyu R and Wang, Xiao-Jing",
  abstract = "The ability to simultaneously record from large numbers of
              neurons in behaving animals has ushered in a new era for the
              study of the neural circuit mechanisms underlying cognitive
              functions. One promising approach to uncovering the dynamical and
              computational principles governing population responses is to
              analyze model recurrent neural networks (RNNs) that have been
              optimized to perform the same tasks as behaving animals. Because
              the optimization of network parameters specifies the desired
              output but not the manner in which to achieve this output,
              ``trained'' networks serve as a source of mechanistic hypotheses
              and a testing ground for data analyses that link neural
              computation to behavior. Complete access to the activity and
              connectivity of the circuit, and the ability to manipulate them
              arbitrarily, make trained networks a convenient proxy for
              biological circuits and a valuable platform for theoretical
              investigation. However, existing RNNs lack basic biological
              features such as the distinction between excitatory and
              inhibitory units (Dale's principle), which are essential if RNNs
              are to provide insights into the operation of biological
              circuits. Moreover, trained networks can achieve the same
              behavioral performance but differ substantially in their
              structure and dynamics, highlighting the need for a simple and
              flexible framework for the exploratory training of RNNs. Here, we
              describe a framework for gradient descent-based training of
              excitatory-inhibitory RNNs that can incorporate a variety of
              biological knowledge. We provide an implementation based on the
              machine learning library Theano, whose automatic differentiation
              capabilities facilitate modifications and extensions. We validate
              this framework by applying it to well-known experimental
              paradigms such as perceptual decision-making, context-dependent
              integration, multisensory integration, parametric working memory,
              and motor sequence generation. Our results demonstrate the wide
              range of neural activity patterns and behavior that can be
              modeled, and suggest a unified setting in which diverse cognitive
              computations and mechanisms can be studied.",
  journal  = "PLoS Comput. Biol.",
  volume   =  12,
  number   =  2,
  pages    = "e1004792",
  month    =  feb,
  year     =  2016,
  language = "en"
}

@ARTICLE{Stubblefield2013-dj,
  title     = "Optogenetic investigation of the role of the superior colliculus
               in orienting movements",
  author    = "Stubblefield, Elizabeth A and Costabile, Jamie D and Felsen,
               Gidon",
  abstract  = "In vivo studies have demonstrated that the superior colliculus
               (SC) integrates sensory information and plays a role in
               controlling orienting motor output. However, how the complex
               microcircuitry within the SC, as documented by slice studies,
               subserves these functions is unclear. Optogenetics affords the
               potential to examine, in behaving animals, the functional roles
               of specific neuron types that comprise heterogeneous nuclei. As
               a first step toward understanding how SC microcircuitry
               underlies motor output, we applied optogenetics to mice
               performing an odor discrimination task in which sensory
               decisions are reported by either a leftward or rightward
               SC-dependent orienting movement. We unilaterally expressed
               either channelrhodopsin-2 or halorhodopsin in the SC and
               delivered light in order to excite or inhibit motor-related SC
               activity as the movement was planned. We found that manipulating
               SC activity predictably affected the direction of the selected
               movement in a manner that depended on the difficulty of the odor
               discrimination. This study demonstrates that the SC plays a
               similar role in directional orienting movements in mice as it
               does in other species, and provides a framework for future
               investigations into how specific SC cell types contribute to
               motor control.",
  journal   = "Behav. Brain Res.",
  publisher = "Elsevier",
  volume    =  255,
  pages     = "55--63",
  month     =  oct,
  year      =  2013,
  keywords  = "ChR2; Channelrhodopsin-2; Decision making; Halorhodopsin;
               Midbrain; Motor planning; Mouse behavior; NpHR; SC;
               channelrhodopsin-2; contra.; contraversive; halorhodopsin;
               ipsi.; ipsiversive; mW/mm(2); milliwatts per millimeter squared
               (power output measured at optic fiber tip); superior colliculus",
  language  = "en"
}

@UNPUBLISHED{Coletta2020-gb,
  title    = "Network structure of the mouse brain connectome with voxel
              resolution",
  author   = "Coletta, Ludovico and Pagani, Marco and Whitesell, Jennifer D and
              Harris, Julie A and Bernhardt, Boris and Gozzi, Alessandro",
  abstract = "Fine-grained descriptions of brain connectivity are fundamental
              for understanding how neural information is processed and relayed
              across spatial scales. Prior investigations of the mouse brain
              connectome have employed discrete anatomical parcellations,
              limiting spatial resolution and potentially concealing network
              attributes critical to the organization of the mammalian
              connectome. Here we provide a voxel-level description of the
              network and hierarchical structure of the directed mouse
              connectome, unconstrained by regional partitioning. We show that
              integrative hub regions can be directionally segregated into
              neural sinks and sources, defining a hierarchical axis. We
              describe a set of structural communities that spatially
              reconstitute previously described fMRI networks of the mouse
              brain, and document that neuromodulatory nuclei are strategically
              wired as critical orchestrators of inter-modular and network
              communicability. Notably, like in primates, the directed mouse
              connectome is organized along two superimposed cortical gradients
              reflecting unimodal-transmodal functional processing and a
              modality-specific sensorimotor axis. These structural features
              can be related to patterns of intralaminar connectivity and to
              the spatial topography of dynamic fMRI brain states,
              respectively. Together, our results reveal a high-resolution
              structural scaffold linking mesoscale connectome topography to
              its macroscale functional organization, and create opportunities
              for identifying targets of interventions to modulate brain
              function in a physiologically-accessible species.",
  journal  = "bioRxiv",
  pages    = "2020.03.06.973164",
  month    =  mar,
  year     =  2020,
  language = "en"
}

@ARTICLE{Doykos2020-or,
  title     = "Monosynaptic inputs to specific cell types of the intermediate
               and deep layers of the superior colliculus",
  author    = "Doykos, Ted K and Gilmer, Jesse I and Person, Abigail L and
               Felsen, Gidon",
  abstract  = "The intermediate and deep layers of the midbrain superior
               colliculus (SC) are a key locus for several critical functions,
               including spatial attention, multisensory integration, and
               behavioral responses. While the SC is known to integrate input
               from a variety of brain regions, progress in understanding how
               these inputs contribute to SC-dependent functions has been
               hindered by the paucity of data on innervation patterns to
               specific types of SC neurons. Here, we use G-deleted rabies
               virus-mediated monosynaptic tracing to identify inputs to
               excitatory and inhibitory neurons of the intermediate and deep
               SC. We observed stronger and more numerous projections to
               excitatory than inhibitory SC neurons. However, a subpopulation
               of excitatory neurons thought to mediate behavioral output
               received weaker inputs, from far fewer brain regions, than the
               overall population of excitatory neurons. Additionally,
               extrinsic inputs tended to target rostral excitatory and
               inhibitory SC neurons more strongly than their caudal
               counterparts, and commissural SC neurons tended to project to
               similar rostrocaudal positions in the other SC. Our findings
               support the view that active intrinsic processes are critical to
               SC-dependent functions, and will enable the examination of how
               specific inputs contribute to these functions.",
  journal   = "J. Comp. Neurol.",
  publisher = "Wiley Online Library",
  month     =  feb,
  year      =  2020,
  keywords  = "RRIDs: FIJI software: SCR\_002285; RRIDs: ImageJ software:
               SCR\_003070; RRIDs: Jackson labs heterozygous Gad2-Cre mice:
               IMSR\_JAX:010802; RRIDs: Jackson labs homozygous Vglut2-Cre
               mice: IMSR\_JAX:028863; RRIDs: MATLAB Computer Vision System
               Toolbox software: SCR\_017581; RRIDs: MATLAB software:
               SCR\_001622; RRIDs: Thermo Fisher Scientific Nissl: AB\_2572212;
               RRIDs: $\mu$Manager software: SCR\_016865; excitatory;
               inhibitory; monosynaptic; neuroanatomy; rabies; sensorimotor;
               superior colliculus",
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@INCOLLECTION{Belkin2002-ei,
  title     = "Laplacian Eigenmaps and Spectral Techniques for Embedding and
               Clustering",
  booktitle = "Advances in Neural Information Processing Systems 14",
  author    = "Belkin, Mikhail and Niyogi, Partha",
  editor    = "Dietterich, T G and Becker, S and Ghahramani, Z",
  abstract  = "Drawing on the correspondence between the graph Laplacian, the
               Laplace-Beltrami operator on a manifold, and the connections to
               the heat equation, we propose a geometrically motivated
               algorithm for constructing a representation for data sampled
               from a low dimensional manifold embedded in a higher dimensional
               space. The algorithm provides a computationally efficient
               approach to nonlinear dimensionality reduction that has locality
               preserving properties and a natural connection to clustering.
               Several applications are …",
  publisher = "MIT Press",
  pages     = "585--591",
  year      =  2002
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Maaten2008-tv,
  title     = "Visualizing Data using {t-SNE}",
  author    = "Maaten, Laurens van der and Hinton, Geoffrey",
  abstract  = "We present a new technique called`` t-SNE'' that visualizes
               high-dimensional data by giving each datapoint a location in a
               two or three-dimensional map. The technique is a variation of
               Stochastic Neighbor Embedding (Hinton and Roweis, 2002) that is
               much easier to optimize …",
  journal   = "J. Mach. Learn. Res.",
  publisher = "jmlr.org",
  volume    =  9,
  number    = "Nov",
  pages     = "2579--2605",
  year      =  2008
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Balasubramanian2002-ly,
  title     = "The isomap algorithm and topological stability",
  author    = "Balasubramanian, Mukund and Schwartz, Eric L",
  abstract  = "Tenenbaum et al.(1) presented an algorithm, Isomap , for
               computing a quasi-isometric, low- dimensional embedding of a set
               of high-dimensional data points. Two issues need to be raised
               concerning this work. First, the basic approach presented by
               Tenenbaum et al. is not …",
  journal   = "Science",
  publisher = "science.sciencemag.org",
  volume    =  295,
  number    =  5552,
  pages     = "7",
  month     =  jan,
  year      =  2002,
  language  = "en"
}

@UNPUBLISHED{Essig2020-br,
  title    = "Inhibitory midbrain neurons mediate decision making",
  author   = "Essig, Jaclyn and Hunt, Joshua B and Felsen, Gidon",
  abstract = "Decision making is critical for survival but its neural basis is
              unclear. Here we examine how functional neural circuitry in the
              output layers of the midbrain superior colliculus (SC) mediates
              spatial choice, an SC-dependent tractable form of decision
              making. We focus on the role of inhibitory SC neurons, using
              optogenetics to record and manipulate their activity in behaving
              mice. Based on data from SC slice experiments and on a canonical
              role of inhibitory neurons in cortical microcircuits, we
              hypothesized that inhibitory SC neurons locally inhibit premotor
              output neurons that represent contralateral targets. However, our
              experimental results refuted this hypothesis. An attractor model
              revealed that our results were instead consistent with inhibitory
              neurons providing long-range inhibition between the two SCs, and
              terminal activation experiments supported this architecture. Our
              study provides mechanistic evidence for competitive inhibition
              between populations representing discrete choices, a common motif
              in theoretical models of decision making.",
  journal  = "bioRxiv",
  pages    = "2020.02.25.965699",
  month    =  feb,
  year     =  2020,
  language = "en"
}

@UNPUBLISHED{Liu2020-pe,
  title    = "Accurate localization of linear probe electrodes across multiple
              brains",
  author   = "Liu, Liu D and Chen, Susu and Economo, Michael N and Li, Nuo and
              Svoboda, Karel",
  abstract = "Recently developed silicon probes have large numbers of recording
              electrodes on long linear shanks. Specifically, Neuropixels
              probes have 960 recording electrodes distributed over 9.6 mm
              shanks. Because of their length, Neuropixels probe recordings in
              rodents naturally span multiple brain areas. Typical studies
              collate recordings across several recording sessions and animals.
              Neurons recorded in different sessions and animals have to be
              aligned to each other and to a standardized brain coordinate
              system. Here we report a workflow for accurate localization of
              individual electrodes in standardized coordinates and aligned
              across individual brains. This workflow relies on imaging brains
              with fluorescent probe tracks and warping 3-dimensional image
              stacks to standardized brain atlases. Electrophysiological
              features are then used to anchor particular electrodes along the
              reconstructed tracks to specific locations in the brain atlas and
              therefore to specific brain structures. We performed ground-truth
              experiments, in which motor cortex outputs are labelled with ChR2
              and a fluorescence protein. Recording from brain regions targeted
              by these outputs reveals better than 100 $\mu$m accuracy for
              electrode localization.",
  journal  = "bioRxiv",
  pages    = "2020.02.25.965210",
  month    =  feb,
  year     =  2020,
  language = "en"
}

@ARTICLE{Becht2018-hp,
  title     = "Dimensionality reduction for visualizing single-cell data using
               {UMAP}",
  author    = "Becht, Etienne and McInnes, Leland and Healy, John and Dutertre,
               Charles-Antoine and Kwok, Immanuel W H and Ng, Lai Guan and
               Ginhoux, Florent and Newell, Evan W",
  abstract  = "Advances in single-cell technologies have enabled
               high-resolution dissection of tissue composition. Several tools
               for dimensionality reduction are available to analyze the large
               number of parameters generated in single-cell studies. Recently,
               a nonlinear dimensionality-reduction technique, uniform manifold
               approximation and projection (UMAP), was developed for the
               analysis of any type of high-dimensional data. Here we apply it
               to biological data, using three well-characterized mass
               cytometry and single-cell RNA sequencing datasets. Comparing the
               performance of UMAP with five other tools, we find that UMAP
               provides the fastest run times, highest reproducibility and the
               most meaningful organization of cell clusters. The work
               highlights the use of UMAP for improved visualization and
               interpretation of single-cell data.",
  journal   = "Nat. Biotechnol.",
  publisher = "nature.com",
  month     =  dec,
  year      =  2018,
  language  = "en"
}

@ARTICLE{McInnes2018-dg,
  title         = "{UMAP}: Uniform Manifold Approximation and Projection for
                   Dimension Reduction",
  author        = "McInnes, Leland and Healy, John and Melville, James",
  abstract      = "UMAP (Uniform Manifold Approximation and Projection) is a
                   novel manifold learning technique for dimension reduction.
                   UMAP is constructed from a theoretical framework based in
                   Riemannian geometry and algebraic topology. The result is a
                   practical scalable algorithm that applies to real world
                   data. The UMAP algorithm is competitive with t-SNE for
                   visualization quality, and arguably preserves more of the
                   global structure with superior run time performance.
                   Furthermore, UMAP has no computational restrictions on
                   embedding dimension, making it viable as a general purpose
                   dimension reduction technique for machine learning.",
  month         =  feb,
  year          =  2018,
  archivePrefix = "arXiv",
  primaryClass  = "stat.ML",
  eprint        = "1802.03426"
}

@ARTICLE{Kobak2019-se,
  title     = "The art of using {t-SNE} for single-cell transcriptomics",
  author    = "Kobak, Dmitry and Berens, Philipp",
  abstract  = "Single-cell transcriptomics yields ever growing data sets
               containing RNA expression levels for thousands of genes from up
               to millions of cells. Common data analysis pipelines include a
               dimensionality reduction step for visualising the data in two
               dimensions, most frequently performed using t-distributed
               stochastic neighbour embedding (t-SNE). It excels at revealing
               local structure in high-dimensional data, but naive applications
               often suffer from severe shortcomings, e.g. the global structure
               of the data is not represented accurately. Here we describe how
               to circumvent such pitfalls, and develop a protocol for creating
               more faithful t-SNE visualisations. It includes PCA
               initialisation, a high learning rate, and multi-scale similarity
               kernels; for very large data sets, we additionally use
               exaggeration and downsampling-based initialisation. We use
               published single-cell RNA-seq data sets to demonstrate that this
               protocol yields superior results compared to the naive
               application of t-SNE.",
  journal   = "Nat. Commun.",
  publisher = "nature.com",
  volume    =  10,
  number    =  1,
  pages     = "5416",
  month     =  nov,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Kuwabara2020-qm,
  title    = "Neural mechanisms of economic choices in mice",
  author   = "Kuwabara, Masaru and Kang, Ningdong and Holy, Timothy E and
              Padoa-Schioppa, Camillo",
  abstract = "Economic choices entail computing and comparing subjective
              values. Evidence from primates indicates that this behavior
              relies on the orbitofrontal cortex. Conversely, previous work in
              rodents provided conflicting results. Here we present a mouse
              model of economic choice behavior, and we show that the lateral
              orbital (LO) area is intimately related to the decision process.
              In the experiments, mice chose between different juices offered
              in variable amounts. Choice patterns closely resembled those
              measured in primates. Optogenetic inactivation of LO dramatically
              disrupted choices by inducing erratic changes of relative value
              and by increasing choice variability. Neuronal recordings
              revealed that different groups of cells encoded the values of
              individual options, the binary choice outcome and the chosen
              value. These groups match those previously identified in
              primates, except that the neuronal representation in mice is
              spatial (in monkeys it is good-based). Our results lay the
              foundations for a circuit-level analysis of economic decisions.",
  journal  = "Elife",
  volume   =  9,
  month    =  feb,
  year     =  2020,
  keywords = "mouse; neuroscience",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Ascoli2007-hp,
  title     = "{NeuroMorpho.Org}: a central resource for neuronal morphologies",
  author    = "Ascoli, Giorgio A and Donohue, Duncan E and Halavi, Maryam",
  abstract  = "The structure of dendrites and axons plays fundamental roles in
               synaptic integration and network connectivity. Synergistic
               advances in neurobiology (eg, intracellular injections,
               fluorescent protein expression), microscopy (eg, multiphoton
               laser scanning, computer controllers), and imaging software (eg,
               Neurolucida tracing, blind deconvolution) are rapidly
               transforming the three-dimensional (3D) reconstruction of
               neuronal morphology into a mainstream technique. In the course
               of electrophysiological, pharmacological, or …",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  27,
  number    =  35,
  pages     = "9247--9251",
  month     =  aug,
  year      =  2007,
  language  = "en"
}

@ARTICLE{Muller2015-ws,
  title    = "Python in neuroscience",
  author   = "Muller, Eilif and Bednar, James A and Diesmann, Markus and
              Gewaltig, Marc-Oliver and Hines, Michael and Davison, Andrew P",
  journal  = "Front. Neuroinform.",
  volume   =  9,
  pages    = "11",
  month    =  apr,
  year     =  2015,
  keywords = "collaboration; interoperability; python language; scientific
              computing; software development",
  language = "en"
}

@ARTICLE{Niedworok2016-wj,
  title    = "{aMAP} is a validated pipeline for registration and segmentation
              of high-resolution mouse brain data",
  author   = "Niedworok, Christian J and Brown, Alexander P Y and Jorge
              Cardoso, M and Osten, Pavel and Ourselin, Sebastien and Modat,
              Marc and Margrie, Troy W",
  abstract = "The validation of automated image registration and segmentation
              is crucial for accurate and reliable mapping of brain
              connectivity and function in three-dimensional (3D) data sets.
              While validation standards are necessarily high and routinely met
              in the clinical arena, they have to date been lacking for
              high-resolution microscopy data sets obtained from the rodent
              brain. Here we present a tool for optimized automated mouse atlas
              propagation (aMAP) based on clinical registration software
              (NiftyReg) for anatomical segmentation of high-resolution 3D
              fluorescence images of the adult mouse brain. We empirically
              evaluate aMAP as a method for registration and subsequent
              segmentation by validating it against the performance of expert
              human raters. This study therefore establishes a benchmark
              standard for mapping the molecular function and cellular
              connectivity of the rodent brain.",
  journal  = "Nat. Commun.",
  volume   =  7,
  pages    = "11879",
  month    =  jul,
  year     =  2016,
  language = "en"
}

@UNPUBLISHED{Guitchounts2020-xj,
  title    = "Encoding of {3D} Head Orienting Movements in Primary Visual
              Cortex",
  author   = "Guitchounts, Grigori and Masis, Javier and Wolff, Steffen B E and
              Cox, David",
  abstract = "Animals actively sample from the sensory world by generating
              complex patterns of movement that evolve in three dimensions. At
              least some of these movements have been shown to influence neural
              codes in sensory areas. For example, in primary visual cortex
              (V1), locomotion-related neural activity influences sensory gain,
              encodes running speed, and predicts the direction of visual flow.
              As most experiments exploring movement-related modulation of V1
              have been performed in head-fixed animals, it remains unclear
              whether or how the naturalistic movements used to interact with
              sensory stimuli--like head orienting--influence visual
              processing. Here we show that 3D head orienting movements
              modulate V1 neuronal activity in a direction-specific manner that
              also depends on the presence or absence of light. We identify two
              largely independent populations of movement-direction-tuned
              neurons that support this modulation, one of which is
              direction-tuned in the dark and the other in the light. Finally,
              we demonstrate that V1 gains access to a motor efference copy
              related to orientation from secondary motor cortex, which has
              been shown to control head orienting movements. These results
              suggest a mechanism through which sensory signals generated by
              purposeful movement can be distinguished from those arising in
              the outside world, and reveal a pervasive role of 3D movement in
              shaping sensory cortical dynamics.",
  journal  = "bioRxiv",
  pages    = "2020.01.16.909473",
  month    =  jan,
  year     =  2020,
  language = "en"
}

@ARTICLE{Mobbs2020-vp,
  title     = "Space, Time, and Fear: Survival Computations along Defensive
               Circuits",
  author    = "Mobbs, Dean and Headley, Drew B and Ding, Weilun and Dayan,
               Peter",
  abstract  = "Naturalistic observations show that decisions to avoid or escape
               predators occur at different spatiotemporal scales and that they
               are supported by different computations and neural circuits. At
               their extremes, proximal threats are addressed by a limited
               repertoire of reflexive and myopic actions, reflecting reduced
               decision and state spaces and model-free (MF) architectures.
               Conversely, distal threats allow increased information
               processing supported by model-based (MB) operations, including
               affective prospection, replay, and planning. However, MF and MB
               computations are often intertwined, and under conditions of
               safety the foundations for future effective reactive execution
               can be laid through MB instruction of MF control. Together,
               these computations are associated with distinct population codes
               embedded within a distributed defensive circuitry whose goal is
               to determine and realize the best policy.",
  journal   = "Trends Cogn. Sci.",
  publisher = "Elsevier",
  volume    =  0,
  number    =  0,
  month     =  feb,
  year      =  2020,
  keywords  = "fear; anxiety; threat imminence continuum; periaqueductal gray;
               hippocampus; prefrontal cortex; model free; model based; Dyna",
  language  = "en"
}

@ARTICLE{Hasson2020-zv,
  title     = "Direct Fit to Nature: An Evolutionary Perspective on Biological
               and Artificial Neural Networks",
  author    = "Hasson, Uri and Nastase, Samuel A and Goldstein, Ariel",
  abstract  = "SummaryEvolution is a blind fitting process by which organisms
               become adapted to their environment. Does the brain use similar
               brute-force fitting processes to learn how to perceive and act
               upon the world? Recent advances in artificial neural networks
               have exposed the power of optimizing millions of synaptic
               weights over millions of observations to operate robustly in
               real-world contexts. These models do not learn simple,
               human-interpretable rules or representations of the world;
               rather, they use local computations to interpolate over
               task-relevant manifolds in a high-dimensional parameter space.
               Counterintuitively, similar to evolutionary processes,
               over-parameterized models can be simple and parsimonious, as
               they provide a versatile, robust solution for learning a diverse
               set of functions. This new family of direct-fit models present a
               radical challenge to many of the theoretical assumptions in
               psychology and neuroscience. At the same time, this shift in
               perspective establishes unexpected links with developmental and
               ecological psychology.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  105,
  number    =  3,
  pages     = "416--434",
  month     =  feb,
  year      =  2020,
  keywords  = "evolution; experimental design; interpolation; learning; neural
               networks",
  language  = "en"
}

@ARTICLE{Barabasi2019-ou,
  title    = "A Genetic Model of the Connectome",
  author   = "Barab{\'a}si, D{\'a}niel L and Barab{\'a}si,
              Albert-L{\'a}szl{\'o}",
  abstract = "The connectomes of organisms of the same species show remarkable
              architectural and often local wiring similarity, raising the
              question: where and how is neuronal connectivity encoded? Here,
              we start from the hypothesis that the genetic identity of neurons
              guides synapse and gap-junction formation and show that such
              genetically driven wiring predicts the existence of specific
              biclique motifs in the connectome. We identify a family of large,
              statistically significant biclique subgraphs in the connectomes
              of three species and show that within many of the observed
              bicliques the neurons share statistically significant expression
              patterns and morphological characteristics, supporting our
              expectation of common genetic factors that drive the synapse
              formation within these subgraphs. The proposed connectome model
              offers a self-consistent framework to link the genetics of an
              organism to the reproducible architecture of its connectome,
              offering experimentally falsifiable predictions on the genetic
              factors that drive the formation of individual neuronal circuits.",
  journal  = "Neuron",
  month    =  nov,
  year     =  2019,
  keywords = "Brain Networks; C. elegans; Connectomics; Generative Model;
              Theory; development; encoding",
  language = "en"
}

@ARTICLE{Kaplan2019-zb,
  title    = "Nested Neuronal Dynamics Orchestrate a Behavioral Hierarchy
              across Timescales",
  author   = "Kaplan, Harris S and Salazar Thula, Oriana and Khoss, Niklas and
              Zimmer, Manuel",
  abstract = "Classical and modern ethological studies suggest that animal
              behavior is organized hierarchically across timescales, such that
              longer-timescale behaviors are composed of specific
              shorter-timescale actions. Despite progress relating neuronal
              dynamics to single-timescale behavior, it remains unclear how
              different timescale dynamics interact to give rise to such
              higher-order behavioral organization. Here, we show, in the
              nematode Caenorhabditis elegans, that a behavioral hierarchy
              spanning three timescales is implemented by nested neuronal
              dynamics. At the uppermost hierarchical level, slow neuronal
              population dynamics spanning brain and motor periphery control
              two faster motor neuron oscillations, toggling them between
              different activity states and functional roles. At lower
              hierarchical levels, these faster oscillations are further nested
              in a manner that enables flexible behavioral control in an
              otherwise rigid hierarchical framework. Our findings establish
              nested neuronal activity patterns as a repeated dynamical motif
              of the C. elegans nervous system, which together implement a
              controllable hierarchical organization of behavior.",
  journal  = "Neuron",
  month    =  nov,
  year     =  2019,
  keywords = "C. elegans neuroscience; behavior organization; behavioral
              hierarchy; ethology; hierarchical organization; motor control;
              neuronal dynamics; neuronal oscillations; quantitative behavior;
              whole-brain imaging",
  language = "en"
}

@ARTICLE{Mendes-Gomes2020-de,
  title    = "Defensive behaviors and brain regional activation changes in rats
              confronting a snake",
  author   = "Mendes-Gomes, Joyce and Motta, Simone Cristina and Passoni Bindi,
              Ricardo and de Oliveira, Amanda Ribeiro and Ullah, Farhad and
              Baldo, Marcus Vinicius C and Coimbra, Norberto Cysne and
              Canteras, Newton Sabino and Blanchard, D Caroline",
  abstract = "In the present study, we examined behavioral and brain regional
              activation changes of rats). To a nonmammalian predator, a wild
              rattler snake (Crotalus durissus terrificus). Accordingly, during
              snake threat, rat subjects showed a striking and highly
              significant behavioral response of freezing, stretch attend, and,
              especially, spatial avoidance of this threat. The brain regional
              activation patterns for these rats were in broad outline similar
              to those of rats encountering other predator threats, showing Fos
              activation of sites in the amygdala, hypothalamus, and
              periaqueductal gray matter. In the amygdala, only the lateral
              nucleus showed significant activation, although the medial
              nucleus, highly responsive to olfaction, also showed higher
              activation. Importantly, the hypothalamus, in particular, was
              somewhat different, with significant Fos increases in the
              anterior and central parts of the ventromedial hypothalamic
              nucleus (VMH), in contrast to patterns of enhanced Fos expression
              in the dorsomedial VMH to cat predators, and in the ventrolateral
              VMH to an attacking conspecific. In addition, the
              juxtodorsalmedial region of the lateral hypothalamus showed
              enhanced Fos activation, where inputs from the septo-hippocampal
              system may suggest the potential involvement of hippocampal
              boundary cells in the very strong spatial avoidance of the snake
              and the area it occupied. Notably, these two hypothalamic paths
              appear to merge into the dorsomedial part of the dorsal
              premammillary nucleus and dorsomedial and lateral parts of the
              periaqueductal gray, all of which present significant increases
              in Fos expression and are likely to be critical for the
              expression of defensive behaviors in responses to the snake
              threat.",
  journal  = "Behav. Brain Res.",
  volume   =  381,
  pages    = "112469",
  month    =  mar,
  year     =  2020,
  keywords = "Amygdala; Antipredatory defense; Hippocampus; Hypothalamus;
              Periaqueductal gray; Prey versus rattlesnake confrontation
              paradigm",
  language = "en"
}

@ARTICLE{Grillner2002-si,
  title    = "Cellular bases of a vertebrate locomotor system-steering,
              intersegmental and segmental co-ordination and sensory control",
  author   = "Grillner, Sten and Wall{\'e}n, Peter",
  abstract = "The isolated brainstem-spinal cord of the lamprey is used as an
              experimental model in the analysis of the cellular bases of
              vertebrate locomotor behaviour. In this article we review the
              neural mechanisms involved in the control of steering,
              intersegmental co-ordination, as well as the segmental burst
              generation and the sensory contribution to motor pattern
              generation. Within these four components of the control system
              for locomotion, we now have good knowledge of not only the
              neurones that take part and their synaptic interactions, but also
              the membrane properties of these neurones, including ion channel
              subtypes, and their contribution to motor pattern generation.",
  journal  = "Brain Res. Brain Res. Rev.",
  volume   =  40,
  number   = "1-3",
  pages    = "92--106",
  month    =  oct,
  year     =  2002,
  language = "en"
}

@ARTICLE{Krumin2018-yz,
  title    = "Decision and navigation in mouse parietal cortex",
  author   = "Krumin, Michael and Lee, Julie J and Harris, Kenneth D and
              Carandini, Matteo",
  abstract = "Posterior parietal cortex (PPC) has been implicated in
              navigation, in the control of movement, and in visually-guided
              decisions. To relate these views, we measured activity in PPC
              while mice performed a virtual navigation task driven by visual
              decisions. PPC neurons were selective for specific combinations
              of the animal's spatial position and heading angle. This
              selectivity closely predicted both the activity of individual PPC
              neurons, and the arrangement of their collective firing patterns
              in choice-selective sequences. These sequences reflected PPC
              encoding of the animal's navigation trajectory. Using decision as
              a predictor instead of heading yielded worse fits, and using it
              in addition to heading only slightly improved the fits.
              Alternative models based on visual or motor variables were
              inferior. We conclude that when mice use vision to choose their
              trajectories, a large fraction of parietal cortex activity can be
              predicted from simple attributes such as spatial position and
              heading.",
  journal  = "Elife",
  volume   =  7,
  month    =  nov,
  year     =  2018,
  keywords = "cortex; decision; mouse; navigation; neuroscience; visual
              processing",
  language = "en"
}

@ARTICLE{Stringer2019-fm,
  title    = "Spontaneous behaviors drive multidimensional, brainwide activity",
  author   = "Stringer, Carsen and Pachitariu, Marius and Steinmetz, Nicholas
              and Reddy, Charu Bai and Carandini, Matteo and Harris, Kenneth D",
  abstract = "Neuronal populations in sensory cortex produce variable responses
              to sensory stimuli and exhibit intricate spontaneous activity
              even without external sensory input. Cortical variability and
              spontaneous activity have been variously proposed to represent
              random noise, recall of prior experience, or encoding of ongoing
              behavioral and cognitive variables. Recording more than 10,000
              neurons in mouse visual cortex, we observed that spontaneous
              activity reliably encoded a high-dimensional latent state, which
              was partially related to the mouse's ongoing behavior and was
              represented not just in visual cortex but also across the
              forebrain. Sensory inputs did not interrupt this ongoing signal
              but added onto it a representation of external stimuli in
              orthogonal dimensions. Thus, visual cortical population activity,
              despite its apparently noisy structure, reliably encodes an
              orthogonal fusion of sensory and multidimensional behavioral
              information.",
  journal  = "Science",
  volume   =  364,
  number   =  6437,
  pages    = "255",
  month    =  apr,
  year     =  2019,
  language = "en"
}

@ARTICLE{Stringer2019-nc,
  title    = "High-dimensional geometry of population responses in visual
              cortex",
  author   = "Stringer, Carsen and Pachitariu, Marius and Steinmetz, Nicholas
              and Carandini, Matteo and Harris, Kenneth D",
  abstract = "A neuronal population encodes information most efficiently when
              its stimulus responses are high-dimensional and uncorrelated, and
              most robustly when they are lower-dimensional and correlated.
              Here we analysed the dimensionality of the encoding of natural
              images by large populations of neurons in the visual cortex of
              awake mice. The evoked population activity was high-dimensional,
              and correlations obeyed an unexpected power law: the nth
              principal component variance scaled as 1/n. This scaling was not
              inherited from the power law spectrum of natural images, because
              it persisted after stimulus whitening. We proved mathematically
              that if the variance spectrum was to decay more slowly then the
              population code could not be smooth, allowing small changes in
              input to dominate population activity. The theory also predicts
              larger power-law exponents for lower-dimensional stimulus
              ensembles, which we validated experimentally. These results
              suggest that coding smoothness may represent a fundamental
              constraint that determines correlations in neural population
              codes.",
  journal  = "Nature",
  volume   =  571,
  number   =  7765,
  pages    = "361--365",
  month    =  jul,
  year     =  2019,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Spellman2015-qp,
  title     = "Hippocampal--prefrontal input supports spatial encoding in
               working memory",
  author    = "Spellman, T and Rigotti, M and Ahmari, S E and Fusi, S and
               Gogos, J A and {others}",
  abstract  = "Spatial working memory, the caching of behaviourally relevant
               spatial cues on a timescale of seconds, is a fundamental
               constituent of cognition. Although the prefrontal cortex and
               hippocampus are known to contribute jointly to successful
               spatial working memory, the …",
  journal   = "Nature",
  publisher = "nature.com",
  year      =  2015
}

@ARTICLE{Rigotti2013-ls,
  title    = "The importance of mixed selectivity in complex cognitive tasks",
  author   = "Rigotti, Mattia and Barak, Omri and Warden, Melissa R and Wang,
              Xiao-Jing and Daw, Nathaniel D and Miller, Earl K and Fusi,
              Stefano",
  abstract = "Single-neuron activity in the prefrontal cortex (PFC) is tuned to
              mixtures of multiple task-related aspects. Such mixed selectivity
              is highly heterogeneous, seemingly disordered and therefore
              difficult to interpret. We analysed the neural activity recorded
              in monkeys during an object sequence memory task to identify a
              role of mixed selectivity in subserving the cognitive functions
              ascribed to the PFC. We show that mixed selectivity neurons
              encode distributed information about all task-relevant aspects.
              Each aspect can be decoded from the population of neurons even
              when single-cell selectivity to that aspect is eliminated.
              Moreover, mixed selectivity offers a significant computational
              advantage over specialized responses in terms of the repertoire
              of input-output functions implementable by readout neurons. This
              advantage originates from the highly diverse nonlinear
              selectivity to mixtures of task-relevant variables, a signature
              of high-dimensional neural representations. Crucially, this
              dimensionality is predictive of animal behaviour as it collapses
              in error trials. Our findings recommend a shift of focus for
              future studies from neurons that have easily interpretable
              response tuning to the widely observed, but rarely analysed,
              mixed selectivity neurons.",
  journal  = "Nature",
  volume   =  497,
  number   =  7451,
  pages    = "585--590",
  month    =  may,
  year     =  2013,
  language = "en"
}

@ARTICLE{Shang2019-nm,
  title    = "A subcortical excitatory circuit for sensory-triggered predatory
              hunting in mice",
  author   = "Shang, Congping and Liu, Aixue and Li, Dapeng and Xie, Zhiyong
              and Chen, Zijun and Huang, Meizhu and Li, Yang and Wang, Yi and
              Shen, Wei L and Cao, Peng",
  abstract = "Predatory hunting plays a fundamental role in animal survival.
              Little is known about the neural circuits that convert sensory
              cues into neural signals to drive this behavior. Here we
              identified an excitatory subcortical neural circuit from the
              superior colliculus to the zona incerta that triggers predatory
              hunting. The superior colliculus neurons that form this pathway
              integrate motion-related visual and vibrissal somatosensory cues
              of prey. During hunting, these neurons send out neural signals
              that are temporally correlated with predatory attacks, but not
              with feeding after prey capture. Synaptic inactivation of this
              pathway selectively blocks hunting for prey without impairing
              other sensory-triggered behaviors. These data reveal a
              subcortical neural circuit that is specifically engaged in
              translating sensory cues into neural signals to provoke predatory
              hunting.",
  journal  = "Nat. Neurosci.",
  volume   =  22,
  number   =  6,
  pages    = "909--920",
  month    =  jun,
  year     =  2019,
  language = "en"
}


@UNPUBLISHED{Cadena2019-ly,
  title    = "How well do deep neural networks trained on object recognition
              characterize the mouse visual system?",
  author   = "Cadena, Santiago A and Sinz, Fabian H and Muhammad, Taliah and
              Froudarakis, Emmanouil and Cobos, Erick and Walker, Edgar Y and
              Reimer, Jake and Bethge, Matthias and Tolias, Andreas and Ecker,
              Alexander S",
  abstract = "Recent work on modeling neural responses in the primate visual
              system has benefited from deep neural networks trained on
              large-scale object recognition, and found a hierarchical
              correspondence between layers of the artificial neural network
              and brain areas along the ventral visual stream. However, we
              neither know whether such task-optimized networks enable equally
              good models of the rodent visual system, nor if a similar
              hierarchical correspondence exists. Here, we address these
              questions in the mouse visual system by extracting features at
              several layers of a convolutional neural network (CNN) trained on
              ImageNet to predict the responses of thousands of neurons in four
              visual areas (V1, LM, AL, RL) to natural images. We found that
              the CNN features outperform classical subunit energy models, but
              found no evidence for an order of the areas we recorded via a
              correspondence to the hierarchy of CNN layers. Moreover, the same
              CNN but with random weights provided an equivalently useful
              feature space for predicting neural responses. Our results
              suggest that object recognition as a high-level task does not
              provide more discriminative features to characterize the mouse
              visual system than a random network. Unlike in the primate,
              training on ethologically relevant visually guided behaviors --
              beyond static object recognition -- may be needed to unveil the
              functional organization of the mouse visual cortex.",
  month    =  sep,
  year     =  2019
}

@ARTICLE{Dean1986-hf,
  title    = "Head and body movements produced by electrical stimulation of
              superior colliculus in rats: effects of interruption of crossed
              tectoreticulospinal pathway",
  author   = "Dean, P and Redgrave, P and Sahibzada, N and Tsuji, K",
  abstract = "Stimulation of the superior colliculus in rats produces movements
              of the head and body that resemble either orientation and
              approach towards a contralateral stimulus, or avoidance of, or
              escape from, such a stimulus. A variety of evidence indicates
              that the crossed descending pathway, which runs in the
              contralateral predorsal bundle to the pontomedullary reticular
              formation and the spinal cord, is involved in orienting
              movements. The nature of this involvement was investigated, by
              assessing the effects on tectally-elicited movements of midbrain
              knife-cuts intended to section the pathway as it crosses midline
              in the dorsal tegmental decussation. As expected, ipsilateral
              movements resembling avoidance or escape were little affected by
              dorsal tegmental decussation section, whereas contralateral
              circling movements of the body were almost abolished. However,
              contralateral movements of the head in response to electrical
              stimulation were not eliminated, nor were orienting head
              movements to visual or tactile stimuli. There was some suggestion
              that section of the dorsal tegmental decussation increased the
              latency of head movements from electrical stimulation at lateral
              sites, and decreased the accuracy of orienting movements to
              sensory stimuli. These results support the view that the crossed
              tectoreticulospinal system is concerned with approach rather than
              avoidance movements. However, it appears that other, as yet
              unidentified, tectal efferent systems are also involved in
              orienting head movements. It is possible that this division of
              labour may reflect functional differences between various kinds
              of apparently similar orienting responses. One suggestion is that
              the tectoreticulospinal system is concerned less in open-loop
              orienting responses (that are initiated but not subsequently
              guided by sensory stimuli), than in following or pursuit
              movements.",
  journal  = "Neuroscience",
  volume   =  19,
  number   =  2,
  pages    = "367--380",
  month    =  oct,
  year     =  1986,
  language = "en"
}

@ARTICLE{Saitoh2007-yr,
  title    = "Tectal control of locomotion, steering, and eye movements in
              lamprey",
  author   = "Saitoh, Kazuya and M{\'e}nard, Ariane and Grillner, Sten",
  abstract = "The intrinsic function of the brain stem-spinal cord networks
              eliciting the locomotor synergy is well described in the
              lamprey-a vertebrate model system. This study addresses the role
              of tectum in integrating eye, body orientation, and locomotor
              movements as in steering and goal-directed behavior. Electrical
              stimuli were applied to different areas within the optic tectum
              in head-restrained semi-intact lampreys (n = 40). Motions of the
              eyes and body were recorded simultaneously (videotaped). Brief
              pulse trains (0.5 s) lateral bending movements of the body
              (orientation movements) were added, and with even longer stimuli
              locomotor movements were initiated. Depending on the tectal area
              stimulated, four characteristic response patterns were observed.
              In a lateral area conjugate horizontal eye movements combined
              with lateral bending movements of the body and locomotor
              movements were elicited, depending on stimulus duration. The
              amplitude of the eye movement and bending movements was site
              specific within this region. In a rostromedial area, bilateral
              downward vertical eye movements occurred. In a caudomedial tectal
              area, large-amplitude undulatory body movements akin to
              struggling behavior were elicited, combined with large-amplitude
              eye movements that were antiphasic to the body movements. The
              alternating eye movements were not dependent on vestibuloocular
              reflexes. Finally, in a caudolateral area locomotor movements
              without eye or bending movements could be elicited. These results
              show that tectum can provide integrated motor responses of eye,
              body orientation, and locomotion of the type that would be
              required in goal-directed locomotion.",
  journal  = "J. Neurophysiol.",
  volume   =  97,
  number   =  4,
  pages    = "3093--3108",
  month    =  apr,
  year     =  2007,
  language = "en"
}

@ARTICLE{Sussillo2013-ey,
  title     = "Opening the black box: low-dimensional dynamics in
               high-dimensional recurrent neural networks",
  author    = "Sussillo, David and Barak, Omri",
  abstract  = "Recurrent neural networks (RNNs) are useful tools for learning
               nonlinear relationships between time-varying inputs and outputs
               with complex temporal dependencies. Recently developed
               algorithms have been successful at training RNNs to perform a
               wide variety of tasks, but the resulting networks have been
               treated as black boxes: their mechanism of operation remains
               unknown. Here we explore the hypothesis that fixed points, both
               stable and unstable, and the linearized dynamics around them,
               can reveal crucial aspects of how RNNs implement their
               computations. Further, we explore the utility of linearization
               in areas of phase space that are not true fixed points but
               merely points of very slow movement. We present a simple
               optimization technique that is applied to trained RNNs to find
               the fixed and slow points of their dynamics. Linearization
               around these slow regions can be used to explore, or
               reverse-engineer, the behavior of the RNN. We describe the
               technique, illustrate it using simple examples, and finally
               showcase it on three high-dimensional RNN examples: a 3-bit
               flip-flop device, an input-dependent sine wave generator, and a
               two-point moving average. In all cases, the mechanisms of
               trained networks could be inferred from the sets of fixed and
               slow points and the linearized dynamics around them.",
  journal   = "Neural Comput.",
  publisher = "MIT Press",
  volume    =  25,
  number    =  3,
  pages     = "626--649",
  month     =  mar,
  year      =  2013,
  keywords  = "RNN",
  language  = "en"
}

@ARTICLE{Werbos1990-qo,
  title    = "Backpropagation through time: what it does and how to do it",
  author   = "Werbos, P J",
  abstract = "Basic backpropagation, which is a simple method now being widely
              used in areas like pattern recognition and fault diagnosis, is
              reviewed. The basic equations for backpropagation through time,
              and applications to areas like pattern recognition involving
              dynamic systems, systems identification, and control are
              discussed. Further extensions of this method, to deal with
              systems other than neural networks, systems involving
              simultaneous equations, or true recurrent networks, and other
              practical issues arising with the method are described.
              Pseudocode is provided to clarify the algorithms. The chain rule
              for ordered derivatives-the theorem which underlies
              backpropagation-is briefly discussed. The focus is on designing a
              simpler version of backpropagation which can be translated into
              computer code and applied directly by neutral network users.",
  journal  = "Proc. IEEE",
  volume   =  78,
  number   =  10,
  pages    = "1550--1560",
  month    =  oct,
  year     =  1990,
  keywords = "identification;neural nets;pattern recognition;pseudocode;pattern
              recognition;fault diagnosis;backpropagation;systems
              identification;neural networks;Backpropagation;Artificial neural
              networks;Supervised learning;Pattern recognition;Neural
              networks;Power system modeling;Equations;Control systems;Fluid
              dynamics;Books"
}

@ARTICLE{Mante2013-yl,
  title    = "Context-dependent computation by recurrent dynamics in prefrontal
              cortex",
  author   = "Mante, Valerio and Sussillo, David and Shenoy, Krishna V and
              Newsome, William T",
  abstract = "Prefrontal cortex is thought to have a fundamental role in
              flexible, context-dependent behaviour, but the exact nature of
              the computations underlying this role remains largely unknown. In
              particular, individual prefrontal neurons often generate
              remarkably complex responses that defy deep understanding of
              their contribution to behaviour. Here we study prefrontal cortex
              activity in macaque monkeys trained to flexibly select and
              integrate noisy sensory inputs towards a choice. We find that the
              observed complexity and functional roles of single neurons are
              readily understood in the framework of a dynamical process
              unfolding at the level of the population. The population dynamics
              can be reproduced by a trained recurrent neural network, which
              suggests a previously unknown mechanism for selection and
              integration of task-relevant inputs. This mechanism indicates
              that selection and integration are two aspects of a single
              dynamical process unfolding within the same prefrontal circuits,
              and potentially provides a novel, general framework for
              understanding context-dependent computations.",
  journal  = "Nature",
  volume   =  503,
  number   =  7474,
  pages    = "78--84",
  month    =  nov,
  year     =  2013,
  language = "en"
}

@ARTICLE{Athalye2019-gr,
  title    = "Neural reinforcement: re-entering and refining neural dynamics
              leading to desirable outcomes",
  author   = "Athalye, Vivek R and Carmena, Jose M and Costa, Rui M",
  abstract = "How do organisms learn to do again, on-demand, a behavior that
              led to a desirable outcome? Dopamine-dependent cortico-striatal
              plasticity provides a framework for learning behavior's value,
              but it is less clear how it enables the brain to re-enter desired
              behaviors and refine them over time. Reinforcing behavior is
              achieved by re-entering and refining the neural patterns that
              produce it. We review studies using brain-machine interfaces
              which reveal that reinforcing cortical population activity
              requires cortico-basal ganglia circuits. Then, we propose a
              formal framework for how reinforcement in cortico-basal ganglia
              circuits acts on the neural dynamics of cortical populations. We
              propose two parallel mechanisms: i) fast reinforcement which
              selects the inputs that permit the re-entrance of the particular
              cortical population dynamics which naturally produced the desired
              behavior, and ii) slower reinforcement which leads to refinement
              of cortical population dynamics and more reliable production of
              neural trajectories driving skillful behavior on-demand.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  60,
  pages    = "145--154",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@ARTICLE{Sussillo2014-mo,
  title    = "Neural circuits as computational dynamical systems",
  author   = "Sussillo, David",
  abstract = "Many recent studies of neurons recorded from cortex reveal
              complex temporal dynamics. How such dynamics embody the
              computations that ultimately lead to behavior remains a mystery.
              Approaching this issue requires developing plausible hypotheses
              couched in terms of neural dynamics. A tool ideally suited to aid
              in this question is the recurrent neural network (RNN). RNNs
              straddle the fields of nonlinear dynamical systems and machine
              learning and have recently seen great advances in both theory and
              application. I summarize recent theoretical and technological
              advances and highlight an example of how RNNs helped to explain
              perplexing high-dimensional neurophysiological data in the
              prefrontal cortex.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  25,
  pages    = "156--163",
  month    =  apr,
  year     =  2014,
  keywords = "RNN To read;RNN",
  language = "en"
}

@ARTICLE{DePasquale2018-on,
  title    = "{full-FORCE}: A target-based method for training recurrent
              networks",
  author   = "DePasquale, Brian and Cueva, Christopher J and Rajan, Kanaka and
              Escola, G Sean and Abbott, L F",
  abstract = "Trained recurrent networks are powerful tools for modeling
              dynamic neural computations. We present a target-based method for
              modifying the full connectivity matrix of a recurrent network to
              train it to perform tasks involving temporally complex
              input/output transformations. The method introduces a second
              network during training to provide suitable ``target'' dynamics
              useful for performing the task. Because it exploits the full
              recurrent connectivity, the method produces networks that perform
              tasks with fewer neurons and greater noise robustness than
              traditional least-squares (FORCE) approaches. In addition, we
              show how introducing additional input signals into the
              target-generating network, which act as task hints, greatly
              extends the range of tasks that can be learned and provides
              control over the complexity and nature of the dynamics of the
              trained, task-performing network.",
  journal  = "PLoS One",
  volume   =  13,
  number   =  2,
  pages    = "e0191527",
  month    =  feb,
  year     =  2018,
  language = "en"
}

@ARTICLE{Sussillo2009-tf,
  title    = "Generating coherent patterns of activity from chaotic neural
              networks",
  author   = "Sussillo, David and Abbott, L F",
  abstract = "Neural circuits display complex activity patterns both
              spontaneously and when responding to a stimulus or generating a
              motor output. How are these two forms of activity related? We
              develop a procedure called FORCE learning for modifying synaptic
              strengths either external to or within a model neural network to
              change chaotic spontaneous activity into a wide variety of
              desired activity patterns. FORCE learning works even though the
              networks we train are spontaneously chaotic and we leave feedback
              loops intact and unclamped during learning. Using this approach,
              we construct networks that produce a wide variety of complex
              output patterns, input-output transformations that require
              memory, multiple outputs that can be switched by control inputs,
              and motor patterns matching human motion capture data. Our
              results reproduce data on premovement activity in motor and
              premotor cortex, and suggest that synaptic plasticity may be a
              more rapid and powerful modulator of network activity than
              generally appreciated.",
  journal  = "Neuron",
  volume   =  63,
  number   =  4,
  pages    = "544--557",
  month    =  aug,
  year     =  2009,
  language = "en"
}

@ARTICLE{Helmbrecht2018-ux,
  title    = "Topography of a Visuomotor Transformation",
  author   = "Helmbrecht, Thomas O and Dal Maschio, Marco and Donovan, Joseph C
              and Koutsouli, Styliani and Baier, Herwig",
  abstract = "The brain converts perceptual information into appropriate
              patterns of muscle activity depending on the categorization and
              localization of sensory cues. Sensorimotor information might
              either be encoded by distributed networks or by ``labeled lines''
              connecting sensory channels to dedicated behavioral pathways.
              Here we investigate, in the context of natural behavior, how the
              tectum of larval zebrafish can inform downstream premotor areas.
              Optogenetic mapping revealed a tectal motor map underlying
              locomotor maneuvers for escape and approach. Single-cell
              reconstructions and high-resolution functional imaging showed
              that two spatially segregated and uncrossed descending axon
              tracts selectively transmit approach and escape signals to the
              hindbrain. Moreover, the approach pathway conveys information
              about retinotopic target coordinates to specific premotor
              ensembles via spatially ordered axonal projections. This
              topographic organization supports a tectum-generated space code
              sufficient to steer orienting movements. We conclude that
              specific labeled lines guide object-directed behavior in the
              larval zebrafish brain.",
  journal  = "Neuron",
  volume   =  100,
  number   =  6,
  pages    = "1429--1445.e4",
  month    =  dec,
  year     =  2018,
  keywords = "hindbrain; motor map; optic tectum; optogenetics; reticular
              formation; space code; superior colliculus; tectal projectome;
              visuomotor transformation; zebrafish",
  language = "en"
}

@ARTICLE{Kardamakis2015-yc,
  title    = "Tectal microcircuit generating visual selection commands on
              gaze-controlling neurons",
  author   = "Kardamakis, Andreas A and Saitoh, Kazuya and Grillner, Sten",
  abstract = "The optic tectum (called superior colliculus in mammals) is
              critical for eye-head gaze shifts as we navigate in the terrain
              and need to adapt our movements to the visual scene. The neuronal
              mechanisms underlying the tectal contribution to stimulus
              selection and gaze reorientation remains, however, unclear at the
              microcircuit level. To analyze this complex--yet phylogenetically
              conserved--sensorimotor system, we developed a novel in vitro
              preparation in the lamprey that maintains the eye and midbrain
              intact and allows for whole-cell recordings from prelabeled
              tectal gaze-controlling cells in the deep layer, while visual
              stimuli are delivered. We found that receptive field activation
              of these cells provide monosynaptic retinal excitation followed
              by local GABAergic inhibition (feedforward). The entire remaining
              retina, on the other hand, elicits only inhibition (surround
              inhibition). If two stimuli are delivered simultaneously, one
              inside and one outside the receptive field, the former excitatory
              response is suppressed. When local inhibition is
              pharmacologically blocked, the suppression induced by competing
              stimuli is canceled. We suggest that this rivalry between visual
              areas across the tectal map is triggered through long-range
              inhibitory tectal connections. Selection commands conveyed via
              gaze-controlling neurons in the optic tectum are, thus, formed
              through synaptic integration of local retinotopic excitation and
              global tectal inhibition. We anticipate that this mechanism not
              only exists in lamprey but is also conserved throughout
              vertebrate evolution.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  112,
  number   =  15,
  pages    = "E1956--65",
  month    =  apr,
  year     =  2015,
  keywords = "GABAergic inhibition; evolution; gaze control; optic tectum;
              superior colliculus",
  language = "en"
}

@ARTICLE{Weldon1983-oz,
  title     = "Rotational behavior following cholinergic stimulation of the
               superior colliculus in rats",
  author    = "Weldon, D A and Calabrese, L C and Nicklaus, K J",
  abstract  = "Rate which received microinjections of carbachol into the
               superior colliculus exhibited pronounced dose-dependent
               rotational behavior contralateral to the site of injection
               (Experiment 1). Wet dog shakes were also observed in some
               animals. Similar injections in the midbrain reticular formation
               produced immobility with slight contralateral flexion of the
               neck. Convulsions were observed in some rats after injections
               into either anatomical location. In Experiment 2, circling
               induced by carbachol in the superior colliculus was blocked by
               prior injection of either the muscarinic receptor antagonist
               scopolamine or the nicotinic receptor antagonist mecamylamine,
               suggesting that both nicotinic and muscarinic receptors are
               involved in the effect. In Experiment 3 contralateral rotational
               behavior was induced by intracollicular microinjections of the
               combination of acetylcholine chloride and physostigmine. The
               results suggest that collicular mediation of contralateral
               rotational behavior, and perhaps orientation, might involve
               cholinergic receptors.",
  journal   = "Pharmacol. Biochem. Behav.",
  publisher = "Elsevier",
  volume    =  19,
  number    =  5,
  pages     = "813--820",
  month     =  nov,
  year      =  1983,
  language  = "en"
}

@ARTICLE{Geula1984-sq,
  title     = "Circling and bodily asymmetry induced by injection of {GABA}
               agonists and antagonists into the superior colliculus",
  author    = "Geula, C and Asdourian, D",
  abstract  = "The observation that ipsiversive circling follows unilateral
               lesions of the deep layers of the superior colliculus (DLSC),
               combined with the recent demonstration of an ipsilateral
               inhibitory GABAergic projection from substantia nigra pars
               reticulata (SNr) to the DLSC suggests a role for tectal GABA in
               circling behavior. In the present experiment, GABA, the GABA
               agonist muscimol, and the GABA antagonists picrotoxin and
               bicuculline were injected into the DLSC through chronic
               cannulae. GABA and muscimol produced significantly higher
               ipsiversive circling and bodily asymmetry than saline
               injections. Picrotoxin and bicuculline resulted in significantly
               higher contraversive circling and asymmetry than saline
               injections. All drugs except bicuculline produced dose-dependent
               circling. GABA injections were also made into the mesencephalic
               reticular formation (MRF) and the periaqueductal gray (PAG). The
               MRF injections produced the same degree of circling and
               asymmetry as the DLSC injections. The PAG injections resulted in
               significantly lower amounts of circling than the DLSC GABA
               injections, but they resulted in equivalent measures of
               asymmetry. These results demonstrate that DLSC GABA produces
               circling and asymmetry, and suggest that the DLSC as well as the
               MRF serve as output stations for the expression of circling
               behavior initiated at the striatum.",
  journal   = "Pharmacol. Biochem. Behav.",
  publisher = "Elsevier",
  volume    =  21,
  number    =  6,
  pages     = "853--858",
  month     =  dec,
  year      =  1984,
  language  = "en"
}

@ARTICLE{Ito2017-gi,
  title     = "Segregation of Visual Response Properties in the Mouse Superior
               Colliculus and Their Modulation during Locomotion",
  author    = "Ito, Shinya and Feldheim, David A and Litke, Alan M",
  abstract  = "The superior colliculus (SC) receives direct input from the
               retina and integrates it with information about sound, touch,
               and state of the animal that is relayed from other parts of the
               brain to initiate specific behavioral outcomes. The superficial
               SC layers (sSC) contain cells that respond to visual stimuli,
               whereas the deep SC layers (dSC) contain cells that also respond
               to auditory and somatosensory stimuli. Here, we used a
               large-scale silicon probe recording system to examine the visual
               response properties of SC cells of head-fixed and alert male
               mice. We found cells with diverse response properties including:
               (1) orientation/direction-selective (OS/DS) cells with a firing
               rate that is suppressed by drifting sinusoidal gratings
               (negative OS/DS cells); (2) suppressed-by-contrast cells; (3)
               cells with complex-like spatial summation nonlinearity; and (4)
               cells with Y-like spatial summation nonlinearity. We also found
               specific response properties that are enriched in different
               depths of the SC. The sSC is enriched with cells with small RFs,
               high evoked firing rates (FRs), and sustained temporal
               responses, whereas the dSC is enriched with the negative OS/DS
               cells and with cells with large RFs, low evoked FRs, and
               transient temporal responses. Locomotion modulates the activity
               of the SC cells both additively and multiplicatively and changes
               the preferred spatial frequency of some SC cells. These results
               provide the first description of the negative OS/DS cells and
               demonstrate that the SC segregates cells with different response
               properties and that the behavioral state of a mouse affects SC
               activity.SIGNIFICANCE STATEMENT The superior colliculus (SC)
               receives visual input from the retina in its superficial layers
               (sSC) and induces eye/head-orientating movements and innate
               defensive responses in its deeper layers (dSC). Despite their
               importance, very little is known about the visual response
               properties of dSC neurons. Using high-density electrode
               recordings and novel model-based analysis, we found several
               novel visual response properties of the SC cells, including
               encoding of a cell's preferred orientation or direction by
               suppression of the firing rate. The sSC and the dSC are enriched
               with cells with different visual response properties. Locomotion
               modulates the cells in the SC. These findings contribute to our
               understanding of how the SC processes visual inputs, a critical
               step in comprehending visually guided behaviors.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  37,
  number    =  35,
  pages     = "8428--8443",
  month     =  aug,
  year      =  2017,
  keywords  = "mouse; silicon probe; superior colliculus; vision",
  language  = "en"
}

@ARTICLE{Bretzner2013-si,
  title     = "{Lhx3-Chx10} reticulospinal neurons in locomotor circuits",
  author    = "Bretzner, Fr{\'e}d{\'e}ric and Brownstone, Robert M",
  abstract  = "Motor behaviors result from the interplay between the brain and
               the spinal cord. Reticulospinal neurons, situated between the
               supraspinal structures that initiate motor movements and the
               spinal cord that executes them, play key integrative roles in
               these behaviors. However, the molecular identities of mammalian
               reticular formation neurons that mediate motor behaviors have
               not yet been determined, thus limiting their study in health and
               disease. In the medullary reticular formation of the mouse, we
               identified neurons that express the transcription factors Lhx3
               and/or Chx10, and demonstrate that these neurons form a
               significant component of glutamatergic reticulospinal pathways.
               Lhx3-positive medullary reticular formation neurons express Fos
               following a locomotor task in the adult, indicating that they
               are active during walking. Furthermore, they receive functional
               inputs from the mesencephalic locomotor region and have
               electrophysiological properties to support tonic repetitive
               firing, both of which are necessary for neurons that mediate the
               descending command for locomotion. Together, these results
               suggest that Lhx3/Chx10 medullary reticular formation neurons
               are involved in locomotion.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  33,
  number    =  37,
  pages     = "14681--14692",
  month     =  sep,
  year      =  2013,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Grillner2020-uq,
  title     = "Current Principles of Motor Control, with Special Reference to
               Vertebrate Locomotion",
  author    = "Grillner, Sten and El Manira, Abdeljabbar",
  abstract  = "The vertebrate control of locomotion involves all levels of the
               nervous system from cortex to the spinal cord. Here, we aim to
               cover all main aspects of this complex behavior, from the
               operation of the microcircuits in the spinal cord to the systems
               and behavioral levels and extend from mammalian locomotion to
               the basic undulatory movements of lamprey and fish. The cellular
               basis of propulsion represents the core of the control system,
               and it involves the spinal central pattern generator networks
               (CPGs) controlling the timing of different muscles, the sensory
               compensation for perturbations, and the brain stem command
               systems controlling the level of activity of the CPGs and the
               speed of locomotion. The forebrain and in particular the basal
               ganglia are involved in determining which motor programs should
               be recruited at a given point of time and can both initiate and
               stop locomotor activity. The propulsive control system needs to
               be integrated with the postural control system to maintain body
               orientation. Moreover, the locomotor movements need to be
               steered so that the subject approaches the goal of the locomotor
               episode, or avoids colliding with elements in the environment or
               simply escapes at high speed. These different aspects will all
               be covered in the review.",
  journal   = "Physiol. Rev.",
  publisher = "physiology.org",
  volume    =  100,
  number    =  1,
  pages     = "271--320",
  month     =  jan,
  year      =  2020,
  keywords  = "basal ganglia; central pattern generators; cerebellum; spinal
               cord; vestibular; visuomotor",
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Kleinman2019-ks,
  title     = "Recurrent neural network models of multi-area computation
               underlying decision-making",
  author    = "Kleinman, M and Chandrasekaran, C and Kao, J C",
  abstract  = "Cognition emerges from the coordination of computations in
               multiple brain areas. However, elucidating these coordinated
               computations within and across brain regions is challenging
               because intra-and inter-areal connectivity are typically
               unknown. Testable hypotheses about …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2019
}

@UNPUBLISHED{Shamash2018-ky,
  title    = "A tool for analyzing electrode tracks from slice histology",
  author   = "Shamash, Philip and Carandini, Matteo and Harris, Kenneth and
              Steinmetz, Nick",
  abstract = "It is now possible to record from hundreds of neurons across
              multiple brain regions in a single electrophysiology experiment.
              An essential step in the ensuing data analysis is to assign
              recorded neurons to the correct brain regions. Brain regions are
              typically identified after the recordings by comparing images of
              brain slices to a reference atlas by eye. This introduces error,
              in particular when slices are not cut at a perfectly coronal
              angle or when electrode tracks span multiple slices. Here we
              introduce SHARP-Track, a tool to localize regions of interest and
              plot the brain regions they pass through. SHARP-Track offers a
              MATLAB user interface to explore the Allen Mouse Brain Atlas,
              register asymmetric slice images to the atlas using manual input,
              and interactively analyze electrode tracks. We find that it
              reduces error compared to localizing electrodes in a reference
              atlas by eye. See [github.com/cortex-lab/allenCCF][1] for the
              software and wiki. [1]: http://github.com/cortex-lab/allenCCF",
  journal  = "bioRxiv",
  pages    = "447995",
  month    =  oct,
  year     =  2018,
  language = "en"
}

@ARTICLE{Savage2017-un,
  title    = "Segregated fronto-cortical and midbrain connections in the mouse
              and their relation to approach and avoidance orienting behaviors",
  author   = "Savage, Michael Anthony and McQuade, Richard and Thiele,
              Alexander",
  abstract = "The orchestration of orienting behaviors requires the interaction
              of many cortical and subcortical areas, for example the superior
              colliculus (SC), as well as prefrontal areas responsible for
              top-down control. Orienting involves different behaviors, such as
              approach and avoidance. In the rat, these behaviors are at least
              partially mapped onto different SC subdomains, the lateral (SCl)
              and medial (SCm), respectively. To delineate the circuitry
              involved in the two types of orienting behavior in mice, we
              injected retrograde tracer into the intermediate and deep layers
              of the SCm and SCl, and thereby determined the main input
              structures to these subdomains. Overall the SCm receives larger
              numbers of afferents compared to the SCl. The prefrontal
              cingulate area (Cg), visual, oculomotor, and auditory areas
              provide strong input to the SCm, while prefrontal motor area 2
              (M2), and somatosensory areas provide strong input to the SCl.
              The prefrontal areas Cg and M2 in turn connect to different
              cortical and subcortical areas, as determined by anterograde
              tract tracing. Even though connectivity pattern often overlap,
              our labeling approaches identified segregated neural circuits
              involving SCm, Cg, secondary visual cortices, auditory areas, and
              the dysgranular retrospenial cortex likely to be involved in
              avoidance behaviors. Conversely, SCl, M2, somatosensory cortex,
              and the granular retrospenial cortex comprise a network likely
              involved in approach/appetitive behaviors.",
  journal  = "J. Comp. Neurol.",
  volume   =  525,
  number   =  8,
  pages    = "1980--1999",
  month    =  jun,
  year     =  2017,
  keywords = "RRID:SCR\_013672; approach behaviors; avoidance behaviors;
              cingulate area; motor cortex area 2; superior colliculus",
  language = "en"
}

@ARTICLE{Lomber2001-zl,
  title    = "Role of the superior colliculus in analyses of space: superficial
              and intermediate layer contributions to visual orienting,
              auditory orienting, and visuospatial discriminations during
              unilateral and bilateral deactivations",
  author   = "Lomber, S G and Payne, B R and Cornwell, P",
  abstract = "The superior colliculus (SC) has been implicated in spatial
              analyses of the environment, although few behavioral studies have
              explicitly tested this role. To test its imputed role in spatial
              analyses, we used a battery of four spatial tasks combined with
              unilateral and bilateral cooling deactivation of the upper and
              intermediate layers of the superior colliculus. We tested the
              abilities of cats to orient to three different stimuli: (1)
              moving visual, (2) stationary visual, (3) stationary white-noise
              aural. Furthermore, we tested the ability of the cats to
              discriminate the relative spatial position of a landmark.
              Unilateral cooling deactivation of the superficial layers of the
              SC induced a profound neglect of both moving and stationary
              visual stimuli presented in, and landmark objects located within,
              the contralateral hemifield. However, responses to auditory
              stimuli were unimpaired. Unilateral cooling deactivation of both
              the superficial and intermediate layers induced a profound
              contralateral neglect of the auditory stimulus. Additional and
              equivalent deactivation of the opposite SC largely restored
              orienting to either moving visual or auditory stimuli, and
              restored landmark position reporting to normal levels. However,
              during bilateral SC deactivation, orienting to the static visual
              stimulus was abolished throughout the entire visual field.
              Overall, unilateral SC deactivation results show that the upper
              and intermediate layers of the SC contribute in different ways to
              guiding behavioral responses to visual and auditory stimuli cues.
              Finally, bilateral superior colliculus deactivations reveal that
              other structures are sufficient to support spatial analyses and
              guide visual behaviors in the absence of neural operations in the
              superior colliculus, but only under certain circumstances.",
  journal  = "J. Comp. Neurol.",
  volume   =  441,
  number   =  1,
  pages    = "44--57",
  month    =  dec,
  year     =  2001,
  language = "en"
}

@ARTICLE{Angelaki2019-ky,
  title    = "The head direction cell network: attractor dynamics, integration
              within the navigation system, and three-dimensional properties",
  author   = "Angelaki, Dora E and Laurens, Jean",
  abstract = "Knowledge of head direction cell function has progressed
              remarkably in recent years. The predominant theory that they form
              an attractor has been confirmed by several experiments. Candidate
              pathways that may convey visual input have been identified. The
              pre-subicular circuitry that conveys head direction signals to
              the medial entorhinal cortex, potentially sustaining path
              integration by grid cells, has been resolved. Although the
              neuronal substrate of the attractor remains unknown in mammals, a
              simple head direction network, whose structure is astoundingly
              similar to neuronal models theorized decades earlier, has been
              identified in insects. Finally, recent experiments have revealed
              that these cells do not encode head direction in the horizontal
              plane only, but also in vertical planes, thus providing a 3D
              orientation signal.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  60,
  pages    = "136--144",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@ARTICLE{Sauerbrei2019-uc,
  title    = "Cortical pattern generation during dexterous movement is
              input-driven",
  author   = "Sauerbrei, Britton A and Guo, Jian-Zhong and Cohen, Jeremy D and
              Mischiati, Matteo and Guo, Wendy and Kabra, Mayank and Verma,
              Nakul and Mensh, Brett and Branson, Kristin and Hantman, Adam W",
  abstract = "The motor cortex controls skilled arm movement by sending
              temporal patterns of activity to lower motor centres1. Local
              cortical dynamics are thought to shape these patterns throughout
              movement execution2-4. External inputs have been implicated in
              setting the initial state of the motor cortex5,6, but they may
              also have a pattern-generating role. Here we dissect the
              contribution of local dynamics and inputs to cortical pattern
              generation during a prehension task in mice. Perturbing cortex to
              an aberrant state prevented movement initiation, but after the
              perturbation was released, cortex either bypassed the normal
              initial state and immediately generated the pattern that controls
              reaching or failed to generate this pattern. The difference in
              these two outcomes was probably a result of external inputs. We
              directly investigated the role of inputs by inactivating the
              thalamus; this perturbed cortical activity and disrupted limb
              kinematics at any stage of the movement. Activation of
              thalamocortical axon terminals at different frequencies disrupted
              cortical activity and arm movement in a graded manner.
              Simultaneous recordings revealed that both thalamic activity and
              the current state of cortex predicted changes in cortical
              activity. Thus, the pattern generator for dexterous arm movement
              is distributed across multiple, strongly interacting brain
              regions.",
  journal  = "Nature",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Sabatini2019-zw,
  title    = "The impact of reporter kinetics on the interpretation of data
              gathered with fluorescent reporters",
  author   = "Sabatini, Bernardo L",
  abstract = "Abstract Fluorescent reporters of biological functions are used
              to monitor biochemical events and signals in cells and tissue.
              For neurobiology, these have been particularly useful for
              monitoring signals in the brains of behaving animals. In order to
              enhance signal-to-noise, fluorescent reporters typically have
              kinetics that are slower than that of the underlying biological
              process. This low-pass filtering by the reporter renders the
              fluorescence transient a leaking integrated version of the
              biological signal. Here I discuss the effects that low-pass
              filtering, or more precisely of integrating by convolving with an
              exponentially decaying kernel, has on the interpretation of the
              relationship between the reporter fluorescence transient and the
              events that underlie it. Unfortunately, when the biological
              events being monitored are impulse-like, such as the firing of an
              action potential or the release of neurotransmitter, filtering
              greatly reduces the maximum correlation coefficient that can be
              found between the events and the fluorescence signal. This can
              erroneously support the conclusion that the fluorescence
              transient and the biological signal that it reports are only
              weakly related. Furthermore, when examining the encoding of
              behavioral state variables by nervous system, filtering by the
              reporter kinetics will favor the interpretation that fluorescence
              transients encode integrals of measured variables as opposed to
              the variables themselves. For these reasons, it is necessary to
              take into account the filtering effects of the indicator by
              deconvolving with the convolution kernel and recovering the
              underlying biological events before making conclusions about what
              is encoded in the signals emitted by fluorescent reporters.",
  journal  = "bioRxiv",
  pages    = "834895",
  month    =  nov,
  year     =  2019,
  language = "en"
}

@ARTICLE{Reinhard2019-zc,
  title    = "A projection specific logic to sampling visual inputs in mouse
              superior colliculus",
  author   = "Reinhard, Katja and Li, Chen and Do, Quan and Burke, Emily G and
              Heynderickx, Steven and Farrow, Karl",
  abstract = "Using sensory information to trigger different behaviors relies
              on circuits that pass through brain regions. The rules by which
              parallel inputs are routed to downstream targets are poorly
              understood. The superior colliculus mediates a set of innate
              behaviors, receiving input from >30 retinal ganglion cell types
              and projecting to behaviorally important targets including the
              pulvinar and parabigeminal nucleus. Combining transsynaptic
              circuit tracing with in vivo and ex vivo electrophysiological
              recordings, we observed a projection-specific logic where each
              collicular output pathway sampled a distinct set of retinal
              inputs. Neurons projecting to the pulvinar or the parabigeminal
              nucleus showed strongly biased sampling from four cell types
              each, while six others innervated both pathways. The visual
              response properties of retinal ganglion cells correlated well
              with those of their disynaptic targets. These findings open the
              possibility that projection-specific sampling of retinal inputs
              forms a basis for the selective triggering of behaviors by the
              superior colliculus.",
  journal  = "Elife",
  volume   =  8,
  month    =  nov,
  year     =  2019,
  keywords = "mouse; neuroscience; parabigeminal nucleus; pulvinar; retina;
              superior colliculus; visual circuits",
  language = "en"
}

@UNPUBLISHED{Kietzmann2018-ou,
  title    = "Deep Neural Networks in Computational Neuroscience",
  author   = "Kietzmann, Tim C and McClure, Patrick and Kriegeskorte, Nikolaus",
  abstract = "Summary The goal of computational neuroscience is to find
              mechanistic explanations of how the nervous system processes
              information to give rise to cognitive function and behaviour. At
              the heart of the field are its models, i.e. mathematical and
              computational descriptions of the system being studied, which map
              sensory stimuli to neural responses and/or neural to behavioural
              responses. These models range from simple to complex. Recently,
              deep neural networks (DNNs) have come to dominate several domains
              of artificial intelligence (AI). As the term ``neural network''
              suggests, these models are inspired by biological brains.
              However, current DNNs neglect many details of biological neural
              networks. These simplifications contribute to their computational
              efficiency, enabling them to perform complex feats of
              intelligence, ranging from perceptual (e.g. visual object and
              auditory speech recognition) to cognitive tasks (e.g. machine
              translation), and on to motor control (e.g. playing computer
              games or controlling a robot arm). In addition to their ability
              to model complex intelligent behaviours, DNNs excel at predicting
              neural responses to novel sensory stimuli with accuracies well
              beyond any other currently available model type. DNNs can have
              millions of parameters, which are required to capture the domain
              knowledge needed for successful task performance. Contrary to the
              intuition that this renders them into impenetrable black boxes,
              the computational properties of the network units are the result
              of four directly manipulable elements: input statistics, network
              structure, functional objective, and learning algorithm. With
              full access to the activity and connectivity of all units,
              advanced visualization techniques, and analytic tools to map
              network representations to neural data, DNNs represent a powerful
              framework for building task-performing models and will drive
              substantial insights in computational neuroscience.",
  journal  = "bioRxiv",
  pages    = "133504",
  month    =  jun,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Nallapu2019-wq,
  title    = "Interacting roles of lateral and medial Orbitofrontal cortex in
              decision-making and learning : A system-level computational model",
  author   = "Nallapu, Bhargav Teja and Alexandre, Fr{\'e}d{\'e}ric",
  abstract = "In the context of flexible and adaptive animal behavior, the
              orbitofrontal cortex (OFC) is found to be one of the crucial
              regions in the prefrontal cortex (PFC) influencing the downstream
              processes of decision-making and learning in the sub-cortical
              regions. Although OFC has been implicated to be important in a
              variety of related behavioral processes, the exact mechanisms are
              unclear, through which the OFC encodes or processes information
              related to decision-making and learning. Here, we propose a
              systems-level view of the OFC, positioning it at the nexus of
              sub-cortical systems and other prefrontal regions. Particularly
              we focus on one of the most recent implications of
              neuroscientific evidences regarding the OFC - possible functional
              dissociation between two of its sub-regions : lateral and medial.
              We present a system-level computational model of decision-making
              and learning involving the two sub-regions taking into account
              their individual roles as commonly implicated in neuroscientific
              studies. We emphasize on the role of the interactions between the
              sub-regions within the OFC as well as the role of other
              sub-cortical structures which form a network with them. We
              leverage well-known computational architecture of
              thalamo-cortical basal ganglia loops, accounting for recent
              experimental findings on monkeys with lateral and medial OFC
              lesions, performing a 3-arm bandit task. First we replicate the
              seemingly dissociate effects of lesions to lateral and medial OFC
              during decision-making as a function of value-difference of the
              presented options. Further we demonstrate and argue that such an
              effect is not necessarily due to the dissociate roles of both the
              subregions, but rather a result of complex temporal dynamics
              between the interacting networks in which they are involved.
              Author summary We first highlight the role of the Orbitofrontal
              Cortex (OFC) in value-based decision making and goal-directed
              behavior in primates. We establish the position of OFC at the
              intersection of cortical mechanisms and thalamo-basal ganglial
              circuits. In order to understand possible mechanisms through
              which the OFC exerts emotional control over behavior, among
              several other possibilities, we consider the case of dissociate
              roles of two of its topographical subregions - lateral and medial
              parts of OFC. We gather predominant roles of each of these
              sub-regions as suggested by numerous experimental evidences in
              the form of a system-level computational model that is based on
              existing neuronal architectures. We argue that besides possible
              dissociation, there could be possible interaction of these
              sub-regions within themselves and through other sub-cortical
              structures, in distinct mechanisms of choice and learning. The
              computational framework described accounts for experimental data
              and can be extended to more comprehensive detail of
              representations required to understand the processes of
              decision-making, learning and the role of OFC and subsequently
              the regions of prefrontal cortex in general.",
  journal  = "bioRxiv",
  pages    = "867515",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@ARTICLE{Yoo2019-jz,
  title    = "The Transition from Evaluation to Selection Involves Neural
              Subspace Reorganization in Core Reward Regions",
  author   = "Yoo, Seng Bum Michael and Hayden, Benjamin Y",
  abstract = "Economic choice proceeds from evaluation, in which we contemplate
              options, to selection, in which we weigh options and choose one.
              These stages must be differentiated so that decision makers do
              not proceed to selection before evaluation is complete. We
              examined responses of neurons in two core reward regions,
              orbitofrontal (OFC) and ventromedial prefrontal cortex (vmPFC),
              during two-option choice with asynchronous offer presentation.
              Our data suggest that neurons selective during the first
              (presumed evaluation) and second (presumed comparison and
              selection) offer epochs come from a single pool. Stage transition
              is accompanied by a shift toward orthogonality in the
              low-dimensional population response manifold. Nonetheless, the
              relative position of each option in driving responses in the
              population subspace is preserved. The orthogonalization we
              observe supports the hypothesis that the transition from
              evaluation to selection leads to reorganization of response
              subspace and suggests a mechanism by which value-related signals
              are prevented from prematurely driving choice.",
  journal  = "Neuron",
  month    =  nov,
  year     =  2019,
  keywords = "comparison; covariance matrix; neuroeconomics; orbitofrontal
              cortex; orthogonalization; valuation; ventromedial prefrontal
              cortex",
  language = "en"
}

@ARTICLE{Woon2019-lj,
  title    = "Involvement of the rodent prelimbic and medial orbitofrontal
              cortices in goal-directed action: A brief review",
  author   = "Woon, Ellen P and Sequeira, Michelle K and Barbee, Britton R and
              Gourley, Shannon L",
  abstract = "Goal-directed action refers to selecting behaviors based on the
              expectation that they will be reinforced with desirable outcomes.
              It is typically conceptualized as opposing habit-based behaviors,
              which are instead supported by stimulus-response associations and
              insensitive to consequences. The prelimbic prefrontal cortex (PL)
              is positioned along the medial wall of the rodent prefrontal
              cortex. It is indispensable for action-outcome-driven
              (goal-directed) behavior, consolidating action-outcome
              relationships and linking contextual information with
              instrumental behavior. In this brief review, we will discuss the
              growing list of molecular factors involved in PL function.
              Ventral to the PL is the medial orbitofrontal cortex (mOFC). We
              will also summarize emerging evidence from rodents (complementing
              existing literature describing humans) that it too is involved in
              action-outcome conditioning. We describe experiments using
              procedures that quantify responding based on reward value, the
              likelihood of reinforcement, or effort requirements, touching
              also on experiments assessing food consumption more generally. We
              synthesize these findings with the argument that the mOFC is
              essential to goal-directed action when outcome value information
              is not immediately observable and must be recalled and inferred.",
  journal  = "J. Neurosci. Res.",
  month    =  dec,
  year     =  2019,
  keywords = "action-outcome; contingency degradation; devaluation; habit;
              mouse; rat; response-outcome; review; reward",
  language = "en"
}

@ARTICLE{Kao2019-hv,
  title    = "Considerations in using recurrent neural networks to probe neural
              dynamics",
  author   = "Kao, Jonathan C",
  abstract = "Recurrent neural networks (RNNs) are increasingly being used to
              model complex cognitive and motor tasks performed by behaving
              animals. RNNs are trained to reproduce animal behavior while also
              capturing key statistics of empirically recorded neural activity.
              In this manner, the RNN can be viewed as an in silico circuit
              whose computational elements share similar motifs with the
              cortical area it is modeling. Furthermore, because the RNN's
              governing equations and parameters are fully known, they can be
              analyzed to propose hypotheses for how neural populations
              compute. In this context, we present important considerations
              when using RNNs to model motor behavior in a delayed reach task.
              First, by varying the network's nonlinear activation and rate
              regularization, we show that RNNs reproducing single-neuron
              firing rate motifs may not adequately capture important
              population motifs. Second, we find that even when RNNs reproduce
              key neurophysiological features on both the single neuron and
              population levels, they can do so through distinctly different
              dynamical mechanisms. To distinguish between these mechanisms, we
              show that an RNN consistent with a previously proposed dynamical
              mechanism is more robust to input noise. Finally, we show that
              these dynamics are sufficient for the RNN to generalize to tasks
              it was not trained on. Together, these results emphasize
              important considerations when using RNN models to probe neural
              dynamics.NEW \& NOTEWORTHY Artificial neurons in a recurrent
              neural network (RNN) may resemble empirical single-unit activity
              but not adequately capture important features on the neural
              population level. Dynamics of RNNs can be visualized in
              low-dimensional projections to provide insight into the RNN's
              dynamical mechanism. RNNs trained in different ways may reproduce
              neurophysiological motifs but do so with distinctly different
              mechanisms. RNNs trained to only perform a delayed reach task can
              generalize to perform tasks where the target is switched or the
              target location is changed.",
  journal  = "J. Neurophysiol.",
  volume   =  122,
  number   =  6,
  pages    = "2504--2521",
  month    =  dec,
  year     =  2019,
  keywords = "artificial neural network; motor cortex; neural computation;
              neural dynamics; recurrent neural network;RNN To read;RNN",
  language = "en"
}

@ARTICLE{Wang2019-ot,
  title    = "Zona Incerta: An Integrative Node for Global Behavioral
              Modulation",
  author   = "Wang, Xiyue and Chou, Xiao-Lin and Zhang, Li I and Tao, Huizhong
              Whit",
  abstract = "Zona incerta (ZI) is a largely inhibitory subthalamic region
              connecting with many brain areas. Early studies have suggested
              involvement of ZI in various functions such as visceral
              activities, arousal, attention, and locomotion, but the specific
              roles of different ZI subdomains or cell types have not been well
              examined. Recent studies combining optogenetics, behavioral
              assays, neural tracing, and neural activity-recording reveal
              novel functional roles of ZI depending on specific input-output
              connectivity patterns. Here, we review these studies and
              summarize functions of ZI into four categories: sensory
              integration, behavioral output control, motivational drive, and
              neural plasticity. In view of these new findings, we propose that
              ZI serves as an integrative node for global modulation of
              behaviors and physiological states.",
  journal  = "Trends Neurosci.",
  month    =  dec,
  year     =  2019,
  keywords = "animal behavior; gain modulation; inhibitory nucleus;
              input/output pattern; motivation; neural plasticity;
              physiological state; processing node; subthalamic region",
  language = "en"
}

@ARTICLE{Marques2019-dw,
  title    = "Internal state dynamics shape brainwide activity and foraging
              behaviour",
  author   = "Marques, Jo{\~a}o C and Li, Meng and Schaak, Diane and Robson,
              Drew N and Li, Jennifer M",
  abstract = "The brain has persistent internal states that can modulate every
              aspect of an animal's mental experience1-4. In complex tasks such
              as foraging, the internal state is dynamic5-8. Caenorhabditis
              elegans alternate between local search and global dispersal5.
              Rodents and primates exhibit trade-offs between exploitation and
              exploration6,7. However, fundamental questions remain about how
              persistent states are maintained in the brain, which upstream
              networks drive state transitions and how state-encoding neurons
              exert neuromodulatory effects on sensory perception and
              decision-making to govern appropriate behaviour. Here, using
              tracking microscopy to monitor whole-brain neuronal activity at
              cellular resolution in freely moving zebrafish larvae9, we show
              that zebrafish spontaneously alternate between two persistent
              internal states during foraging for live prey (Paramecia). In the
              exploitation state, the animal inhibits locomotion and promotes
              hunting, generating small, localized trajectories. In the
              exploration state, the animal promotes locomotion and suppresses
              hunting, generating long-ranging trajectories that enhance
              spatial dispersion. We uncover a dorsal raphe subpopulation with
              persistent activity that robustly encodes the exploitation state.
              The exploitation-state-encoding neurons, together with a
              multimodal trigger network that is associated with state
              transitions, form a stochastically activated nonlinear dynamical
              system. The activity of this oscillatory network correlates with
              a global retuning of sensorimotor transformations during foraging
              that leads to marked changes in both the motivation to hunt for
              prey and the accuracy of motor sequences during hunting. This
              work reveals an important hidden variable that shapes the
              temporal structure of motivation and decision-making.",
  journal  = "Nature",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Sanchez-Bellot2019-me,
  title    = "Push-pull regulation of exploratory behavior by two opposing
              hippocampal to prefrontal cortex pathways",
  author   = "S{\'a}nchez-Bellot, Candela and MacAskill, Andrew F",
  abstract = "We found that the hippocampal projection to prefrontal cortex is
              composed of two parallel circuits located in the superficial or
              deep hippocampal pyramidal layers. These circuits have unique
              upstream and downstream connectivity, and are differentially
              active during exploration of a potentially threatening
              environment. Artificial activation of the superficial circuit
              promotes exploration via preferential recruitment of PFC
              inhibition, while activation of the deep circuit promotes
              avoidance via direct excitation.",
  journal  = "bioRxiv",
  pages    = "2019.12.18.880831",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@ARTICLE{Pollock_undated-sq,
  title  = "Engineering recurrent neural networks from task-relevant manifolds
            and dynamics",
  author = "Pollock, Eli and Jazayeri, Mehrdad"
}

@ARTICLE{Mearns2019-md,
  title     = "Deconstructing Hunting Behavior Reveals a Tightly Coupled
               {Stimulus-Response} Loop",
  author    = "Mearns, Duncan S and Donovan, Joseph C and Fernandes,
               Ant{\'o}nio M and Semmelhack, Julia L and Baier, Herwig",
  abstract  = "SummaryAnimal behavior often forms sequences, built from simple
               stereotyped actions and shaped by environmental cues. A
               comprehensive characterization of the interplay between an
               animal's movements and its environment is necessary to
               understand the sensorimotor transformations performed by the
               brain. Here, we use unsupervised methods to study behavioral
               sequences in zebrafish larvae. We generate a map of swim bouts,
               revealing that fish modulate their tail movements along a
               continuum. During prey capture, larvae produce stereotyped
               sequences using a subset of bouts from a broader behavioral
               repertoire. These sequences exhibit low-order transition
               dynamics and immediately respond to changes in visual cues.
               Chaining of prey capture bouts is disrupted in visually impaired
               (lakritz and blumenkohl) mutants, and removing the prey stimulus
               during ongoing behavior in closed-loop virtual reality causes
               larvae to immediately abort the hunting sequence. These results
               suggest that the continuous integration of sensory information
               is necessary to structure the behavior. This stimulus-response
               loop serves to bring prey into the anterior dorsal visual field
               of the larvae. Fish then release a capture strike maneuver
               comprising a stereotyped jaw movement and tail movements
               fine-tuned to the distance of the prey. Fish with only one
               intact eye fail to correctly position the prey in the strike
               zone, but are able to produce the strike itself. Our analysis
               shows that short-term integration of binocular visual cues
               shapes the behavioral dynamics of hunting, thus uncovering the
               temporal organization of a goal-directed behavior in a
               vertebrate.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  0,
  number    =  0,
  month     =  dec,
  year      =  2019,
  keywords  = "zebrafish; ethology; prey capture; unsupervised machine
               learning; behavioral sequences",
  language  = "en"
}

@ARTICLE{Lefler2019-ke,
  title    = "The role of the periaqueductal gray in escape behavior",
  author   = "Lefler, Yaara and Campagner, Dario and Branco, Tiago",
  abstract = "Escape behavior is a defensive action deployed by animals in
              response to imminent threats. In mammalian species, a variety of
              different brain circuits are known to participate in this crucial
              survival behavior. One of these circuits is the periaqueductal
              gray, a midbrain structure that can command a variety of
              instinctive behaviors. Recent experiments using modern systems
              neuroscience techniques have begun to elucidate the specific role
              of the periaqueductal gray in controlling escape. These have
              shown that periaqueductal gray neurons are crucial units for
              gating and commanding the initiation of escape, specifically
              activated in situations of imminent, escapable threat. In
              addition, it is becoming clear that the periaqueductal gray
              integrates brain-wide information that can modulate escape
              initiation to generate flexible defensive behaviors.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  60,
  pages    = "115--121",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@ARTICLE{Perreault2019-da,
  title    = "Diversity of reticulospinal systems in mammals",
  author   = "Perreault, Marie-Claude and Giorgi, Andrea",
  abstract = "Reticulospinal (RS) neurons provide the spinal cord with the
              executive signals for a large repertoire of motor and autonomic
              functions, ensuring at the same time that these functions are
              adapted to the different behavioral contexts. This requires the
              coordinated action of many RS neurons. In this mini-review, we
              examine how the RS neurons that carry out specific functions
              distribute across the three parts of the brain stem. Extensive
              overlap between populations suggests a need to explore
              multi-functionality at the single cell-level. We next contrast
              functional diversity and homogeneity in transmitter phenotype.
              Then, we examine the molecular genetic mechanisms that specify
              brain stem development and likely contribute to RS neurons
              identities. We advocate that a better knowledge of the
              developmental lineage of the RS neurons and a better knowledge of
              RS neuron activity across multiple behaviors will help uncover
              the fundamental principles behind the diversity of RS systems in
              mammals.",
  journal  = "Curr Opin Physiol",
  volume   =  8,
  pages    = "161--169",
  month    =  apr,
  year     =  2019,
  keywords = "Brain Stem; Control of Movement and Bodily Functions; Reticular
              Formation; Reticulospinal",
  language = "en"
}

@UNPUBLISHED{Finkelstein2019-ne,
  title    = "Attractor dynamics gate cortical information flow during
              decision-making",
  author   = "Finkelstein, Arseny and Fontolan, Lorenzo and Economo, Michael N
              and Li, Nuo and Romani, Sandro and Svoboda, Karel",
  abstract = "Decisions about future actions are held in memory until enacted,
              making them vulnerable to distractors. The neural mechanisms
              controlling decision robustness to distractors remain unknown. We
              trained mice to report optogenetic stimulation of somatosensory
              cortex, with a delay separating sensation and action. Distracting
              stimuli influenced behavior less when delivered later during
              delay --- demonstrating temporal gating of sensory information
              flow. Gating occurred even though distractor-evoked activity
              percolated through the cortex without attenuation. Instead,
              choice-related dynamics in frontal cortex became progressively
              robust to distractors as time passed. Reverse-engineering of
              neural networks trained to reproduce frontal-cortex activity
              revealed that chosen actions were stabilized via attractor
              dynamics, which gated out distracting stimuli. Our results reveal
              a dynamic gating mechanism that operates by controlling the
              degree of commitment to a chosen course of action.",
  journal  = "bioRxiv",
  pages    = "2019.12.14.876425",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Isa2019-ww,
  title    = "Difference in context-dependency between orienting and
              defense-like responses induced by the superior colliculus",
  author   = "Isa, Kaoru and Sooksawate, Thongchai and Kobayashi, Kenta and
              Kobayashi, Kazuto and Redgrave, Peter and Isa, Tadashi",
  abstract = "Abstract Previous electrical stimulation and lesion experiments
              have suggested that the crossed descending output pathway from
              the deeper layers (SCd) of superior colliculus (SC) controls
              orienting responses, while the uncrossed pathway mediates
              defense-like behavior. Here we extended these investigations by
              using selective optogenetic activation of each pathway in mice
              with channelrhodopsin 2 expression by double viral vector
              techniques. Brief photo-stimulation of the crossed pathway evoked
              short latency contraversive orienting-like head turns, while
              extended stimulation induced contraversive circling responses. In
              contrast, stimulation of uncrossed pathway induced short-latency
              upward head movements followed by longer-latency defense-like
              behaviors including retreat and flight. The novel discovery was
              that the evoked defense-like responses varied depending on the
              environment, suggesting that uncrossed output can be influenced
              by top-down modification of the SC or its downstream. This
              further suggests that the SCd-defense system can be profoundly
              modulated by non-motor, affective and cognitive components, in
              addition to direct sensory inputs.",
  journal  = "bioRxiv",
  pages    = "729772",
  month    =  aug,
  year     =  2019,
  language = "en"
}

@ARTICLE{Stone2017-ix,
  title    = "An Anatomically Constrained Model for Path Integration in the Bee
              Brain",
  author   = "Stone, Thomas and Webb, Barbara and Adden, Andrea and Weddig,
              Nicolai Ben and Honkanen, Anna and Templin, Rachel and Wcislo,
              William and Scimeca, Luca and Warrant, Eric and Heinze, Stanley",
  abstract = "Path integration is a widespread navigational strategy in which
              directional changes and distance covered are continuously
              integrated on an outward journey, enabling a straight-line return
              to home. Bees use vision for this task-a celestial-cue-based
              visual compass and an optic-flow-based visual odometer-but the
              underlying neural integration mechanisms are unknown. Using
              intracellular electrophysiology, we show that
              polarized-light-based compass neurons and optic-flow-based
              speed-encoding neurons converge in the central complex of the bee
              brain, and through block-face electron microscopy, we identify
              potential integrator cells. Based on plausible output targets for
              these cells, we propose a complete circuit for path integration
              and steering in the central complex, with anatomically identified
              neurons suggested for each processing step. The resulting model
              circuit is thus fully constrained biologically and provides a
              functional interpretation for many previously unexplained
              architectural features of the central complex. Moreover, we show
              that the receptive fields of the newly discovered speed neurons
              can support path integration for the holonomic motion (i.e., a
              ground velocity that is not precisely aligned with body
              orientation) typical of bee flight, a feature not captured in any
              previously proposed model of path integration. In a broader
              context, the model circuit presented provides a general mechanism
              for producing steering signals by comparing current and desired
              headings-suggesting a more basic function for central complex
              connectivity, from which path integration may have evolved.",
  journal  = "Curr. Biol.",
  volume   =  27,
  number   =  20,
  pages    = "3069--3085.e11",
  month    =  oct,
  year     =  2017,
  keywords = "central complex; circuit modeling; compass orientation; insect
              brain; navigation; neuroanatomy; optic flow; path integration;
              polarized light; robotics",
  language = "en"
}

@UNPUBLISHED{Plitt2019-hy,
  title    = "Experience dependent contextual codes in the hippocampus",
  author   = "Plitt, Mark H and Giocomo, Lisa M",
  abstract = "The hippocampus is a medial temporal lobe brain structure that
              contains circuitry and neural representations capable of
              supporting declarative memory. Hippocampal place cells fire in
              one or few restricted spatial locations in a given environment.
              Between environmental contexts, place cell firing fields remap
              (turning on/off or moving to a new spatial location), providing a
              unique population-wide neural code for context specificity.
              However, the manner by which features associated with a given
              context combine to drive place cell remapping remains a matter of
              debate. Here we show that remapping of neural representations in
              region CA1 of the hippocampus is strongly driven by prior beliefs
              about the frequency of certain contexts, and that remapping is
              equivalent to an optimal estimate of the identity of the current
              context under that prior. This prior-driven remapping is learned
              early in training and remains robust to changes in behavioral
              task-demands. Furthermore, a simple associative learning
              mechanism is sufficient to reproduce these results. Our findings
              demonstrate that place cell remapping is a generalization of
              representing an animal9s location. Rather than simply
              representing location in physical space, the hippocampus
              represents an optimal estimate of location in a multi-dimensional
              stimulus space.",
  journal  = "bioRxiv",
  pages    = "864090",
  month    =  dec,
  year     =  2019,
  language = "en"
}

@ARTICLE{Wang2020-ee,
  title    = "Egocentric and allocentric representations of space in the rodent
              brain",
  author   = "Wang, Cheng and Chen, Xiaojing and Knierim, James J",
  abstract = "Spatial signals are prevalent within the hippocampus and its
              neighboring regions. It is generally accepted that these signals
              are defined with respect to the external world (i.e., a
              world-centered, or allocentric, frame of reference). Recently,
              evidence of egocentric processing (i.e., self-centered, defined
              relative to the subject) in the extended hippocampal system has
              accumulated. These results support the idea that egocentric
              sensory information, derived from primary sensory cortical areas,
              may be transformed to allocentric representations that interact
              with the allocentric hippocampal system. We propose a framework
              to explain the implications of the egocentric-allocentric
              transformations to the functions of the medial temporal lobe
              memory system.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  60,
  pages    = "12--20",
  month    =  feb,
  year     =  2020
}

@ARTICLE{Hoy2019-jh,
  title    = "Defined Cell Types in Superior Colliculus Make Distinct
              Contributions to Prey Capture Behavior in the Mouse",
  author   = "Hoy, Jennifer L and Bishop, Hannah I and Niell, Cristopher M",
  abstract = "The superior colliculus (SC) plays a highly conserved role in
              visual processing and mediates visual orienting behaviors across
              species, including both overt motor orienting [1, 2] and
              orienting of attention [3, 4]. To determine the specific circuits
              within the superficial superior colliculus (sSC) that drive
              orienting and approach behavior toward appetitive stimuli, we
              explored the role of three genetically defined cell types in
              mediating prey capture in mice. Chemogenetic inactivation of two
              classically defined cell types, the wide-field (WF) and
              narrow-field (NF) vertical neurons, revealed that they are
              involved in distinct aspects of prey capture. WF neurons were
              required for rapid prey detection and distant approach
              initiation, whereas NF neurons were required for accurate
              orienting during pursuit as well as approach initiation and
              continuity. In contrast, prey capture did not require
              parvalbumin-expressing (PV) neurons that have previously been
              implicated in fear responses. The visual coding and projection
              targets of WF and NF cells were consistent with their roles in
              prey detection versus pursuit, respectively. Thus, our studies
              link specific neural circuit connectivity and function with
              stimulus detection and orienting behavior, providing insight into
              visuomotor and attentional mechanisms mediated by superior
              colliculus.",
  journal  = "Curr. Biol.",
  month    =  nov,
  year     =  2019,
  keywords = "mouse vision; prey capture; receptive fields; superior colliculus",
  language = "en"
}

@ARTICLE{Winnubst2019-eo,
  title    = "Reconstruction of 1,000 Projection Neurons Reveals New Cell Types
              and Organization of {Long-Range} Connectivity in the Mouse Brain",
  author   = "Winnubst, Johan and Bas, Erhan and Ferreira, Tiago A and Wu,
              Zhuhao and Economo, Michael N and Edson, Patrick and Arthur, Ben
              J and Bruns, Christopher and Rokicki, Konrad and Schauder, David
              and Olbris, Donald J and Murphy, Sean D and Ackerman, David G and
              Arshadi, Cameron and Baldwin, Perry and Blake, Regina and
              Elsayed, Ahmad and Hasan, Mashtura and Ramirez, Daniel and Dos
              Santos, Bruno and Weldon, Monet and Zafar, Amina and Dudman,
              Joshua T and Gerfen, Charles R and Hantman, Adam W and Korff,
              Wyatt and Sternson, Scott M and Spruston, Nelson and Svoboda,
              Karel and Chandrashekar, Jayaram",
  abstract = "Neuronal cell types are the nodes of neural circuits that
              determine the flow of information within the brain. Neuronal
              morphology, especially the shape of the axonal arbor, provides an
              essential descriptor of cell type and reveals how individual
              neurons route their output across the brain. Despite the
              importance of morphology, few projection neurons in the mouse
              brain have been reconstructed in their entirety. Here we present
              a robust and efficient platform for imaging and reconstructing
              complete neuronal morphologies, including axonal arbors that span
              substantial portions of the brain. We used this platform to
              reconstruct more than 1,000 projection neurons in the motor
              cortex, thalamus, subiculum, and hypothalamus. Together, the
              reconstructed neurons constitute more than 85 meters of axonal
              length and are available in a searchable online database. Axonal
              shapes revealed previously unknown subtypes of projection neurons
              and suggest organizational principles of long-range connectivity.",
  journal  = "Cell",
  volume   =  179,
  number   =  1,
  pages    = "268--281.e13",
  month    =  sep,
  year     =  2019,
  keywords = "automated reconstruction; axonal morphology; long-range
              projections; morphology database; neuronal cell types; neuronal
              connectivity; projection neurons; single-cell reconstruction;
              whole brain",
  language = "en"
}

@ARTICLE{Ragan2012-yo,
  title     = "Serial two-photon tomography for automated ex vivo mouse brain
               imaging",
  author    = "Ragan, Timothy and Kadiri, Lolahon R and Venkataraju, Kannan
               Umadevi and Bahlmann, Karsten and Sutin, Jason and Taranda,
               Julian and Arganda-Carreras, Ignacio and Kim, Yongsoo and Seung,
               H Sebastian and Osten, Pavel",
  abstract  = "Here we describe an automated method, named serial two-photon
               (STP) tomography, that achieves high-throughput fluorescence
               imaging of mouse brains by integrating two-photon microscopy and
               tissue sectioning. STP tomography generates high-resolution
               datasets that are free of distortions and can be readily warped
               in three dimensions, for example, for comparing multiple
               anatomical tracings. This method opens the door to routine
               systematic studies of neuroanatomy in mouse models of human
               brain disorders.",
  journal   = "Nat. Methods",
  publisher = "nature.com",
  volume    =  9,
  number    =  3,
  pages     = "255--258",
  month     =  jan,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Kuan2015-mt,
  title     = "Neuroinformatics of the Allen Mouse Brain Connectivity Atlas",
  author    = "Kuan, Leonard and Li, Yang and Lau, Chris and Feng, David and
               Bernard, Amy and Sunkin, Susan M and Zeng, Hongkui and Dang,
               Chinh and Hawrylycz, Michael and Ng, Lydia",
  abstract  = "The Allen Mouse Brain Connectivity Atlas is a mesoscale whole
               brain axonal projection atlas of the C57Bl/6J mouse brain.
               Anatomical trajectories throughout the brain were mapped into a
               common 3D space using a standardized platform to generate a
               comprehensive and quantitative database of inter-areal and
               cell-type-specific projections. This connectivity atlas has
               several desirable features, including brain-wide coverage,
               validated and versatile experimental techniques, a single
               standardized data format, a quantifiable and integrated
               neuroinformatics resource, and an open-access public online
               database (http://connectivity.brain-map.org/). Meaningful
               informatics data quantification and comparison is key to
               effective use and interpretation of connectome data. This relies
               on successful definition of a high fidelity atlas template and
               framework, mapping precision of raw data sets into the 3D
               reference framework, accurate signal detection and quantitative
               connection strength algorithms, and effective presentation in an
               integrated online application. Here we describe key informatics
               pipeline steps in the creation of the Allen Mouse Brain
               Connectivity Atlas and include basic application use cases.",
  journal   = "Methods",
  publisher = "Elsevier",
  volume    =  73,
  pages     = "4--17",
  month     =  feb,
  year      =  2015,
  keywords  = "Digital atlas; Image registration; Mouse connectivity atlas;
               Neuronal projection; Signal detection",
  language  = "en"
}

@ARTICLE{Sunkin2013-ap,
  title     = "Allen Brain Atlas: an integrated spatio-temporal portal for
               exploring the central nervous system",
  author    = "Sunkin, Susan M and Ng, Lydia and Lau, Chris and Dolbeare, Tim
               and Gilbert, Terri L and Thompson, Carol L and Hawrylycz,
               Michael and Dang, Chinh",
  abstract  = "The Allen Brain Atlas (http://www.brain-map.org) provides a
               unique online public resource integrating extensive gene
               expression data, connectivity data and neuroanatomical
               information with powerful search and viewing tools for the adult
               and developing brain in mouse, human and non-human primate.
               Here, we review the resources available at the Allen Brain
               Atlas, describing each product and data type [such as in situ
               hybridization (ISH) and supporting histology, microarray, RNA
               sequencing, reference atlases, projection mapping and magnetic
               resonance imaging]. In addition, standardized and unique
               features in the web applications are described that enable users
               to search and mine the various data sets. Features include both
               simple and sophisticated methods for gene searches, colorimetric
               and fluorescent ISH image viewers, graphical displays of ISH,
               microarray and RNA sequencing data, Brain Explorer software for
               3D navigation of anatomy and gene expression, and an interactive
               reference atlas viewer. In addition, cross data set searches
               enable users to query multiple Allen Brain Atlas data sets
               simultaneously. All of the Allen Brain Atlas resources can be
               accessed through the Allen Brain Atlas data portal.",
  journal   = "Nucleic Acids Res.",
  publisher = "academic.oup.com",
  volume    =  41,
  number    = "Database issue",
  pages     = "D996--D1008",
  month     =  jan,
  year      =  2013,
  language  = "en"
}

@ARTICLE{Lein2007-di,
  title     = "Genome-wide atlas of gene expression in the adult mouse brain",
  author    = "Lein, Ed S and Hawrylycz, Michael J and Ao, Nancy and Ayres,
               Mikael and Bensinger, Amy and Bernard, Amy and Boe, Andrew F and
               Boguski, Mark S and Brockway, Kevin S and Byrnes, Emi J and
               Chen, Lin and Chen, Li and Chen, Tsuey-Ming and Chin, Mei Chi
               and Chong, Jimmy and Crook, Brian E and Czaplinska, Aneta and
               Dang, Chinh N and Datta, Suvro and Dee, Nick R and Desaki, Aimee
               L and Desta, Tsega and Diep, Ellen and Dolbeare, Tim A and
               Donelan, Matthew J and Dong, Hong-Wei and Dougherty, Jennifer G
               and Duncan, Ben J and Ebbert, Amanda J and Eichele, Gregor and
               Estin, Lili K and Faber, Casey and Facer, Benjamin A and Fields,
               Rick and Fischer, Shanna R and Fliss, Tim P and Frensley, Cliff
               and Gates, Sabrina N and Glattfelder, Katie J and Halverson,
               Kevin R and Hart, Matthew R and Hohmann, John G and Howell,
               Maureen P and Jeung, Darren P and Johnson, Rebecca A and Karr,
               Patrick T and Kawal, Reena and Kidney, Jolene M and Knapik,
               Rachel H and Kuan, Chihchau L and Lake, James H and Laramee,
               Annabel R and Larsen, Kirk D and Lau, Christopher and Lemon,
               Tracy A and Liang, Agnes J and Liu, Ying and Luong, Lon T and
               Michaels, Jesse and Morgan, Judith J and Morgan, Rebecca J and
               Mortrud, Marty T and Mosqueda, Nerick F and Ng, Lydia L and Ng,
               Randy and Orta, Geralyn J and Overly, Caroline C and Pak, Tu H
               and Parry, Sheana E and Pathak, Sayan D and Pearson, Owen C and
               Puchalski, Ralph B and Riley, Zackery L and Rockett, Hannah R
               and Rowland, Stephen A and Royall, Joshua J and Ruiz, Marcos J
               and Sarno, Nadia R and Schaffnit, Katherine and Shapovalova,
               Nadiya V and Sivisay, Taz and Slaughterbeck, Clifford R and
               Smith, Simon C and Smith, Kimberly A and Smith, Bryan I and
               Sodt, Andy J and Stewart, Nick N and Stumpf, Kenda-Ruth and
               Sunkin, Susan M and Sutram, Madhavi and Tam, Angelene and
               Teemer, Carey D and Thaller, Christina and Thompson, Carol L and
               Varnam, Lee R and Visel, Axel and Whitlock, Ray M and Wohnoutka,
               Paul E and Wolkey, Crissa K and Wong, Victoria Y and Wood,
               Matthew and Yaylaoglu, Murat B and Young, Rob C and Youngstrom,
               Brian L and Yuan, Xu Feng and Zhang, Bin and Zwingman, Theresa A
               and Jones, Allan R",
  abstract  = "Molecular approaches to understanding the functional circuitry
               of the nervous system promise new insights into the relationship
               between genes, brain and behaviour. The cellular diversity of
               the brain necessitates a cellular resolution approach towards
               understanding the functional genomics of the nervous system. We
               describe here an anatomically comprehensive digital atlas
               containing the expression patterns of approximately 20,000 genes
               in the adult mouse brain. Data were generated using automated
               high-throughput procedures for in situ hybridization and data
               acquisition, and are publicly accessible online. Newly developed
               image-based informatics tools allow global genome-scale
               structural analysis and cross-correlation, as well as
               identification of regionally enriched genes. Unbiased
               fine-resolution analysis has identified highly specific cellular
               markers as well as extensive evidence of cellular heterogeneity
               not evident in classical neuroanatomical atlases. This highly
               standardized atlas provides an open, primary data resource for a
               wide variety of further studies concerning brain organization
               and function.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  445,
  number    =  7124,
  pages     = "168--176",
  month     =  jan,
  year      =  2007,
  language  = "en"
}

@ARTICLE{Osten2013-ze,
  title    = "Mapping brain circuitry with a light microscope",
  author   = "Osten, Pavel and Margrie, Troy W",
  abstract = "The beginning of the 21st century has seen a renaissance in light
              microscopy and anatomical tract tracing that together are rapidly
              advancing our understanding of the form and function of neuronal
              circuits. The introduction of instruments for automated imaging
              of whole mouse brains, new cell type--specific and trans-synaptic
              tracers, and computational methods for handling the whole-brain
              data sets has opened the door to neuroanatomical studies at an
              unprecedented scale. We present an overview of the present state
              and future opportunities in charting long-range and local
              connectivity in the entire mouse brain and in linking brain
              circuits to function.",
  journal  = "Nat. Methods",
  volume   =  10,
  number   =  6,
  pages    = "515--523",
  month    =  jun,
  year     =  2013,
  language = "en"
}

@ARTICLE{Steinmetz2019-av,
  title     = "Distributed coding of choice, action and engagement across the
               mouse brain",
  author    = "Steinmetz, Nicholas A and Zatka-Haas, Peter and Carandini,
               Matteo and Harris, Kenneth D",
  abstract  = "Vision, choice, action and behavioural engagement arise from
               neuronal activity that may be distributed across brain regions.
               Here we delineate the spatial distribution of neurons underlying
               these processes. We used Neuropixels probes1,2 to record from
               approximately 30,000 neurons in 42 brain regions of mice
               performing a visual discrimination task3. Neurons in nearly all
               regions responded non-specifically when the mouse initiated an
               action. By contrast, neurons encoding visual stimuli and
               upcoming choices occupied restricted regions in the neocortex,
               basal ganglia and midbrain. Choice signals were rare and emerged
               with indistinguishable timing across regions. Midbrain neurons
               were activated before contralateral choices and were suppressed
               before ipsilateral choices, whereas forebrain neurons could
               prefer either side. Brain-wide pre-stimulus activity predicted
               engagement in individual trials and in the overall task, with
               enhanced subcortical but suppressed neocortical activity during
               engagement. These results reveal organizing principles for the
               distribution of neurons encoding behaviourally relevant
               variables across the mouse brain.",
  journal   = "Nature",
  publisher = "Nature Publishing Group",
  pages     = "1--8",
  month     =  nov,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Economo2018-pj,
  title    = "Distinct descending motor cortex pathways and their roles in
              movement",
  author   = "Economo, Michael N and Viswanathan, Sarada and Tasic, Bosiljka
              and Bas, Erhan and Winnubst, Johan and Menon, Vilas and Graybuck,
              Lucas T and Nguyen, Thuc Nghi and Smith, Kimberly A and Yao,
              Zizhen and Wang, Lihua and Gerfen, Charles R and Chandrashekar,
              Jayaram and Zeng, Hongkui and Looger, Loren L and Svoboda, Karel",
  abstract = "Activity in the motor cortex predicts movements, seconds before
              they are initiated. This preparatory activity has been observed
              across cortical layers, including in descending pyramidal tract
              neurons in layer 5. A key question is how preparatory activity is
              maintained without causing movement, and is ultimately converted
              to a motor command to trigger appropriate movements. Here, using
              single-cell transcriptional profiling and axonal reconstructions,
              we identify two types of pyramidal tract neuron. Both types
              project to several targets in the basal ganglia and brainstem.
              One type projects to thalamic regions that connect back to motor
              cortex; populations of these neurons produced early preparatory
              activity that persisted until the movement was initiated. The
              second type projects to motor centres in the medulla and mainly
              produced late preparatory activity and motor commands. These
              results indicate that two types of motor cortex output neurons
              have specialized roles in motor control.",
  journal  = "Nature",
  volume   =  563,
  number   =  7729,
  pages    = "79--84",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@ARTICLE{Cunningham2014-aw,
  title    = "Dimensionality reduction for large-scale neural recordings",
  author   = "Cunningham, John P and Yu, Byron M",
  abstract = "Most sensory, cognitive and motor functions depend on the
              interactions of many neurons. In recent years, there has been
              rapid development and increasing use of technologies for
              recording from large numbers of neurons, either sequentially or
              simultaneously. A key question is what scientific insight can be
              gained by studying a population of recorded neurons beyond
              studying each neuron individually. Here, we examine three
              important motivations for population studies: single-trial
              hypotheses requiring statistical power, hypotheses of population
              response structure and exploratory analyses of large data sets.
              Many recent studies have adopted dimensionality reduction to
              analyze these populations and to find features that are not
              apparent at the level of individual neurons. We describe the
              dimensionality reduction methods commonly applied to population
              activity and offer practical advice about selecting methods and
              interpreting their outputs. This review is intended for
              experimental and computational researchers who seek to understand
              the role dimensionality reduction has had and can have in systems
              neuroscience, and who seek to apply these methods to their own
              data.",
  journal  = "Nat. Neurosci.",
  volume   =  17,
  number   =  11,
  pages    = "1500--1509",
  month    =  nov,
  year     =  2014,
  language = "en"
}

@ARTICLE{Bassett2017-qa,
  title    = "Network neuroscience",
  author   = "Bassett, Danielle S and Sporns, Olaf",
  abstract = "Despite substantial recent progress, our understanding of the
              principles and mechanisms underlying complex brain function and
              cognition remains incomplete. Network neuroscience proposes to
              tackle these enduring challenges. Approaching brain structure and
              function from an explicitly integrative perspective, network
              neuroscience pursues new ways to map, record, analyze and model
              the elements and interactions of neurobiological systems. Two
              parallel trends drive the approach: the availability of new
              empirical tools to create comprehensive maps and record dynamic
              patterns among molecules, neurons, brain areas and social
              systems; and the theoretical framework and computational tools of
              modern network science. The convergence of empirical and
              computational advances opens new frontiers of scientific inquiry,
              including network dynamics, manipulation and control of brain
              networks, and integration of network processes across
              spatiotemporal domains. We review emerging trends in network
              neuroscience and attempt to chart a path toward a better
              understanding of the brain as a multiscale networked system.",
  journal  = "Nat. Neurosci.",
  volume   =  20,
  number   =  3,
  pages    = "353--364",
  month    =  feb,
  year     =  2017,
  language = "en"
}

@ARTICLE{Engel2019-qn,
  title    = "New perspectives on dimensionality and variability from
              large-scale cortical dynamics",
  author   = "Engel, Tatiana A and Steinmetz, Nicholas A",
  abstract = "The neocortex is a multi-scale network, with intricate local
              circuitry interwoven into a global mesh of long-range
              connections. Neural activity propagates within this network on a
              wide range of temporal and spatial scales. At the micro scale,
              neurophysiological recordings reveal coordinated dynamics in
              local neural populations, which support behaviorally relevant
              computations. At the macro scale, neuroimaging modalities measure
              global activity fluctuations organized into spatiotemporal
              patterns across the entire brain. Here we review recent advances
              linking the local and global scales of cortical dynamics and
              their relationship to behavior. We argue that diverse
              experimental observations on the dimensionality and variability
              of neural activity can be reconciled by considering how activity
              propagates in space and time on multiple spatial scales.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  58,
  pages    = "181--190",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Kao2019-wk,
  title    = "Neuroscience out of control: control-theoretic perspectives on
              neural circuit dynamics",
  author   = "Kao, Ta-Chu and Hennequin, Guillaume",
  abstract = "A major challenge in systems neuroscience is to understand how
              the dynamics of neural circuits give rise to behaviour. Analysis
              of complex dynamical systems is also at the heart of control
              engineering, where it is central to the design of robust control
              strategies. Although a rich engineering literature has grown over
              decades to facilitate the analysis of such systems, little of it
              has percolated into neuroscience so far. Here, we give a brief
              introduction to a number of core control-theoretic concepts that
              provide useful perspectives on neural circuit dynamics. We
              introduce important mathematical tools related to these concepts,
              and establish connections to neural circuit analysis, focusing on
              a number of themes that have arisen from the modern 'state-space'
              view on neural population dynamics.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  58,
  pages    = "122--129",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Wilting2019-lp,
  title    = "25 years of criticality in neuroscience - established results,
              open controversies, novel concepts",
  author   = "Wilting, J and Priesemann, V",
  abstract = "Twenty-five years ago, Dunkelmann and Radons (1994) showed that
              neural networks can self-organize to a critical state. In models,
              the critical state offers a number of computational advantages.
              Thus this hypothesis, and in particular the experimental work by
              Beggs and Plenz (2003), has triggered an avalanche of research,
              with thousands of studies referring to it. Nonetheless,
              experimental results are still contradictory. How is it possible,
              that a hypothesis has attracted active research for decades, but
              nonetheless remains controversial? We discuss the experimental
              and conceptual controversy, and then present a parsimonious
              solution that (i) unifies the contradictory experimental results,
              (ii) avoids disadvantages of a critical state, and (iii) enables
              rapid, adaptive tuning of network properties to task
              requirements.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  58,
  pages    = "105--111",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Sharpee2019-zx,
  title    = "An argument for hyperbolic geometry in neural circuits",
  author   = "Sharpee, Tatyana O",
  abstract = "This review connects several lines of research to argue that
              hyperbolic geometry should be broadly applicable to neural
              circuits as well as other biological circuits. The reason for
              this is that networks that conform to hyperbolic geometry are
              maximally responsive to external and internal perturbations.
              These networks also allow for efficient communication under
              conditions where nodes are added or removed. We will argue that
              one of the signatures of hyperbolic geometry is the celebrated
              Zipf's law (also sometimes known as the Pareto distribution) that
              states that the probability to observe a given pattern is
              inversely related to its rank. Zipf's law is observed in a
              variety of biological systems - from protein sequences, neural
              networks to economics. These observations provide further
              evidence for the ubiquity of networks with an underlying
              hyperbolic metric structure. Recent studies in neuroscience
              specifically point to the relevance of a three-dimensional
              hyperbolic space for neural signaling. The three-dimensional
              hyperbolic space may confer additional robustness compared to
              other dimensions. We illustrate how the use of hyperbolic
              coordinates revealed a novel topographic organization within the
              olfactory system. The use of such coordinates may facilitate
              representation of relevant signals elsewhere in the brain.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  58,
  pages    = "101--104",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Whiteway2019-fp,
  title    = "The quest for interpretable models of neural population activity",
  author   = "Whiteway, Matthew R and Butts, Daniel A",
  abstract = "Many aspects of brain function arise from the coordinated
              activity of large populations of neurons. Recent developments in
              neural recording technologies are providing unprecedented access
              to the activity of such populations during increasingly complex
              experimental contexts; however, extracting scientific insights
              from such recordings requires the concurrent development of
              analytical tools that relate this population activity to
              system-level function. This is a primary motivation for latent
              variable models, which seek to provide a low-dimensional
              description of population activity that can be related to
              experimentally controlled variables, as well as uncontrolled
              variables such as internal states (e.g. attention and arousal)
              and elements of behavior. While deriving an understanding of
              function from traditional latent variable methods relies on
              low-dimensional visualizations, new approaches are targeting more
              interpretable descriptions of the components underlying
              system-level function.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  58,
  pages    = "86--93",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Curto2019-ar,
  title    = "Relating network connectivity to dynamics: opportunities and
              challenges for theoretical neuroscience",
  author   = "Curto, Carina and Morrison, Katherine",
  abstract = "We review recent work relating network connectivity to the
              dynamics of neural activity. While concepts stemming from network
              science provide a valuable starting point, the interpretation of
              graph-theoretic structures and measures can be highly dependent
              on the dynamics associated to the network. Properties that are
              quite meaningful for linear dynamics, such as random walk and
              network flow models, may be of limited relevance in the
              neuroscience setting. Theoretical and computational neuroscience
              are playing a vital role in understanding the relationship
              between network connectivity and the nonlinear dynamics
              associated to neural networks.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  58,
  pages    = "11--20",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Comoli2012-li,
  title    = "Segregated anatomical input to sub-regions of the rodent superior
              colliculus associated with approach and defense",
  author   = "Comoli, Eliane and Das Neves Favaro, Pl{\'\i}nio and Vautrelle,
              Nicolas and Leriche, Mariana and Overton, Paul G and Redgrave,
              Peter",
  abstract = "The superior colliculus (SC) is responsible for sensorimotor
              transformations required to direct gaze toward or away from
              unexpected, biologically salient events. Significant changes in
              the external world are signaled to SC through primary
              multisensory afferents, spatially organized according to a
              retinotopic topography. For animals, where an unexpected event
              could indicate the presence of either predator or prey, early
              decisions to approach or avoid are particularly important.
              Rodents' ecology dictates predators are most often detected
              initially as movements in upper visual field (mapped in medial
              SC), while appetitive stimuli are normally found in lower visual
              field (mapped in lateral SC). Our purpose was to exploit this
              functional segregation to reveal neural sites that can bias or
              modulate initial approach or avoidance responses. Small
              injections of Fluoro-Gold were made into medial or lateral
              sub-regions of intermediate and deep layers of SC (SCm/SCl). A
              remarkable segregation of input to these two functionally defined
              areas was found. (i) There were structures that projected only to
              SCm (e.g., specific cortical areas, lateral geniculate and
              suprageniculate thalamic nuclei, ventromedial and premammillary
              hypothalamic nuclei, and several brainstem areas) or SCl (e.g.,
              primary somatosensory cortex representing upper body parts and
              vibrissae and parvicellular reticular nucleus in the brainstem).
              (ii) Other structures projected to both SCm and SCl but from
              topographically segregated populations of neurons (e.g., zona
              incerta and substantia nigra pars reticulata). (iii) There were a
              few brainstem areas in which retrogradely labeled neurons were
              spatially overlapping (e.g., pedunculopontine nucleus and locus
              coeruleus). These results indicate significantly more structures
              across the rat neuraxis are in a position to modulate defense
              responses evoked from SCm, and that neural mechanisms modulating
              SC-mediated defense or appetitive behavior are almost entirely
              segregated.",
  journal  = "Front. Neuroanat.",
  volume   =  6,
  pages    = "9",
  month    =  apr,
  year     =  2012,
  keywords = "approach; defense; segregated anatomical inputs; superior
              colliculus",
  language = "en"
}

@ARTICLE{Pandarinath2018-lc,
  title    = "Inferring single-trial neural population dynamics using
              sequential auto-encoders",
  author   = "Pandarinath, Chethan and O'Shea, Daniel J and Collins, Jasmine
              and Jozefowicz, Rafal and Stavisky, Sergey D and Kao, Jonathan C
              and Trautmann, Eric M and Kaufman, Matthew T and Ryu, Stephen I
              and Hochberg, Leigh R and Henderson, Jaimie M and Shenoy, Krishna
              V and Abbott, L F and Sussillo, David",
  abstract = "Neuroscience is experiencing a revolution in which simultaneous
              recording of thousands of neurons is revealing population
              dynamics that are not apparent from single-neuron responses. This
              structure is typically extracted from data averaged across many
              trials, but deeper understanding requires studying phenomena
              detected in single trials, which is challenging due to incomplete
              sampling of the neural population, trial-to-trial variability,
              and fluctuations in action potential timing. We introduce latent
              factor analysis via dynamical systems, a deep learning method to
              infer latent dynamics from single-trial neural spiking data. When
              applied to a variety of macaque and human motor cortical
              datasets, latent factor analysis via dynamical systems accurately
              predicts observed behavioral variables, extracts precise firing
              rate estimates of neural dynamics on single trials, infers
              perturbations to those dynamics that correlate with behavioral
              choices, and combines data from non-overlapping recording
              sessions spanning months to improve inference of underlying
              dynamics.",
  journal  = "Nat. Methods",
  volume   =  15,
  number   =  10,
  pages    = "805--815",
  month    =  oct,
  year     =  2018,
  language = "en"
}

@ARTICLE{Yu2009-pm,
  title    = "Gaussian-process factor analysis for low-dimensional single-trial
              analysis of neural population activity",
  author   = "Yu, Byron M and Cunningham, John P and Santhanam, Gopal and Ryu,
              Stephen I and Shenoy, Krishna V and Sahani, Maneesh",
  abstract = "We consider the problem of extracting smooth, low-dimensional
              neural trajectories that summarize the activity recorded
              simultaneously from many neurons on individual experimental
              trials. Beyond the benefit of visualizing the high-dimensional,
              noisy spiking activity in a compact form, such trajectories can
              offer insight into the dynamics of the neural circuitry
              underlying the recorded activity. Current methods for extracting
              neural trajectories involve a two-stage process: the spike trains
              are first smoothed over time, then a static
              dimensionality-reduction technique is applied. We first describe
              extensions of the two-stage methods that allow the degree of
              smoothing to be chosen in a principled way and that account for
              spiking variability, which may vary both across neurons and
              across time. We then present a novel method for extracting neural
              trajectories-Gaussian-process factor analysis (GPFA)-which
              unifies the smoothing and dimensionality-reduction operations in
              a common probabilistic framework. We applied these methods to the
              activity of 61 neurons recorded simultaneously in macaque
              premotor and motor cortices during reach planning and execution.
              By adopting a goodness-of-fit metric that measures how well the
              activity of each neuron can be predicted by all other recorded
              neurons, we found that the proposed extensions improved the
              predictive ability of the two-stage methods. The predictive
              ability was further improved by going to GPFA. From the extracted
              trajectories, we directly observed a convergence in neural state
              during motor planning, an effect that was shown indirectly by
              previous studies. We then show how such methods can be a powerful
              tool for relating the spiking activity across a neural population
              to the subject's behavior on a single-trial basis. Finally, to
              assess how well the proposed methods characterize neural
              population activity when the underlying time course is known, we
              performed simulations that revealed that GPFA performed tens of
              percent better than the best two-stage method.",
  journal  = "J. Neurophysiol.",
  volume   =  102,
  number   =  1,
  pages    = "614--635",
  month    =  jul,
  year     =  2009,
  language = "en"
}

@ARTICLE{Kim2019-fo,
  title    = "Generation of stable heading representations in diverse visual
              scenes",
  author   = "Kim, Sung Soo and Hermundstad, Ann M and Romani, Sandro and
              Abbott, L F and Jayaraman, Vivek",
  abstract = "Many animals rely on an internal heading representation when
              navigating in varied environments1--10. How this representation
              is linked to the sensory cues that define different surroundings
              is unclear. In the fly brain, heading is represented by `compass'
              neurons that innervate a ring-shaped structure known as the
              ellipsoid body3,11,12. Each compass neuron receives inputs from
              `ring' neurons that are selective for particular visual
              features13--16; this combination provides an ideal substrate for
              the extraction of directional information from a visual scene.
              Here we combine two-photon calcium imaging and optogenetics in
              tethered flying flies with circuit modelling, and show how the
              correlated activity of compass and visual neurons drives
              plasticity17--22, which flexibly transforms two-dimensional
              visual cues into a stable heading representation. We also
              describe how this plasticity enables the fly to convert a partial
              heading representation, established from orienting within part of
              a novel setting, into a complete heading representation. Our
              results provide mechanistic insight into the memory-related
              computations that are essential for flexible navigation in varied
              surroundings.",
  journal  = "Nature",
  month    =  nov,
  year     =  2019
}

@ARTICLE{Dabaghian2012-lc,
  title    = "A topological paradigm for hippocampal spatial map formation
              using persistent homology",
  author   = "Dabaghian, Y and M{\'e}moli, F and Frank, L and Carlsson, G",
  abstract = "An animal's ability to navigate through space rests on its
              ability to create a mental map of its environment. The
              hippocampus is the brain region centrally responsible for such
              maps, and it has been assumed to encode geometric information
              (distances, angles). Given, however, that hippocampal output
              consists of patterns of spiking across many neurons, and
              downstream regions must be able to translate those patterns into
              accurate information about an animal's spatial environment, we
              hypothesized that 1) the temporal pattern of neuronal firing,
              particularly co-firing, is key to decoding spatial information,
              and 2) since co-firing implies spatial overlap of place fields, a
              map encoded by co-firing will be based on connectivity and
              adjacency, i.e., it will be a topological map. Here we test this
              topological hypothesis with a simple model of hippocampal
              activity, varying three parameters (firing rate, place field
              size, and number of neurons) in computer simulations of rat
              trajectories in three topologically and geometrically distinct
              test environments. Using a computational algorithm based on
              recently developed tools from Persistent Homology theory in the
              field of algebraic topology, we find that the patterns of
              neuronal co-firing can, in fact, convey topological information
              about the environment in a biologically realistic length of time.
              Furthermore, our simulations reveal a ``learning region'' that
              highlights the interplay between the parameters in combining to
              produce hippocampal states that are more or less adept at map
              formation. For example, within the learning region a lower number
              of neurons firing can be compensated by adjustments in firing
              rate or place field size, but beyond a certain point map
              formation begins to fail. We propose that this learning region
              provides a coherent theoretical lens through which to view
              conditions that impair spatial learning by altering place cell
              firing rates or spatial specificity.",
  journal  = "PLoS Comput. Biol.",
  volume   =  8,
  number   =  8,
  pages    = "e1002581",
  month    =  aug,
  year     =  2012,
  language = "en"
}

@ARTICLE{McNaughton2004-qd,
  title     = "A two-dimensional neuropsychology of defense: fear/anxiety and
               defensive distance",
  author    = "McNaughton, Neil and Corr, Philip J",
  abstract  = "We present in this paper a picture of the neural systems
               controlling defense that updates and simplifies Gray's
               ``Neuropsychology of Anxiety''. It is based on two behavioural
               dimensions: 'defensive distance' as defined by the Blanchards
               and 'defensive direction'. Defensive direction is a categorical
               dimension with avoidance of threat corresponding to fear and
               approach to threat corresponding to anxiety. These two
               psychological dimensions are mapped to underlying neural
               dimensions. Defensive distance is mapped to neural level, with
               the shortest defensive distances involving the lowest neural
               level (periaqueductal grey) and the largest defensive distances
               the highest neural level (prefrontal cortex). Defensive
               direction is mapped to separate parallel streams that run across
               these levels. A significant departure from prior models is the
               proposal that both fear and anxiety are represented at all
               levels. The theory is presented in a simplified form that does
               not incorporate the interactions that must occur between
               non-adjacent levels of the system. It also requires expansion to
               include the dimension of escapability of threat. Our current
               development and these proposed future extensions do not change
               the core concepts originally proposed by Gray and, we argue,
               demonstrate their enduring value.",
  journal   = "Neurosci. Biobehav. Rev.",
  publisher = "Elsevier",
  volume    =  28,
  number    =  3,
  pages     = "285--305",
  month     =  may,
  year      =  2004,
  language  = "en"
}

@ARTICLE{Martin2011-fc,
  title    = "Molecular and neuroanatomical characterization of single neurons
              in the mouse medullary gigantocellular reticular nucleus",
  author   = "Martin, E M and Devidze, N and Shelley, D N and Westberg, L and
              Fontaine, C and Pfaff, D W",
  abstract = "Medullary gigantocellular reticular nucleus (mGi) neurons have
              been ascribed a variety of behaviors, many of which may fall
              under the concepts of either arousal or motivation. Despite this,
              many details of the connectivity of mGi neurons, particularly in
              reference to those neurons with ascending axons, remain unknown.
              To provide a neuroanatomical and molecular characterization of
              these cells, with reference to arousal and level-setting systems,
              large medullary reticular neurons were characterized with
              retrograde dye techniques and with real-time reverse
              transcriptase PCR (RT-PCR) analyses of single-neuron mRNA
              expression in the mouse. We have shown that receptors consistent
              with participation in generalized arousal are expressed by single
              mGi neurons and that receptors from different families of
              arousal-related neurotransmitters are rarely coexpressed. Through
              retrograde labeling, we have shown that neurons with ascending
              axons and neurons with descending axons tend to form
              like-with-like clusters, a finding that is consistent across age
              and gender. In comparing the two groups of retrogradely labeled
              neurons in neonatal animals, those neurons with axons that ascend
              to the midbrain show markers for GABAergic or coincident
              GABAergic and glutamatergic function; in contrast, approximately
              60\% of the neurons with axons that descend to the spinal cord
              are glutamatergic. We discuss the mGi's relationship to the
              voluntary and emotional motor systems and speculate that neurons
              in the mGi may represent a mammalian analogue to Mauthner cells,
              with a separation of function for neurons with ascending and
              descending axons.",
  journal  = "J. Comp. Neurol.",
  volume   =  519,
  number   =  13,
  pages    = "2574--2593",
  month    =  sep,
  year     =  2011,
  language = "en"
}

@ARTICLE{Liang2016-po,
  title    = "Terminations of reticulospinal fibers originating from the
              gigantocellular reticular formation in the mouse spinal cord",
  author   = "Liang, Huazheng and Watson, Charles and Paxinos, George",
  abstract = "The present study investigated the projections of the
              gigantocellular reticular nucleus (Gi) and its neighbors--the
              dorsal paragigantocellular reticular nucleus (DPGi), the
              alpha/ventral part of the gigantocellular reticular nucleus
              (GiA/V), and the lateral paragigantocellular reticular nucleus
              (LPGi)--to the mouse spinal cord by injecting the anterograde
              tracer biotinylated dextran amine (BDA) into the Gi, DPGi,
              GiA/GiV, and LPGi. The Gi projected to the entire spinal cord
              bilaterally with an ipsilateral predominance. Its fibers traveled
              in both the ventral and lateral funiculi with a greater presence
              in the ventral funiculus. As the fibers descended in the spinal
              cord, their density in the lateral funiculus increased. The
              terminals were present mainly in laminae 7-10 with a dorsolateral
              expansion caudally. In the lumbar and sacral cord, a considerable
              number of terminals were also present in laminae 5 and 6.
              Contralateral fibers shared a similar pattern to their
              ipsilateral counterparts and some fibers were seen to cross the
              midline. Fibers arising from the DPGi were similarly distributed
              in the spinal cord except that there was no dorsolateral
              expansion in the lumbar and sacral segments and there were fewer
              fiber terminals. Fibers arising from GiA/V predominantly traveled
              in the ventral and lateral funiculi ipsilaterally. Ipsilaterally,
              the density of fibers in the ventral funiculus decreased along
              the rostrocaudal axis, whereas the density of fibers in the
              lateral funiculus increased. They terminate mainly in the medial
              ventral horn and lamina 10 with a smaller number of fibers in the
              dorsal horn. Fibers arising from the LPGi traveled in both the
              ventral and lateral funiculi and the density of these fibers in
              the ventral and lateral funiculi decreased dramatically in the
              lumbar and sacral segments. Their terminals were present in the
              ventral horn with a large portion of them terminating in the
              motor neuron columns. The present study is the first
              demonstration of the termination pattern of fibers arising from
              the Gi, DPGi, GiA/GiV, and LPGi in the mouse spinal cord. It
              provides an anatomical foundation for those who are conducting
              spinal cord injury and locomotion related research.",
  journal  = "Brain Struct. Funct.",
  volume   =  221,
  number   =  3,
  pages    = "1623--1633",
  month    =  apr,
  year     =  2016,
  keywords = "Blood pressure control; Gigantocellular reticular nucleus;
              Locomotion; Medullary reticulospinal tract; Paragigantocellular
              nucleus; Spinal cord",
  language = "en"
}

@ARTICLE{Mobbs2018-li,
  title    = "Foraging for foundations in decision neuroscience: insights from
              ethology",
  author   = "Mobbs, Dean and Trimmer, Pete C and Blumstein, Daniel T and
              Dayan, Peter",
  abstract = "Modern decision neuroscience offers a powerful and broad account
              of human behaviour using computational techniques that link
              psychological and neuroscientific approaches to the ways that
              individuals can generate near-optimal choices in complex
              controlled environments. However, until recently, relatively
              little attention has been paid to the extent to which the
              structure of experimental environments relates to natural
              scenarios, and the survival problems that individuals have
              evolved to solve. This situation not only risks leaving
              decision-theoretic accounts ungrounded but also makes various
              aspects of the solutions, such as hard-wired or Pavlovian
              policies, difficult to interpret in the natural world. Here, we
              suggest importing concepts, paradigms and approaches from the
              fields of ethology and behavioural ecology, which concentrate on
              the contextual and functional correlates of decisions made about
              foraging and escape and address these lacunae.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  19,
  number   =  7,
  pages    = "419--427",
  month    =  jul,
  year     =  2018,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Cooper1998-ii,
  title     = "Superior colliculus and active navigation: Role of visual and
               non-visual cues in controlling cellular representations of space",
  author    = "Cooper, B G and Miya, D Y and Mizumori, S J Y",
  abstract  = "To begin investigation of the contribution of the superior
               colliculus to unrestrained navigation, the nature of behavioral
               representation by individual neurons was identified as rats
               performed a spatial memory task. Similar to what has been
               observed for hippocampus, many superior collicular cells showed
               elevated firing as animals traversed particular locations on the
               maze, and also during directional movement. However, when
               compared to hippocampal place fields, superior collicular
               location fields were found to be more broad …",
  journal   = "Hippocampus",
  publisher = "Wiley Online Library",
  volume    =  8,
  number    =  4,
  pages     = "340--372",
  year      =  1998
}

@ARTICLE{Kraskov2004-de,
  title    = "Estimating mutual information",
  author   = "Kraskov, Alexander and St{\"o}gbauer, Harald and Grassberger,
              Peter",
  abstract = "We present two classes of improved estimators for mutual
              information M(X,Y), from samples of random points distributed
              according to some joint probability density mu(x,y). In contrast
              to conventional estimators based on binnings, they are based on
              entropy estimates from k -nearest neighbor distances. This means
              that they are data efficient (with k=1 we resolve structures down
              to the smallest possible scales), adaptive (the resolution is
              higher where data are more numerous), and have minimal bias.
              Indeed, the bias of the underlying entropy estimates is mainly
              due to nonuniformity of the density at the smallest resolved
              scale, giving typically systematic errors which scale as
              functions of k/N for N points. Numerically, we find that both
              families become exact for independent distributions, i.e. the
              estimator M(X,Y) vanishes (up to statistical fluctuations) if
              mu(x,y)=mu(x)mu(y). This holds for all tested marginal
              distributions and for all dimensions of x and y. In addition, we
              give estimators for redundancies between more than two random
              variables. We compare our algorithms in detail with existing
              algorithms. Finally, we demonstrate the usefulness of our
              estimators for assessing the actual independence of components
              obtained from independent component analysis (ICA), for improving
              ICA, and for estimating the reliability of blind source
              separation.",
  journal  = "Phys. Rev. E Stat. Nonlin. Soft Matter Phys.",
  volume   =  69,
  number   = "6 Pt 2",
  pages    = "066138",
  month    =  jun,
  year     =  2004,
  language = "en"
}

@ARTICLE{Sooksawate2013-hx,
  title    = "Viral vector-mediated selective and reversible blockade of the
              pathway for visual orienting in mice",
  author   = "Sooksawate, Thongchai and Isa, Kaoru and Matsui, Ryosuke and
              Kato, Shigeki and Kinoshita, Masaharu and Kobayashi, Kenta and
              Watanabe, Dai and Kobayashi, Kazuto and Isa, Tadashi",
  abstract = "Recently, by using a combination of two viral vectors, we
              developed a technique for pathway-selective and reversible
              synaptic transmission blockade, and successfully induced a
              behavioral deficit of dexterous hand movements in macaque monkeys
              by affecting a population of spinal interneurons. To explore the
              capacity of this technique to work in other pathways and species,
              and to obtain fundamental methodological information, we tried to
              block the crossed tecto-reticular pathway, which is known to
              control orienting responses to visual targets, in mice. A
              neuron-specific retrograde gene transfer vector with the gene
              encoding enhanced tetanus neurotoxin (eTeNT) tagged with enhanced
              green fluorescent protein (EGFP) under the control of a
              tetracycline responsive element was injected into the left medial
              pontine reticular formation. 7-17 days later, an adeno-associated
              viral vector with a highly efficient Tet-ON sequence, rtTAV16,
              was injected into the right superior colliculus. 5-9 weeks later,
              the daily administration of doxycycline (Dox) was initiated.
              Visual orienting responses toward the left side were impaired 1-4
              days after Dox administration. Anti-GFP immunohistochemistry
              revealed that a number of neurons in the intermediate and deep
              layers of the right superior colliculus were positively stained,
              indicating eTeNT expression. After the termination of Dox
              administration, the anti-GFP staining returned to the baseline
              level within 28 days. A second round of Dox administration,
              starting from 28 days after the termination of the first Dox
              administration, resulted in the reappearance of the behavioral
              impairment. These findings showed that pathway-selective and
              reversible blockade of synaptic transmission also causes
              behavioral effects in rodents, and that the crossed
              tecto-reticular pathway clearly controls visual orienting
              behaviors.",
  journal  = "Front. Neural Circuits",
  volume   =  7,
  pages    = "162",
  month    =  oct,
  year     =  2013,
  keywords = "Tet-ON; mouse; orienting behavior; pontine reticular formation;
              superior colliculus; tetanus neurotoxin; viral vector",
  language = "en"
}

@ARTICLE{Felsen2008-nl,
  title    = "Neural substrates of sensory-guided locomotor decisions in the
              rat superior colliculus",
  author   = "Felsen, Gidon and Mainen, Zachary F",
  abstract = "Deciding in which direction to move is a ubiquitous feature of
              animal behavior, but the neural substrates of locomotor choices
              are not well understood. The superior colliculus (SC) is a
              midbrain structure known to be important for controlling the
              direction of gaze, particularly when guided by visual or auditory
              cues, but which may play a more general role in behavior
              involving spatial orienting. To test this idea, we recorded and
              manipulated activity in the SC of freely moving rats performing
              an odor-guided spatial choice task. In this context, not only did
              a substantial majority of SC neurons encode choice direction
              during goal-directed locomotion, but many also predicted the
              upcoming choice and maintained selectivity for it after movement
              completion. Unilateral inactivation of SC activity profoundly
              altered spatial choices. These results indicate that the SC
              processes information necessary for spatial locomotion,
              suggesting a broad role for this structure in sensory-guided
              orienting and navigation.",
  journal  = "Neuron",
  volume   =  60,
  number   =  1,
  pages    = "137--148",
  month    =  oct,
  year     =  2008,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Dean1986-of,
  title    = "Head and body movements produced by electrical stimulation of
              superior colliculus in rats: effects of interruption of crossed
              tectoreticulospinal pathway",
  author   = "Dean, P and Redgrave, P and Sahibzada, N and Tsuji, K",
  abstract = "Stimulation of the superior colliculus in rats produces movements
              of the head and body that resemble either orientation and
              approach towards a contralateral stimulus, or avoidance of, or
              escape from, such a stimulus. A variety of evidence indicates
              that the crossed descending pathway, which runs in the
              contralateral predorsal bundle to the pontomedullary reticular
              formation and the spinal cord, is involved in orienting
              movements. The nature of this involvement was investigated, by
              assessing the effects on tectally-elicited movements of midbrain
              knife-cuts intended to section the pathway as it crosses midline
              in the dorsal tegmental decussation. As expected, ipsilateral
              movements resembling avoidance or escape were little affected by
              dorsal tegmental decussation section, whereas contralateral
              circling movements of the body were almost abolished. However,
              contralateral movements of the head in response to electrical
              stimulation were not eliminated, nor were orienting head
              movements to visual or tactile stimuli. There was some suggestion
              that section of the dorsal tegmental decussation increased the
              latency of head movements from electrical stimulation at lateral
              sites, and decreased the accuracy of orienting movements to
              sensory stimuli. These results support the view that the crossed
              tectoreticulospinal system is concerned with approach rather than
              avoidance movements. However, it appears that other, as yet
              unidentified, tectal efferent systems are also involved in
              orienting head movements. It is possible that this division of
              labour may reflect functional differences between various kinds
              of apparently similar orienting responses. One suggestion is that
              the tectoreticulospinal system is concerned less in open-loop
              orienting responses (that are initiated but not subsequently
              guided by sensory stimuli), than in following or pursuit
              movements.",
  journal  = "Neuroscience",
  volume   =  19,
  number   =  2,
  pages    = "367--380",
  month    =  oct,
  year     =  1986,
  language = "en"
}

@ARTICLE{Masullo2019-mk,
  title     = "Genetically Defined Functional Modules for Spatial Orienting in
               the Mouse Superior Colliculus",
  author    = "Masullo, Laura and Mariotti, Letizia and Alexandre, Nicolas and
               Freire-Pritchett, Paula and Boulanger, Jerome and Tripodi, Marco",
  abstract  = "Summary In order to explore and interact with their
               surroundings, animals need to orient toward specific positions
               in space. Throughout the animal kingdom, head movements
               represent a primary form of orienting behavior. The superior
               colliculus (SC) is a fundamental structure for the generation of
               orienting responses, but how genetically distinct groups of
               collicular neurons contribute to these spatially tuned behaviors
               remains largely to be defined. Here, through the genetic
               dissection of the murine SC, we identify a functionally and
               genetically homogeneous subclass of glutamatergic neurons
               defined by the expression of the paired-like homeodomain
               transcription factor Pitx2. We show that the optogenetic
               stimulation of Pitx2ON neurons drives three-dimensional head
               displacements characterized by stepwise, saccade-like
               kinematics. Furthermore, during naturalistic foraging behavior,
               the activity of Pitx2ON neurons precedes and predicts the onset
               of spatially tuned head movements. Intriguingly, we reveal that
               Pitx2ON neurons are clustered in an orderly array of anatomical
               modules that tile the entire intermediate layer of the SC. Such
               a modular organization gives origin to a discrete and
               discontinuous representation of the motor space, with each
               Pitx2ON module subtending a defined portion of the animal's
               egocentric space. The modularity of Pitx2ON neurons provides an
               anatomical substrate for the convergence of spatially coherent
               sensory and motor signals of cortical and subcortical origins,
               thereby promoting the recruitment of appropriate movement
               vectors. Overall, these data support the view of the superior
               colliculus as a selectively addressable and modularly organized
               spatial-motor register.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  29,
  number    =  17,
  pages     = "2892--2904.e8",
  month     =  sep,
  year      =  2019,
  keywords  = "superior colliculus; Pitx2; motor control; head movement;
               orienting behaviour"
}

@ARTICLE{Wilson2018-yh,
  title     = "{Three-Dimensional} Representation of Motor Space in the Mouse
               Superior Colliculus",
  author    = "Wilson, Jonathan J and Alexandre, Nicolas and Trentin, Caterina
               and Tripodi, Marco",
  abstract  = "From the act of exploring an environment to that of grasping a
               cup of tea, animals must put in register their motor acts with
               their surrounding space. In the motor domain, this is likely to
               be defined by a register of three-dimensional (3D) displacement
               vectors, whose recruitment allows motion in the direction of a
               target. One such spatially targeted action is seen in the head
               reorientation behavior of mice, yet the neural mechanisms
               underlying these 3D behaviors remain unknown. Here, by
               developing a head-mounted inertial sensor for studying 3D head
               rotations and combining it with electrophysiological recordings,
               we show that neurons in the mouse superior colliculus are either
               individually or conjunctively tuned to the three Eulerian
               components of head rotation. The average displacement vectors
               associated with motor-tuned colliculus neurons remain stable
               over time and are unaffected by changes in firing rate or the
               duration of spike trains. Finally, we show that the motor tuning
               of collicular neurons is largely independent from visual or
               landmark cues. By describing the 3D nature of motor tuning in
               the superior colliculus, we contribute to long-standing debate
               on the dimensionality of collicular motor decoding; furthermore,
               by providing an experimental paradigm for the study of the
               metric of motor tuning in mice, this study also paves the way to
               the genetic dissection of the circuits underlying spatially
               targeted motion.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  28,
  number    =  11,
  pages     = "1744--1755.e12",
  month     =  jun,
  year      =  2018,
  keywords  = "3D; motor control; space encoding; superior colliculus",
  language  = "en"
}

@ARTICLE{Tenenbaum2000-kv,
  title    = "A global geometric framework for nonlinear dimensionality
              reduction",
  author   = "Tenenbaum, J B and de Silva, V and Langford, J C",
  abstract = "Scientists working with large volumes of high-dimensional data,
              such as global climate patterns, stellar spectra, or human gene
              distributions, regularly confront the problem of dimensionality
              reduction: finding meaningful low-dimensional structures hidden
              in their high-dimensional observations. The human brain confronts
              the same problem in everyday perception, extracting from its
              high-dimensional sensory inputs-30,000 auditory nerve fibers or
              10(6) optic nerve fibers-a manageably small number of
              perceptually relevant features. Here we describe an approach to
              solving dimensionality reduction problems that uses easily
              measured local metric information to learn the underlying global
              geometry of a data set. Unlike classical techniques such as
              principal component analysis (PCA) and multidimensional scaling
              (MDS), our approach is capable of discovering the nonlinear
              degrees of freedom that underlie complex natural observations,
              such as human handwriting or images of a face under different
              viewing conditions. In contrast to previous algorithms for
              nonlinear dimensionality reduction, ours efficiently computes a
              globally optimal solution, and, for an important class of data
              manifolds, is guaranteed to converge asymptotically to the true
              structure.",
  journal  = "Science",
  volume   =  290,
  number   =  5500,
  pages    = "2319--2323",
  month    =  dec,
  year     =  2000,
  language = "en"
}

@ARTICLE{Hebert2019-gx,
  title    = "Inexperienced preys know when to flee or to freeze in front of a
              threat",
  author   = "H{\'e}bert, Marie and Versace, Elisabetta and Vallortigara,
              Giorgio",
  abstract = "Using appropriate antipredatory responses is crucial for
              survival. While slowing down reduces the chances of being
              detected from distant predators, fleeing away is advantageous in
              front of an approaching predator. Whether appropriate responses
              depend on experience with moving objects is still an open
              question. To clarify whether adopting appropriate fleeing or
              freezing responses requires previous experience, we investigated
              responses of chicks naive to movement. When exposed to the moving
              cues mimicking an approaching predator (a rapidly expanding,
              looming stimulus), chicks displayed a fast escape response. In
              contrast, when presented with a distal threat (a small stimulus
              sweeping overhead) they decreased their speed, a maneuver useful
              to avoid detection. The fast expansion of the stimulus toward the
              subject, rather than its size per se or change in luminance,
              triggered the escape response. These results show that young
              animals, in the absence of previous experience, can use motion
              cues to select the appropriate responses to different threats.
              The adaptive needs of young preys are thus matched by spontaneous
              defensive mechanisms that do not require learning.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  month    =  oct,
  year     =  2019,
  keywords = "antipredatory behaviors; defense strategies; motion cues; naive
              animals; threat detection",
  language = "en"
}

@ARTICLE{Shin2019-hi,
  title     = "Dynamics of Awake {Hippocampal-Prefrontal} Replay for Spatial
               Learning and {Memory-Guided} Decision Making",
  author    = "Shin, Justin D and Tang, Wenbo and Jadhav, Shantanu P",
  abstract  = "SummarySpatial learning requires remembering and choosing paths
               to goals. Hippocampal place cells replay spatial paths during
               immobility in reverse and forward order, offering a potential
               mechanism. However, how replay supports both goal-directed
               learning and memory-guided decision making is unclear. We
               therefore continuously tracked awake replay in the same
               hippocampal-prefrontal ensembles throughout learning of a
               spatial alternation task. We found that, during pauses between
               behavioral trajectories, reverse and forward hippocampal replay
               supports an internal cognitive search of available past and
               future possibilities and exhibits opposing learning gradients
               for prediction of past and future behavioral paths,
               respectively. Coordinated hippocampal-prefrontal replay
               distinguished correct past and future paths from alternative
               choices, suggesting a role in recall of past paths to guide
               planning of future decisions for spatial working memory. Our
               findings reveal a learning shift from hippocampal
               reverse-replay-based retrospective evaluation to
               forward-replay-based prospective planning, with prefrontal
               readout of memory-guided paths for learning and decision making.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  0,
  number    =  0,
  month     =  oct,
  year      =  2019,
  keywords  = "hippocampus; prefrontal cortex; replay; sharp-wave ripple;
               spatial learning; decision making; working memory; prospection;
               retrospection; planning",
  language  = "en"
}

@ARTICLE{Harris2019-ht,
  title    = "Hierarchical organization of cortical and thalamic connectivity",
  author   = "Harris, Julie A and Mihalas, Stefan and Hirokawa, Karla E and
              Whitesell, Jennifer D and Choi, Hannah and Bernard, Amy and Bohn,
              Phillip and Caldejon, Shiella and Casal, Linzy and Cho, Andrew
              and Feiner, Aaron and Feng, David and Gaudreault, Nathalie and
              Gerfen, Charles R and Graddis, Nile and Groblewski, Peter A and
              Henry, Alex M and Ho, Anh and Howard, Robert and Knox, Joseph E
              and Kuan, Leonard and Kuang, Xiuli and Lecoq, Jerome and Lesnar,
              Phil and Li, Yaoyao and Luviano, Jennifer and McConoughey,
              Stephen and Mortrud, Marty T and Naeemi, Maitham and Ng, Lydia
              and Oh, Seung Wook and Ouellette, Benjamin and Shen, Elise and
              Sorensen, Staci A and Wakeman, Wayne and Wang, Quanxin and Wang,
              Yun and Williford, Ali and Phillips, John W and Jones, Allan R
              and Koch, Christof and Zeng, Hongkui",
  abstract = "The mammalian cortex is a laminar structure containing many areas
              and cell types that are densely interconnected in complex ways,
              and for which generalizable principles of organization remain
              mostly unknown. Here we describe a major expansion of the Allen
              Mouse Brain Connectivity Atlas resource1, involving around a
              thousand new tracer experiments in the cortex and its main
              satellite structure, the thalamus. We used Cre driver lines (mice
              expressing Cre recombinase) to comprehensively and selectively
              label brain-wide connections by layer and class of projection
              neuron. Through observations of axon termination patterns, we
              have derived a set of generalized anatomical rules to describe
              corticocortical, thalamocortical and corticothalamic projections.
              We have built a model to assign connection patterns between areas
              as either feedforward or feedback, and generated testable
              predictions of hierarchical positions for individual cortical and
              thalamic areas and for cortical network modules. Our results show
              that cell-class-specific connections are organized in a shallow
              hierarchy within the mouse corticothalamic network.",
  journal  = "Nature",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Buel1935-sn,
  title     = "Differential errors in animal mazes",
  author    = "Buel, J",
  abstract  = "93 different possible factors that may determine the
               differential errors made in maze-running are drawn from a
               literature of 111 titles, and grouped under the headings:
               genetic make-up, physiological determiners, physical
               determiners, route and blind preferences, goal functions,
               emotional factors, extra-maze, pre-maze, and temporal factors,
               maze structure and pattern, general orientation, expectancy,
               organizing factors. A discussion by the author follows.
               (PsycINFO Database Record (c) 2016 APA, all rights reserved)",
  journal   = "Psychol. Bull.",
  publisher = "psycnet.apa.org",
  volume    =  32,
  number    =  1,
  pages     = "67--99",
  month     =  jan,
  year      =  1935
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Tolman1938-aa,
  title     = "The determiners of behavior at a choice point",
  author    = "Tolman, Edward Chace",
  abstract  = "An analysis of the complex of causal determinants on which a
               rat's behavior of turning right or left depends shows them to be
               divided into`` environmental variables,'' such as maintenance
               schedule, appropriate goal-object, types of stimuli provided and
               responses …",
  journal   = "Psychol. Rev.",
  publisher = "American Psychological Association",
  volume    =  45,
  number    =  1,
  pages     = "1",
  year      =  1938
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{W_R_Boyce_Gibson1900-dh,
  title     = "The Principle of Least Action as a Psychological Principle",
  author    = "{W. R. Boyce Gibson}",
  abstract  = "Action, Leipzig, 1877. 2lMYcanique Analytique, p. 246.'In this
               respect the Principle of Least Action is found wanting;* f.
               Bartholomew Price, Infinitesimal Calculus, vol. iv., p. 150.
               4Lagrange,(UEluvres, ed. Serret, vol. i., p. 365), in a sequel
               to a paper of his Essai d'unte nouvelle methode pour determiner
               le. s maxima et les minima des formules intJgrales indefinies. 5
               H. v. Helmholtz,`` Iber die physikalische Bedentung des Princips
               der Kleinsten Wirkung,'' Journal ffir die reine und angewandte
               Mathemiatik (usually known as Crelle's …",
  journal   = "Mind",
  publisher = "[Oxford University Press, Mind Association]",
  volume    =  9,
  number    =  36,
  pages     = "469--495",
  year      =  1900
}

@ARTICLE{Gengerelli1930-zo,
  title     = "The principle of maxima and minima in animal learning",
  author    = "Gengerelli, J A",
  abstract  = "A series of experiments were performed with blinded and normal
               white rats to determine the nature of the path which the animals
               would eventually select from an indefinite number of possible
               paths leading to food. The animals entered by one corner of the
               platform 6 ft. by 6 ft. which was enclosed on all sides by a 5
               in. wall and covered with wire mesh. Food was placed at the
               diagonally opposite corner to the entrance corner, in a small
               food box which was outside of the platform and which the animal
               entered by means of a short alley leading to it. Both food and
               observer were invisible to the animal. It was found in
               practically all cases that the path finally chosen by the
               animals (both normal and blinded), when all possibility of
               olfactory orientation was eliminated, was the path of ``least
               effort,'' namely, the path whose distance was a minimum. In the
               experiments where there were no obstructions on the platform,
               the actual path finally chosen was the diagonal from the
               entrance corner to the food corner. The behavior of the rats can
               be most accurately described by stating that the path which the
               animals finally chose served as a limit to which they
               approximated more and more closely with each successive trail.
               (PsycINFO Database Record (c) 2016 APA, all rights reserved)",
  journal   = "J. Comp. Psychol.",
  publisher = "psycnet.apa.org",
  volume    =  11,
  number    =  2,
  pages     = "193--236",
  month     =  dec,
  year      =  1930
}

@ARTICLE{De_Camp1920-jm,
  title     = "Relative distance as a factor in the white rat's selection of a
               path",
  author    = "De Camp, Joseph Edgar",
  abstract  = "Elimination of errors and decrease in length of path from
               starting point to goal (usually food) are characteristic of
               animal learning. Of two paths leading to food, one being longer,
               the animal soon chooses the shorter. This has been observed with
               white rats in their learning of mazes. This article is a report
               of an attempt to study this selection by the white rat of the
               shorter of two paths.(PsycINFO Database Record (c) 2017 APA, all
               rights reserved)",
  journal   = "Psychobiology",
  publisher = "Williams \& Wilkins Company",
  volume    =  2,
  number    =  3,
  pages     = "245",
  year      =  1920
}

@ARTICLE{Richards2019-sy,
  title    = "A deep learning framework for neuroscience",
  author   = "Richards, Blake A and Lillicrap, Timothy P and Beaudoin, Philippe
              and Bengio, Yoshua and Bogacz, Rafal and Christensen, Amelia and
              Clopath, Claudia and Costa, Rui Ponte and de Berker, Archy and
              Ganguli, Surya and Gillon, Colleen J and Hafner, Danijar and
              Kepecs, Adam and Kriegeskorte, Nikolaus and Latham, Peter and
              Lindsay, Grace W and Miller, Kenneth D and Naud, Richard and
              Pack, Christopher C and Poirazi, Panayiota and Roelfsema, Pieter
              and Sacramento, Jo{\~a}o and Saxe, Andrew and Scellier, Benjamin
              and Schapiro, Anna C and Senn, Walter and Wayne, Greg and Yamins,
              Daniel and Zenke, Friedemann and Zylberberg, Joel and Therien,
              Denis and Kording, Konrad P",
  abstract = "Systems neuroscience seeks explanations for how the brain
              implements a wide variety of perceptual, cognitive and motor
              tasks. Conversely, artificial intelligence attempts to design
              computational systems based on the tasks they will have to solve.
              In artificial neural networks, the three components specified by
              design are the objective functions, the learning rules and the
              architectures. With the growing success of deep learning, which
              utilizes brain-inspired architectures, these three designed
              components have increasingly become central to how we model,
              engineer and optimize complex artificial learning systems. Here
              we argue that a greater focus on these components would also
              benefit systems neuroscience. We give examples of how this
              optimization-based framework can drive theoretical and
              experimental progress in neuroscience. We contend that this
              principled perspective on systems neuroscience will help to
              generate more rapid progress.",
  journal  = "Nat. Neurosci.",
  volume   =  22,
  number   =  11,
  pages    = "1761--1770",
  month    =  nov,
  year     =  2019,
  keywords = "RNN To read;RNN"
}

@ARTICLE{Kendler1943-np,
  title     = "The influence of a sub-goal on maze behavior",
  author    = "Kendler, H H",
  abstract  = "The writer reports an experiment designed to determine the
               effect upon learning of a simple distance discrimination of
               varying the ratio of the total distance to the final turn while
               keeping the absolute distance from starting point to goal
               constant. One group of rats was trained on a maze pattern with a
               ratio of 2.33 to the final turn, the other group being trained
               with a ratio of 1.36. The first group (ratio 2.33) took
               significantly less trials and made significantly less errors in
               reaching the criterion of learning. The author feels that the
               results may be interpreted as being in some way attributable to
               the secondary reinforcing characteristics of the final turn or
               ``sub-goal.'' (PsycINFO Database Record (c) 2016 APA, all rights
               reserved)",
  journal   = "J. Comp. Psychol.",
  publisher = "psycnet.apa.org",
  volume    =  36,
  number    =  2,
  pages     = "67--73",
  month     =  oct,
  year      =  1943
}

@ARTICLE{Hull1951-zh,
  title     = "Essentials of behavior",
  author    = "Hull, Clark L",
  abstract  = "``This volume is designed to present briefly and in an
               intelligible manner the basic laws [postulates and corollaries]
               of mammalian behavior, and to serve as a useful introduction to
               the current aspects of behavior theory.'' The history of the
               present set of postulates is given in the notes. Glossary of
               symbols. 79-item bibliography. (PsycINFO Database Record (c)
               2016 APA, all rights reserved)",
  publisher = "Yale University Press Essentials of behavior.",
  volume    =  145,
  year      =  1951,
  address   = "New Haven, CT, US",
  keywords  = "books;Books"
}


@ARTICLE{Waters1937-tc,
  title     = "The Principle of Least Effort in Learning",
  author    = "Waters, R H",
  journal   = "J. Gen. Psychol.",
  publisher = "Routledge",
  volume    =  16,
  number    =  1,
  pages     = "3--20",
  month     =  jan,
  year      =  1937
}

@ARTICLE{Hull1932-hs,
  title     = "The goal-gradient hypothesis and maze learning",
  author    = "Hull, C L",
  abstract  = "The hypothesis, which is an extension of Hull's goal reaction
               hypothesis, is that the goal reaction gets conditioned most
               strongly to the stimuli preceding it, and the other reactions in
               the sequence get conditioned to their stimuli, with a strength
               inversely proportional to their temporal or spatial remoteness
               from the goal reaction. Since this assumes a gradient, which is
               related to the goal, he calls it a goal-gradient. The shape of
               this gradient is shown, by reference to Yoshioka's experiment in
               selection of maze pathways by the rat, to be positively
               accelerated, and to conform to the logarithmic law. The author
               deduces ten actual behavior phenomena from his principle, such
               as choice of shorter path, order of elimination of blind alleys,
               relative rates of locomotion in different parts of the maze,
               etc. (PsycINFO Database Record (c) 2016 APA, all rights
               reserved)",
  journal   = "Psychol. Rev.",
  publisher = "psycnet.apa.org",
  volume    =  39,
  number    =  1,
  pages     = "25--43",
  month     =  jan,
  year      =  1932
}

@ARTICLE{Sams1925-ng,
  title     = "Time discrimination in white rats",
  author    = "Sams, C F and Tolman, E C",
  abstract  = "With two alternative paths in a maze equal in every respect
               except that the animal was detained in a detention chamber 1
               minute before being allowed to enter one alley and 6 minutes
               before allowed to enter the other alley, with the food now
               reachable by path one and now by path two, the investigators
               discovered that almost invariably the animal will learn to seek
               food through that path, the entrance to which has been delayed
               for the shorter period of time. A threshold of difference of
               delay was worked out for one animal; it was a ratio between 1:4
               and 1:5 minutes. (PsycINFO Database Record (c) 2016 APA, all
               rights reserved)",
  journal   = "J. Comp. Psychol.",
  publisher = "psycnet.apa.org",
  volume    =  5,
  number    =  3,
  pages     = "255--263",
  month     =  jun,
  year      =  1925
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Clements1928-ph,
  title     = "The effect of time on distance discrimination in the albino rat",
  author    = "Clements, Forrest E",
  abstract  = "An asymmetrical T-shaped apparatus with paths giving a distance
               ratio of 1:10 was constructed in such a manner that the rat
               could be detained for varying lengths of time immediately after
               making a choice. One group of rats were allowed to make their
               choice of either alley and continue without delay while the
               other three groups were delayed for 30 seconds, 60 seconds, and
               120 seconds, respectively. The experiment aimed to determine if
               the time spent in running the pathway was as effective as time
               spent in waiting. Without a delay learning begins immediately
               and proceeds rapidly. But when a time interval exists between
               the moment of choice and the continuation of the path to food
               learning does not commence immediately. ``For several days each
               animal apparently learns nothing, his choice of path seeming due
               to chance. Suddenly, however, he begins to learn and from that
               point on his learning proceeds at approximately the same rate as
               that of those animals where there was no detention. The longer
               the detention the longer the initial period of no apparent
               progress. If the detention is long enough… the animals are
               probably unable ever to make the discrimination.'' The group
               which had been delayed 120 seconds ran for 25 days with no signs
               of learning to discriminate the shorter path. On the 26th day
               the detention was removed for three of these rats, whereupon
               they learned it in much shorter time than the animals with no
               detention and no previous acquaintance with the apparatus. ``The
               longer the detention the longer it takes the rat to 'get the
               idea' until, with a long enough detention, the animal's memory
               is perhaps not long enough to span the gap between turning a
               particular way and the 'realization' of the preferential
               character (shortness) of that way.'' (PsycINFO Database Record
               (c) 2017 APA, all rights reserved)",
  journal   = "J. Comp. Psychol.",
  publisher = "psycnet.apa.org",
  volume    =  8,
  number    =  4,
  pages     = "317--324",
  month     =  oct,
  year      =  1928
}

@MISC{Tolman1967-ym,
  title  = "Purposive Behavior in Animal",
  author = "{Tolman}",
  year   =  1967
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Snygg1936-xx,
  title     = "Maze Learning as Perception",
  author    = "Snygg, Donald",
  abstract  = "Because of the growing tendency to think of problems of
               perception and learning as identical, it seems desirable to
               examine empirically the utility of such a viewpoint. The
               systematic advantages of such a simplification of laws and
               entities are tempting; but the ultimate test of the assumption
               of likeness between learning and perception must be its
               usefulness. During a recent investigation (6) of the relative
               difficulty of various patterns of ten- section Warden multiple-U
               mazes it was found that the relative ilumber of entries into the
               …",
  journal   = "The Pedagogical Seminary and Journal of Genetic Psychology",
  publisher = "Routledge",
  volume    =  49,
  number    =  1,
  pages     = "231--239",
  month     =  sep,
  year      =  1936
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Yoshioka1929-bn,
  title     = "Weber's law in the discrimination of maze distance by the white
               rat",
  author    = "Yoshioka, Joseph Geno",
  abstract  = "Using the method of wrong and right cases and two specially
               constructed mazes which allowed the lengths of the alleys to be
               altered, the author attempted to determine whether Weber's Law
               holds for the discrimination of maze distance by the white
               rat.`` Maze I was so constructed that two paths visually similar
               were offered for choice. One path was 211 inches long and kept
               constant, while the other could be shortened by steps of 13
               inches. Maze II was similarly constructed, but magnified by two.
               Five short paths were used in each maze …",
  journal   = "Publ. Psychol.",
  publisher = "psycnet.apa.org",
  year      =  1929
}

@ARTICLE{Yoshioka1928-ob,
  title     = "Pattern Versus Frequency and Recency Factors in Maze Learning: A
               Preliminary Study",
  author    = "Yoshioka, Joseph G",
  abstract  = "*Received for publication by Calvin P. Stone .of the Editorial
               Board, April 2, 1928.",
  journal   = "The Pedagogical Seminary and Journal of Genetic Psychology",
  publisher = "Routledge",
  volume    =  35,
  number    =  2,
  pages     = "193--200",
  month     =  jun,
  year      =  1928
}

@ARTICLE{Snygg1935-tx,
  title     = "Mazes in Which Rats Take the Longer Path to Food",
  author    = "Snygg, Donald",
  journal   = "J. Psychol.",
  publisher = "Routledge",
  volume    =  1,
  number    =  1,
  pages     = "153--166",
  month     =  jan,
  year      =  1935
}

@ARTICLE{Krim2016-el,
  title    = "Discovering the Whole by the Coarse: A topological paradigm for
              data analysis",
  author   = "Krim, H and Gentimis, T and Chintakunta, H",
  abstract = "The increasing interest in big data applications is ushering in a
              large effort in seeking new, efficient, and adapted data models
              to reduce complexity, while preserving maximal intrinsic
              information. Graph-based models have recently been getting a lot
              of attention on account of their intuitive and direct connection
              to the data [43]. The cost of these models, however, is to some
              extent giving up geometric insight as well as algebraic
              flexibility.",
  journal  = "IEEE Signal Process. Mag.",
  volume   =  33,
  number   =  2,
  pages    = "95--104",
  month    =  mar,
  year     =  2016,
  keywords = "Big Data;data analysis;data models;graph theory;Big Data
              application;adapted data model;graph-based model;data
              analysis;Topology;Three-dimensional displays;Data analysis;Big
              data;Time series analysis;Delays"
}

@ARTICLE{Curto2008-cc,
  title     = "Cell groups reveal structure of stimulus space",
  author    = "Curto, Carina and Itskov, Vladimir",
  abstract  = "An important task of the brain is to represent the outside
               world. It is unclear how the brain may do this, however, as it
               can only rely on neural responses and has no independent access
               to external stimuli in order to ``decode'' what those responses
               mean. We investigate what can be learned about a space of
               stimuli using only the action potentials (spikes) of cells with
               stereotyped -- but unknown -- receptive fields. Using
               hippocampal place cells as a model system, we show that one can
               (1) extract global features of the environment and (2) construct
               an accurate representation of space, up to an overall scale
               factor, that can be used to track the animal's position. Unlike
               previous approaches to reconstructing position from place cell
               activity, this information is derived without knowing place
               fields or any other functions relating neural responses to
               position. We find that simply knowing which groups of cells fire
               together reveals a surprising amount of structure in the
               underlying stimulus space; this may enable the brain to
               construct its own internal representations.",
  journal   = "PLoS Comput. Biol.",
  publisher = "journals.plos.org",
  volume    =  4,
  number    =  10,
  pages     = "e1000205",
  month     =  oct,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Giusti2015-fa,
  title     = "Clique topology reveals intrinsic geometric structure in neural
               correlations",
  author    = "Giusti, Chad and Pastalkova, Eva and Curto, Carina and Itskov,
               Vladimir",
  abstract  = "Detecting meaningful structure in neural activity and
               connectivity data is challenging in the presence of hidden
               nonlinearities, where traditional eigenvalue-based methods may
               be misleading. We introduce a novel approach to matrix analysis,
               called clique topology, that extracts features of the data
               invariant under nonlinear monotone transformations. These
               features can be used to detect both random and geometric
               structure, and depend only on the relative ordering of matrix
               entries. We then analyzed the activity of pyramidal neurons in
               rat hippocampus, recorded while the animal was exploring a 2D
               environment, and confirmed that our method is able to detect
               geometric organization using only the intrinsic pattern of
               neural correlations. Remarkably, we found similar results during
               nonspatial behaviors such as wheel running and rapid eye
               movement (REM) sleep. This suggests that the geometric structure
               of correlations is shaped by the underlying hippocampal circuits
               and is not merely a consequence of position coding. We propose
               that clique topology is a powerful new tool for matrix analysis
               in biological settings, where the relationship of observed
               quantities to more meaningful variables is often nonlinear and
               unknown.",
  journal   = "Proc. Natl. Acad. Sci. U. S. A.",
  publisher = "National Acad Sciences",
  volume    =  112,
  number    =  44,
  pages     = "13455--13460",
  month     =  nov,
  year      =  2015,
  keywords  = "Betti curves; clique topology; neural coding; structure of
               neural correlation; topological data analysis",
  language  = "en"
}

@ARTICLE{Giusti2016-st,
  title    = "Two's company, three (or more) is a simplex :
              Algebraic-topological tools for understanding higher-order
              structure in neural data",
  author   = "Giusti, Chad and Ghrist, Robert and Bassett, Danielle S",
  abstract = "The language of graph theory, or network science, has proven to
              be an exceptional tool for addressing myriad problems in
              neuroscience. Yet, the use of networks is predicated on a
              critical simplifying assumption: that the quintessential unit of
              interest in a brain is a dyad - two nodes (neurons or brain
              regions) connected by an edge. While rarely mentioned, this
              fundamental assumption inherently limits the types of neural
              structure and function that graphs can be used to model. Here, we
              describe a generalization of graphs that overcomes these
              limitations, thereby offering a broad range of new possibilities
              in terms of modeling and measuring neural phenomena.
              Specifically, we explore the use of simplicial complexes: a
              structure developed in the field of mathematics known as
              algebraic topology, of increasing applicability to real data due
              to a rapidly growing computational toolset. We review the
              underlying mathematical formalism as well as the budding
              literature applying simplicial complexes to neural data, from
              electrophysiological recordings in animal models to hemodynamic
              fluctuations in humans. Based on the exceptional flexibility of
              the tools and recent ground-breaking insights into neural
              function, we posit that this framework has the potential to
              eclipse graph theory in unraveling the fundamental mysteries of
              cognition.",
  journal  = "J. Comput. Neurosci.",
  volume   =  41,
  number   =  1,
  pages    = "1--14",
  month    =  aug,
  year     =  2016,
  keywords = "Filtration; Networks; Simplicial complex; Topology",
  language = "en"
}

@ARTICLE{Cox2016-ty,
  title         = "Clique Topology Reveals Intrinsic Geometric Structure in
                   Neural Correlations: An Overview",
  author        = "Cox, David",
  abstract      = "This publication serves as an overview of clique topology --
                   a novel matrix analysis technique used to extract structural
                   features from neural activity data that contains hidden
                   nonlinearities. We highlight work done by Gusti et al. which
                   introduces clique topology and verifies its applicability to
                   neural feature extraction by showing that neural
                   correlations in the rat hippocampus are determined by
                   geometric structure of hippocampal circuits, rather than
                   being a consequence of positional coding.",
  month         =  aug,
  year          =  2016,
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.NC",
  eprint        = "1608.03463"
}

@ARTICLE{Ghrist2007-kx,
  title    = "Barcodes: The persistent topology of data",
  author   = "Ghrist, Robert",
  abstract = "This article surveys recent work of Carlsson and collaborators on
              applications of computational algebraic topology to problems of
              feature detection and shape recognition in high-dimensional data.
              The primary mathematical tool considered is a homology theory for
              point-cloud data sets--persistent homology--and a novel
              representation of this algebraic characterization--barcodes. We
              sketch an application of these techniques to the classification
              of natural images.",
  journal  = "Bull. Am. Math. Soc.",
  volume   =  45,
  number   =  01,
  pages    = "61--76",
  month    =  oct,
  year     =  2007
}

@ARTICLE{Dabaghian2014-yp,
  title    = "Reconceiving the hippocampal map as a topological template",
  author   = "Dabaghian, Yuri and Brandt, Vicky L and Frank, Loren M",
  abstract = "The role of the hippocampus in spatial cognition is
              incontrovertible yet controversial. Place cells, initially
              thought to be location-specifiers, turn out to respond
              promiscuously to a wide range of stimuli. Here we test the idea,
              which we have recently demonstrated in a computational model,
              that the hippocampal place cells may ultimately be interested in
              a space's topological qualities (its connectivity) more than its
              geometry (distances and angles); such higher-order functioning
              would be more consistent with other known hippocampal functions.
              We recorded place cell activity in rats exploring morphing linear
              tracks that allowed us to dissociate the geometry of the track
              from its topology. The resulting place fields preserved the
              relative sequence of places visited along the track but did not
              vary with the metrical features of the track or the direction of
              the rat's movement. These results suggest a reinterpretation of
              previous studies and new directions for future experiments.",
  journal  = "Elife",
  volume   =  3,
  pages    = "e03476",
  month    =  aug,
  year     =  2014,
  keywords = "geometry; hippocampus; place cells; spatial learning; topology",
  language = "en"
}

@ARTICLE{Cholvin2013-ad,
  title    = "The ventral midline thalamus contributes to strategy shifting in
              a memory task requiring both prefrontal cortical and hippocampal
              functions",
  author   = "Cholvin, Thibault and Loureiro, Micha{\"e}l and Cassel, Raphaelle
              and Cosquer, Brigitte and Geiger, Karine and De Sa Nogueira,
              David and Raingard, H{\'e}l{\`e}ne and Robelin, Laura and Kelche,
              Christian and Pereira de Vasconcelos, Anne and Cassel,
              Jean-Christophe",
  abstract = "Electrophysiological and neuroanatomical evidence for reciprocal
              connections with the medial prefrontal cortex (mPFC) and the
              hippocampus make the reuniens and rhomboid (ReRh) thalamic nuclei
              a putatively major functional link for regulations of
              cortico-hippocampal interactions. In a first experiment using a
              new water escape device for rodents, the double-H maze, we
              demonstrated in rats that a bilateral muscimol (MSCI)
              inactivation (0.70 vs 0.26 and 0 nmol) of the mPFC or dorsal
              hippocampus (dHip) induces major deficits in a strategy
              shifting/spatial memory retrieval task. By way of comparison,
              only dHip inactivation impaired recall in a classical spatial
              memory task in the Morris water maze. In the second experiment,
              we showed that ReRh inactivation using 0.70 nmol of MSCI, which
              reduced performance without obliterating memory retrieval in the
              water maze, produces an as large strategy shifting/memory
              retrieval deficit as mPFC or dHip inactivation in the double-H
              maze. Thus, behavioral adaptations to task contingency
              modifications requiring a shift toward the use of a memory for
              place might operate in a distributed circuit encompassing the
              mPFC (as the potential set-shifting structure), the hippocampus
              (as the spatial memory substrate), and the ventral midline
              thalamus, and therein the ReRh (as the coordinator of this
              processing). The results of the current experiments provide a
              significant extension of our understanding of the involvement of
              ventral midline thalamic nuclei in cognitive processes: they
              point to a role of the ReRh in strategy shifting in a memory task
              requiring cortical and hippocampal functions and further
              elucidate the functional system underlying behavioral
              flexibility.",
  journal  = "J. Neurosci.",
  volume   =  33,
  number   =  20,
  pages    = "8772--8783",
  month    =  may,
  year     =  2013,
  language = "en"
}

@ARTICLE{Ito2018-xs,
  title    = "Prefrontal-hippocampal interactions for spatial navigation",
  author   = "Ito, Hiroshi T",
  abstract = "Animals have the ability to navigate to a desired location by
              making use of information about environmental landmarks and their
              own movements. While decades of neuroscience research have
              identified neurons in the hippocampus and parahippocampal
              structures that represent an animal's position in space, it is
              still largely unclear how an animal can choose the next movement
              direction to reach a desired goal. As the goal destination is
              typically located somewhere outside of the range of sensory
              perception, the animal is required to rely on the internal metric
              of space to estimate the direction and distance of the
              destination to plan a next action. Therefore, the hippocampal
              spatial map should interact with action-planning systems in other
              cortical regions. In accordance with this idea, several recent
              studies have indicated the importance of functional interactions
              between the hippocampus and the prefrontal cortex for
              goal-directed navigation. In this paper, I will review these
              studies and discuss how an animal can estimate its future
              positions correspond to a next movement. Investigation of the
              navigation problem may further provide general insights into
              internal models of the brain for action planning.",
  journal  = "Neurosci. Res.",
  volume   =  129,
  pages    = "2--7",
  month    =  apr,
  year     =  2018,
  keywords = "Hippocampus; Prefrontal cortex; Spatial navigation",
  language = "en"
}

@ARTICLE{McKenna2004-kw,
  title    = "Afferent projections to nucleus reuniens of the thalamus",
  author   = "McKenna, James Timothy and Vertes, Robert P",
  abstract = "The nucleus reuniens (RE) is the largest of the midline nuclei of
              the thalamus and the major source of thalamic afferents to the
              hippocampus and parahippocampal structures. Nucleus reuniens has
              recently been shown to exert powerful excitatory actions on CA1
              of the hippocampus. Few reports on any species have examined
              afferent projections to nucleus reuniens. By using the retrograde
              anatomical tracer Fluorogold, we examined patterns of afferent
              projections to RE in the rat. We showed that RE receives a
              diverse and widely distributed set of afferents projections. The
              main sources of input to nucleus reuniens were from the
              orbitomedial, insular, ectorhinal, perirhinal, and retrosplenial
              cortices; CA1/subiculum of hippocampus; claustrum, tania tecta,
              lateral septum, substantia innominata, and medial and lateral
              preoptic nuclei of the basal forebrain; medial nucleus of
              amygdala; paraventricular and lateral geniculate nuclei of the
              thalamus; zona incerta; anterior, ventromedial, lateral,
              posterior, supramammillary, and dorsal premammillary nuclei of
              the hypothalamus; and ventral tegmental area, periaqueductal
              gray, medial and posterior pretectal nuclei, superior colliculus,
              precommissural/commissural nuclei, nucleus of the posterior
              commissure, parabrachial nucleus, laterodorsal and
              pedunculopontine tegmental nuclei, nucleus incertus, and dorsal
              and median raphe nuclei of the brainstem. The present findings of
              widespread projections to RE, mainly from
              limbic/limbic-associated structures, suggest that nucleus
              reuniens represents a critical relay in the transfer of limbic
              information (emotional/cognitive) from RE to its major targets,
              namely, to the hippocampus and orbitomedial prefrontal cortex. RE
              appears to be a major link in the two-way exchange of information
              between the hippocampus and the medial prefrontal cortex.",
  journal  = "J. Comp. Neurol.",
  volume   =  480,
  number   =  2,
  pages    = "115--142",
  month    =  dec,
  year     =  2004,
  language = "en"
}

@ARTICLE{Varela2014-yv,
  title    = "Anatomical substrates for direct interactions between
              hippocampus, medial prefrontal cortex, and the thalamic nucleus
              reuniens",
  author   = "Varela, C and Kumar, S and Yang, J Y and Wilson, M A",
  abstract = "The reuniens nucleus in the midline thalamus projects to the
              medial prefrontal cortex (mPFC) and the hippocampus, and has been
              suggested to modulate interactions between these regions, such as
              spindle-ripple correlations during sleep and theta band coherence
              during exploratory behavior. Feedback from the hippocampus to the
              nucleus reuniens has received less attention but has the
              potential to influence thalamocortical networks as a function of
              hippocampal activation. We used the retrograde tracer cholera
              toxin B conjugated to two fluorophores to study thalamic
              projections to the dorsal and ventral hippocampus and to the
              prelimbic and infralimbic subregions of mPFC. We also examined
              the feedback connections from the hippocampus to reuniens. The
              goal was to evaluate the anatomical basis for direct coordination
              between reuniens, mPFC, and hippocampus by looking for
              double-labeled cells in reuniens and hippocampus. In confirmation
              of previous reports, the nucleus reuniens was the origin of most
              thalamic afferents to the dorsal hippocampus, whereas both
              reuniens and the lateral dorsal nucleus projected to ventral
              hippocampus. Feedback from hippocampus to reuniens originated
              primarily in the dorsal and ventral subiculum. Thalamic cells
              with collaterals to mPFC and hippocampus were found in reuniens,
              across its anteroposterior axis, and represented, on average,
              about 8 \% of the labeled cells in reuniens. Hippocampal cells
              with collaterals to mPFC and reuniens were less common (~1 \% of
              the labeled subicular cells), and located in the molecular layer
              of the subiculum. The results indicate that a subset of reuniens
              cells can directly coordinate activity in mPFC and hippocampus.
              Cells with collaterals in the hippocampus-reuniens-mPFC network
              may be important for the systems consolidation of memory traces
              and for theta synchronization during exploratory behavior.",
  journal  = "Brain Struct. Funct.",
  volume   =  219,
  number   =  3,
  pages    = "911--929",
  month    =  may,
  year     =  2014,
  language = "en"
}

@ARTICLE{Kim2016-zg,
  title    = "Simultaneous fast measurement of circuit dynamics at multiple
              sites across the mammalian brain",
  author   = "Kim, Christina K and Yang, Samuel J and Pichamoorthy, Nandini and
              Young, Noah P and Kauvar, Isaac and Jennings, Joshua H and
              Lerner, Talia N and Berndt, Andre and Lee, Soo Yeun and
              Ramakrishnan, Charu and Davidson, Thomas J and Inoue, Masatoshi
              and Bito, Haruhiko and Deisseroth, Karl",
  abstract = "Real-time activity measurements from multiple specific cell
              populations and projections are likely to be important for
              understanding the brain as a dynamical system. Here we developed
              frame-projected independent-fiber photometry (FIP), which we used
              to record fluorescence activity signals from many brain regions
              simultaneously in freely behaving mice. We explored the
              versatility of the FIP microscope by quantifying real-time
              activity relationships among many brain regions during social
              behavior, simultaneously recording activity along multiple axonal
              pathways during sensory experience, performing simultaneous
              two-color activity recording, and applying optical perturbation
              tuned to elicit dynamics that match naturally occurring patterns
              observed during behavior.",
  journal  = "Nat. Methods",
  volume   =  13,
  number   =  4,
  pages    = "325--328",
  month    =  apr,
  year     =  2016,
  language = "en"
}

@ARTICLE{Guo2015-ev,
  title    = "Multi-channel fiber photometry for population neuronal activity
              recording",
  author   = "Guo, Qingchun and Zhou, Jingfeng and Feng, Qiru and Lin, Rui and
              Gong, Hui and Luo, Qingming and Zeng, Shaoqun and Luo, Minmin and
              Fu, Ling",
  abstract = "Fiber photometry has become increasingly popular among
              neuroscientists as a convenient tool for the recording of
              genetically defined neuronal population in behaving animals.
              Here, we report the development of the multi-channel fiber
              photometry system to simultaneously monitor neural activities in
              several brain areas of an animal or in different animals. In this
              system, a galvano-mirror modulates and cyclically couples the
              excitation light to individual multimode optical fiber bundles. A
              single photodetector collects excited light and the configuration
              of fiber bundle assembly and the scanner determines the total
              channel number. We demonstrated that the system exhibited
              negligible crosstalk between channels and optical signals could
              be sampled simultaneously with a sample rate of at least 100 Hz
              for each channel, which is sufficient for recording calcium
              signals. Using this system, we successfully recorded GCaMP6
              fluorescent signals from the bilateral barrel cortices of a
              head-restrained mouse in a dual-channel mode, and the
              orbitofrontal cortices of multiple freely moving mice in a
              triple-channel mode. The multi-channel fiber photometry system
              would be a valuable tool for simultaneous recordings of
              population activities in different brain areas of a given animal
              and different interacting individuals.",
  journal  = "Biomed. Opt. Express",
  volume   =  6,
  number   =  10,
  pages    = "3919--3931",
  month    =  oct,
  year     =  2015,
  keywords = "(170.0170) Medical optics and biotechnology; (170.2150)
              Endoscopic imaging; (170.2655) Functional monitoring and imaging;
              (180.2520) Fluorescence microscopy",
  language = "en"
}

@ARTICLE{Chaudhuri2019-yh,
  title     = "The intrinsic attractor manifold and population dynamics of a
               canonical cognitive circuit across waking and sleep",
  author    = "Chaudhuri, Rishidev and Ger{\c c}ek, Berk and Pandey, Biraj and
               Peyrache, Adrien and Fiete, Ila",
  abstract  = "Neural circuits construct distributed representations of key
               variables-external stimuli or internal constructs of quantities
               relevant for survival, such as an estimate of one's location in
               the world-as vectors of population activity. Although population
               activity vectors may have thousands of entries (dimensions), we
               consider that they trace out a low-dimensional manifold whose
               dimension and topology match the represented variable. This
               manifold perspective enables blind discovery and decoding of the
               represented variable using only neural population activity
               (without knowledge of the input, output, behavior or
               topography). We characterize and directly visualize manifold
               structure in the mammalian head direction circuit, revealing
               that the states form a topologically nontrivial one-dimensional
               ring. The ring exhibits isometry and is invariant across waking
               and rapid eye movement sleep. This result directly demonstrates
               that there are continuous attractor dynamics and enables
               powerful inference about mechanism. Finally, external rather
               than internal noise limits memory fidelity, and the manifold
               approach reveals new dynamical trajectories during sleep.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  22,
  number    =  9,
  pages     = "1512--1520",
  month     =  sep,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Spreemann2015-as,
  title         = "Using persistent homology to reveal hidden information in
                   neural data",
  author        = "Spreemann, Gard and Dunn, Benjamin and Botnan, Magnus Bakke
                   and Baas, Nils A",
  abstract      = "We propose a method, based on persistent homology, to
                   uncover topological properties of a priori unknown
                   covariates of neuron activity. Our input data consist of
                   spike train measurements of a set of neurons of interest, a
                   candidate list of the known stimuli that govern neuron
                   activity, and the corresponding state of the animal
                   throughout the experiment performed. Using a generalized
                   linear model for neuron activity and simple assumptions on
                   the effects of the external stimuli, we infer away any
                   contribution to the observed spike trains by the candidate
                   stimuli. Persistent homology then reveals useful information
                   about any further, unknown, covariates.",
  month         =  oct,
  year          =  2015,
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.NC",
  eprint        = "1510.06629"
}

@ARTICLE{Baas2017-zd,
  title    = "On the concept of space in neuroscience",
  author   = "Baas, Nils A",
  abstract = "In this paper we study recording of neurons creating spatial
              information in the brain. To sets of spike trains we associate a
              topological space which captures the structure of the space in
              which the movement takes place. This space has an even richer
              structure depending on other than spatial stimuli. We describe a
              method to separate the various stimuli and conclude when they
              describe the structure of the space. We discuss what we should
              mean by neural space and its structure, and come up with some
              speculations for the future.",
  journal  = "Current Opinion in Systems Biology",
  volume   =  1,
  pages    = "32--37",
  month    =  feb,
  year     =  2017,
  keywords = "Neurons; spike trains; place cells; grid cells; persistent
              homology; dynamic Ising model; neural space; hyperstructure"
}

@ARTICLE{Chen2014-rg,
  title    = "Neural representation of spatial topology in the rodent
              hippocampus",
  author   = "Chen, Zhe and Gomperts, Stephen N and Yamamoto, Jun and Wilson,
              Matthew A",
  abstract = "Pyramidal cells in the rodent hippocampus often exhibit clear
              spatial tuning in navigation. Although it has been long suggested
              that pyramidal cell activity may underlie a topological code
              rather than a topographic code, it remains unclear whether an
              abstract spatial topology can be encoded in the ensemble spiking
              activity of hippocampal place cells. Using a statistical approach
              developed previously, we investigate this question and related
              issues in greater detail. We recorded ensembles of hippocampal
              neurons as rodents freely foraged in one- and two-dimensional
              spatial environments and used a ``decode-to-uncover'' strategy to
              examine the temporally structured patterns embedded in the
              ensemble spiking activity in the absence of observed spatial
              correlates during periods of rodent navigation or awake
              immobility. Specifically, the spatial environment was represented
              by a finite discrete state space. Trajectories across spatial
              locations (``states'') were associated with consistent
              hippocampal ensemble spiking patterns, which were characterized
              by a state transition matrix. From this state transition matrix,
              we inferred a topology graph that defined the connectivity in the
              state space. In both one- and two-dimensional environments, the
              extracted behavior patterns from the rodent hippocampal
              population codes were compared against randomly shuffled spike
              data. In contrast to a topographic code, our results support the
              efficiency of topological coding in the presence of sparse sample
              size and fuzzy space mapping. This computational approach allows
              us to quantify the variability of ensemble spiking activity,
              examine hippocampal population codes during off-line states, and
              quantify the topological complexity of the environment.",
  journal  = "Neural Comput.",
  volume   =  26,
  number   =  1,
  pages    = "1--39",
  month    =  jan,
  year     =  2014,
  language = "en"
}

@ARTICLE{Curto2016-sc,
  title    = "What can topology tell us about the neural code?",
  author   = "Curto, Carina",
  abstract = "Neuroscience is undergoing a period of rapid experimental
              progress and expansion. New mathematical tools, previously
              unknown in the neuroscience community, are now being used to
              tackle fundamental questions and analyze emerging data sets.
              Consistent with this trend, the last decade has seen an uptick in
              the use of topological ideas and methods in neuroscience. In this
              paper I will survey recent applications of topology in
              neuroscience, and explain why topology is an especially natural
              tool for understanding neural codes.",
  journal  = "Bull. Am. Math. Soc.",
  volume   =  54,
  number   =  1,
  pages    = "63--78",
  month    =  sep,
  year     =  2016
}

@ARTICLE{Alexander2015-vc,
  title    = "Retrosplenial cortex maps the conjunction of internal and
              external spaces",
  author   = "Alexander, Andrew S and Nitz, Douglas A",
  abstract = "Intelligent behavior demands not only multiple forms of spatial
              representation, but also coordination among the brain regions
              mediating those representations. Retrosplenial cortex is densely
              interconnected with the majority of cortical and subcortical
              brain structures that register an animal's position in multiple
              internal and external spatial frames of reference. This unique
              anatomy suggests that it functions to integrate distinct forms of
              spatial information and provides an interface for transformations
              between them. Evidence for this was found in rats traversing two
              different routes placed at different environmental locations.
              Retrosplenial ensembles robustly encoded conjunctions of progress
              through the current route, position in the larger environment and
              the left versus right turning behavior of the animal. Thus, the
              retrosplenial cortex has the requisite dynamics to serve as an
              intermediary between brain regions generating different forms of
              spatial mapping, a result that is consistent with navigational
              and episodic memory impairments following damage to this region
              in humans.",
  journal  = "Nat. Neurosci.",
  volume   =  18,
  number   =  8,
  pages    = "1143--1151",
  month    =  aug,
  year     =  2015,
  language = "en"
}

@UNPUBLISHED{McClain2019-rs,
  title    = "Position-theta-phase model of hippocampal place cell activity
              applied to quantification of running speed modulation of firing
              rate",
  author   = "McClain, Kathryn and Tingley, David and Heeger, David and
              Buzs{\'a}ki, Gy{\"o}rgy",
  abstract = "Abstract Spiking activity of place cells in the hippocampus
              encodes the animal's position as it moves through an environment.
              Within a cell's place field, both the firing rate and the phase
              of spiking in the local theta oscillation contain spatial
              information. We propose a position-theta-phase (PTP) model that
              captures the simultaneous expression of the firing-rate code and
              theta-phase code in place cell spiking. This model parametrically
              characterizes place fields to compare across cells, time and
              condition, generates realistic place cell simulation data, and
              conceptualizes a framework for principled hypothesis testing to
              identify additional features of place cell activity. We use the
              PTP model to assess the effect of running speed in place cell
              data recorded from rats running on linear tracks. For the
              majority of place fields we do not find evidence for speed
              modulation of the firing rate. For a small subset of place
              fields, we find firing rates significantly increase or decrease
              with speed. We use the PTP model to compare candidate mechanisms
              of speed modulation in significantly modulated fields, and
              determine that speed acts as a gain control on the magnitude of
              firing rate. Our model provides a tool that connects rigorous
              analysis with a computational framework for understanding place
              cell activity.Significance The hippocampus is heavily studied in
              the context of spatial navigation, and the format of spatial
              information in hippocampus is multifaceted and complex.
              Furthermore, the hippocampus is also thought to contain
              information about other important aspects of behavior such as
              running speed, though there is not agreement on the nature and
              magnitude of their effect. To understand how all of these
              variables are simultaneously represented and used to guide
              behavior, a theoretical framework is needed that can be directly
              applied to the data we record. We present a model that captures
              well-established spatial-encoding features of hippocampal
              activity and provides the opportunity to identify and incorporate
              novel features for our collective understanding.",
  journal  = "bioRxiv",
  pages    = "714105",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@ARTICLE{Friedmann_undated-xv,
  title  = "Mapping Mesoscale Axonal Projections in the Mouse Brain Using A
            {3D} Convolutional Network",
  author = "Friedmann, Drew and Pun, Albert and Adams, Eliza L and Lui, Jan H
            and Kebschull, Justus M and Grutzner, Sophie M and Castagnola,
            Caitlin and Tessier-Lavigne, Marc and Luo, Liqun"
}

@ARTICLE{Rubin2019-tw,
  title    = "Revealing neural correlates of behavior without behavioral
              measurements",
  author   = "Rubin, Alon and Sheintuch, Liron and Brande-Eilat, Noa and
              Pinchasof, Or and Rechavi, Yoav and Geva, Nitzan and Ziv, Yaniv",
  abstract = "Measuring neuronal tuning curves has been instrumental for many
              discoveries in neuroscience but requires a priori assumptions
              regarding the identity of the encoded variables. We applied
              unsupervised learning to large-scale neuronal recordings in
              behaving mice from circuits involved in spatial cognition and
              uncovered a highly-organized internal structure of ensemble
              activity patterns. This emergent structure allowed defining for
              each neuron an 'internal tuning-curve' that characterizes its
              activity relative to the network activity, rather than relative
              to any predefined external variable, revealing place-tuning and
              head-direction tuning without relying on measurements of place or
              head-direction. Similar investigation in prefrontal cortex
              revealed schematic representations of distances and actions, and
              exposed a previously unknown variable, the 'trajectory-phase'.
              The internal structure was conserved across mice, allowing using
              one animal's data to decode another animal's behavior. Thus, the
              internal structure of neuronal activity itself enables
              reconstructing internal representations and discovering new
              behavioral variables hidden within a neural code.",
  journal  = "Nat. Commun.",
  volume   =  10,
  number   =  1,
  pages    = "4745",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Kastner2019-xb,
  title    = "Dynamic preferences account for inter-animal variability during
              the continual learning of a cognitive task",
  author   = "Kastner, David B and Miller, Eric A and Yang, Zhounan and Roumis,
              Demetris K and Liu, Daniel F and Frank, Loren M and Dayan, Peter",
  abstract = "In novel situations, behavior necessarily reduces to latent
              biases. How these biases interact with new experiences to enable
              subsequent behavior remains poorly understood. We exposed rats to
              a family of spatial alternation contingencies and developed a
              series of reinforcement learning agents to describe the behavior.
              The performance of these agents shows that accurately describing
              the learning of individual animals requires accounting for their
              individual dynamic preferences as well as general, shared,
              cognitive processes. Agents that include only memory of past
              choice do not account for the behavior. Adding an explicit
              representation of biases allows agents to perform the task as
              rapidly as the rats, to accurately predict critical facets of
              their behavior on which it was not fitted, and to capture
              individual differences quantitatively. Our results illustrate the
              value of making explicit models of learning and highlight the
              importance of considering the initial state of each animal in
              understanding behavior.",
  journal  = "bioRxiv",
  pages    = "808006",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Faisal2008-as,
  title     = "Noise in the nervous system",
  author    = "Faisal, A Aldo and Selen, Luc P J and Wolpert, Daniel M",
  abstract  = "Noise--random disturbances of signals--poses a fundamental
               problem for information processing and affects all aspects of
               nervous-system function. However, the nature, amount and impact
               of noise in the nervous system have only recently been addressed
               in a quantitative manner. Experimental and computational methods
               have shown that multiple noise sources contribute to cellular
               and behavioural trial-to-trial variability. We review the
               sources of noise in the nervous system, from the molecular to
               the behavioural level, and show how noise contributes to
               trial-to-trial variability. We highlight how noise affects
               neuronal networks and the principles the nervous system applies
               to counter detrimental effects of noise, and briefly discuss
               noise's potential benefits.",
  journal   = "Nat. Rev. Neurosci.",
  publisher = "nature.com",
  volume    =  9,
  number    =  4,
  pages     = "292--303",
  month     =  apr,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Beck2012-xf,
  title     = "Not noisy, just wrong: the role of suboptimal inference in
               behavioral variability",
  author    = "Beck, Jeffrey M and Ma, Wei Ji and Pitkow, Xaq and Latham, Peter
               E and Pouget, Alexandre",
  abstract  = "Behavior varies from trial to trial even when the stimulus is
               maintained as constant as possible. In many models, this
               variability is attributed to noise in the brain. Here, we
               propose that there is another major source of variability:
               suboptimal inference. Importantly, we argue that in most tasks
               of interest, and particularly complex ones, suboptimal inference
               is likely to be the dominant component of behavioral
               variability. This perspective explains a variety of intriguing
               observations, including why variability appears to be larger on
               the sensory than on the motor side, and why our sensors are
               sometimes surprisingly unreliable.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  74,
  number    =  1,
  pages     = "30--39",
  month     =  apr,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Ellard2009-vi,
  title    = "Spatial cognition in the gerbil: computing optimal escape routes
              from visual threats",
  author   = "Ellard, Colin G and Eller, Meghan C",
  abstract = "Previous studies in our laboratory have shown that when presented
              with a sudden stimulus simulating an oncoming predator, Mongolian
              gerbils can compute the optimal trajectory to a safe refuge,
              taking into account the position of the threat, the location of a
              clearly visible refuge, and several other contextual variables as
              well. In the present studies, the main goal was to explore the
              abilities of gerbils to use mental representations of spaces that
              were visually occluded by opaque barriers to compute efficient
              escape trajectories. In all studies, gerbils were placed into a
              round open field containing a single refuge. On each trial, an
              overhead visual stimulus was caused to 'fly' overhead, eliciting
              robust escape movements from the gerbils. By manipulating the
              shape and position of a series of opaque barriers that were
              interposed between the gerbils and the refuge, we were able to
              show that gerbils can compute the shortest route to an invisible
              target, even when the available routes to the target are made
              complex by using elaborate barrier shapes. These findings suggest
              that gerbils can maintain representations of their locations with
              respect to salient environmental landmarks and refuges, even when
              such locations are not continuously visible.",
  journal  = "Anim. Cogn.",
  volume   =  12,
  number   =  2,
  pages    = "333--345",
  month    =  mar,
  year     =  2009,
  language = "en"
}

@ARTICLE{Chen2019-pb,
  title    = "{High-Throughput} Mapping of {Long-Range} Neuronal Projection
              Using In Situ Sequencing",
  author   = "Chen, Xiaoyin and Sun, Yu-Chi and Zhan, Huiqing and Kebschull,
              Justus M and Fischer, Stephan and Matho, Katherine and Huang, Z
              Josh and Gillis, Jesse and Zador, Anthony M",
  abstract = "Summary Understanding neural circuits requires deciphering
              interactions among myriad cell types defined by spatial
              organization, connectivity, gene expression, and other
              properties. Resolving these cell types requires both
              single-neuron resolution and high throughput, a challenging
              combination with conventional methods. Here, we introduce
              barcoded anatomy resolved by sequencing (BARseq), a multiplexed
              method based on RNA barcoding for mapping projections of
              thousands of spatially resolved neurons in a single brain and
              relating those projections to other properties such as gene or
              Cre expression. Mapping the projections to 11 areas of 3,579
              neurons in mouse auditory cortex using BARseq confirmed the
              laminar organization of the three top classes (intratelencephalic
              [IT], pyramidal tract-like [PT-like], and corticothalamic [CT])
              of projection neurons. In depth analysis uncovered a projection
              type restricted almost exclusively to transcriptionally defined
              subtypes of IT neurons. By bridging anatomical and transcriptomic
              approaches at cellular resolution with high throughput, BARseq
              can potentially uncover the organizing principles underlying the
              structure and formation of neural circuits.",
  journal  = "Cell",
  volume   =  179,
  number   =  3,
  pages    = "772--786.e19",
  month    =  oct,
  year     =  2019,
  keywords = "high throughput; projection mapping; cellular barcoding;
              sequencing; auditory cortex"
}

@UNPUBLISHED{Van_Wijngaarden2019-md,
  title    = "Representation of Distance and Direction of Nearby Boundaries in
              Retrosplenial Cortex",
  author   = "van Wijngaarden, Joeri B G and Babl, Susanne S and Ito, Hiroshi T",
  abstract = "Borders and edges are salient and behaviourally relevant features
              for navigating the environment. The brain forms dedicated neural
              representations of environmental boundaries, which are assumed to
              serve as a reference for spatial coding. Here we expand this
              border coding network to include the retrosplenial cortex (RSC)
              in which we identified neurons that increase their firing near
              all boundaries of an arena. RSC border cells specifically encode
              walls, but not objects, and maintain their tuning in the absence
              of direct sensory detection. Unlike border cells in the medial
              entorhinal cortex (MEC), RSC border cells are sensitive to the
              animal9s direction to nearby walls located contralateral to the
              recorded hemisphere. Pharmacogenetic inactivation of MEC led to a
              disruption of RSC border coding, but not vice versa, indicating
              network directionality. Together these data shed light on how
              information about distance and direction of boundaries is
              generated in the brain for guiding navigation behaviour.",
  journal  = "bioRxiv",
  pages    = "807453",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Headley2019-if,
  title     = "Embracing Complexity in Defensive Networks",
  author    = "Headley, Drew B and Kanta, Vasiliki and Kyriazi, Pinelopi and
               Par{\'e}, Denis",
  abstract  = "The neural basis of defensive behaviors continues to attract
               much interest, not only because they are important for survival
               but also because their dysregulation may be at the origin of
               anxiety disorders. Recently, a dominant approach in the field
               has been the optogenetic manipulation of specific circuits or
               cell types within these circuits to dissect their role in
               different defensive behaviors. While the usefulness of
               optogenetics is unquestionable, we argue that this method, as
               currently applied, fosters an atomistic conceptualization of
               defensive behaviors, which hinders progress in understanding the
               integrated responses of nervous systems to threats. Instead, we
               advocate for a holistic approach to the problem, including
               observational study of natural behaviors and their neuronal
               correlates at multiple sites, coupled to the use of
               optogenetics, not to globally turn on or off neurons of
               interest, but to manipulate specific activity patterns
               hypothesized to regulate defensive behaviors.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  103,
  number    =  2,
  pages     = "189--201",
  month     =  jul,
  year      =  2019,
  keywords  = "amygdala; defensive behaviors; extinction; fear; infralimbic;
               medial prefrontal cortex; prelimbic",
  language  = "en"
}

@ARTICLE{Honegger2018-xu,
  title    = "Stochasticity, individuality and behavior",
  author   = "Honegger, Kyle and de Bivort, Benjamin",
  abstract = "No two individuals are exactly alike. More than a simple
              platitude, this observation reflects the fundamentally stochastic
              nature of biological systems. The term 'stochastic' describes
              features that cannot be predicted a priori from readily
              measurable variables. In the dichotomous framework in which
              biological variation arises from genetic or environmental
              effects, stochastic effects are classified as environmental
              because they are not passed on to offspring - any non-heritable
              cause is, by definition, environmental. But non-heritable effects
              can be subdivided into those which can be predicted from
              measurable variables, and those that cannot. These latter effects
              are stochastic.",
  journal  = "Curr. Biol.",
  volume   =  28,
  number   =  1,
  pages    = "R8--R12",
  month    =  jan,
  year     =  2018,
  language = "en"
}

@ARTICLE{Calhoun2017-ur,
  title    = "Quantifying behavior to solve sensorimotor transformations:
              advances from worms and flies",
  author   = "Calhoun, Adam J and Murthy, Mala",
  abstract = "The development of new computational tools has recently opened up
              the study of natural behaviors at a precision that was previously
              unachievable. These tools permit a highly quantitative analysis
              of behavioral dynamics at timescales that are well matched to the
              timescales of neural activity. Here we examine how combining
              these methods with established techniques for estimating an
              animal's sensory experience presents exciting new opportunities
              for dissecting the sensorimotor transformations performed by the
              nervous system. We focus this review primarily on examples from
              Caenorhabditis elegans and Drosophila melanogaster-for these
              model systems, computational approaches to characterize behavior,
              in combination with unparalleled genetic tools for neural
              activation, silencing, and recording, have already proven
              instrumental for illuminating underlying neural mechanisms.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  46,
  pages    = "90--98",
  month    =  oct,
  year     =  2017,
  language = "en"
}

@ARTICLE{Chiel1997-dl,
  title    = "The brain has a body: adaptive behavior emerges from interactions
              of nervous system, body and environment",
  author   = "Chiel, H J and Beer, R D",
  abstract = "Studies of mechanisms of adaptive behavior generally focus on
              neurons and circuits. But adaptive behavior also depends on
              interactions among the nervous system, body and environment:
              sensory preprocessing and motor post-processing filter inputs to
              and outputs from the nervous system; co-evolution and
              co-development of nervous system and periphery create matching
              and complementarity between them; body structure creates
              constraints and opportunities for neural control; and continuous
              feedback between nervous system, body and environment are
              essential for normal behavior. This broader view of adaptive
              behavior has been a major underpinning of ecological psychology
              and has influenced behavior-based robotics. Computational
              neuroethology, which jointly models neural control and periphery
              of animals, is a promising methodology for understanding adaptive
              behavior.",
  journal  = "Trends Neurosci.",
  volume   =  20,
  number   =  12,
  pages    = "553--557",
  month    =  dec,
  year     =  1997,
  language = "en"
}

@UNPUBLISHED{Jackson2019-yb,
  title    = "Many paths to the same goal: metaheuristic operation of brains
              during natural behavior",
  author   = "Jackson, Brian J and Fatima, Gusti Lulu and Oh, Sujean and Gire,
              David H",
  abstract = "During self-guided behaviors animals rapidly identify the
              constraints of the problems they face and adaptively employ
              appropriate cognitive strategies and heuristics to solve these
              problems[1][1],[2][2]. This ability is currently an area of
              active investigation in artificial intelligence[3][3]. Recent
              work in computer science has suggested that this type of flexible
              problem solving could be achievable with metaheuristic approaches
              in which specific algorithms are selected based upon the
              identified demands of the problem to be
              solved[4][4],[5][5],[6][6],[7][7]. Investigating how animals
              employ such metaheuristics while solving self-guided natural
              problems is a fertile area for biologically inspired algorithm
              development. Here we show that animals adaptively shift cognitive
              resources between sensory and memory systems during natural
              behavior to optimize performance under uncertainty. We
              demonstrate this using a new, laboratory-based discovery method
              to define the strategies used to solve a difficult optimization
              scenario, the stochastic ``traveling salesman''
              problem[5][5],[8][8],[9][9]. Using this system we precisely
              manipulated the strength of prior information available to
              animals as well as the complexity of the problem. We find that
              rats are capable of efficiently solving this problem, even under
              conditions in which prior information is unreliable and the space
              of possible solutions is large. We compared animal performance to
              a Bayesian search and found that performance is consistent with a
              metaheuristic approach that adaptively allocates cognitive
              resources between sensory processing and memory, enhancing
              sensory acuity and reducing memory load under conditions in which
              prior information is unreliable. Our findings set the foundation
              for new approaches to understand the neural substrates of natural
              behavior as well as the rational development of biologically
              inspired metaheuristic approaches for complex real-world
              optimization. [1]: \#ref-1 [2]: \#ref-2 [3]: \#ref-3 [4]: \#ref-4
              [5]: \#ref-5 [6]: \#ref-6 [7]: \#ref-7 [8]: \#ref-8 [9]: \#ref-9",
  journal  = "bioRxiv",
  pages    = "697607",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@ARTICLE{Spiro1998-pw,
  title    = "Neuroethology: a meeting of brain and behavior",
  author   = "Spiro, J E and White, S A",
  journal  = "Neuron",
  volume   =  21,
  number   =  5,
  pages    = "981--989",
  month    =  nov,
  year     =  1998,
  language = "en"
}

@UNPUBLISHED{Findling2019-yc,
  title    = "Imprecise neural computations as source of human adaptive
              behavior in volatile environments",
  author   = "Findling, Charles and Chopin, Nicolas and Koechlin, Etienne",
  abstract = "Everyday life features uncertain and ever-changing situations. In
              such environments, optimal adaptive behavior requires
              higher-order inferential capabilities to grasp the volatility of
              external contingencies. These capabilities however involve
              complex and rapidly intractable computations, so that we poorly
              understand how humans develop efficient adaptive behaviors in
              such environments. Here we demonstrate this counterintuitive
              result: simple, low-level inferential processes involving
              imprecise computations conforming to the psychophysical Weber Law
              actually lead to near-optimal adaptive behavior, regardless of
              the environment volatility. Using volatile experimental settings,
              we further show that such imprecise, low-level inferential
              processes accounted for observed human adaptive performances,
              unlike optimal adaptive models involving higher-order inferential
              capabilities, their biologically more plausible, algorithmic
              approximations and non-inferential adaptive models like
              reinforcement learning. Thus, minimal inferential capabilities
              may have evolved along with imprecise neural computations as
              contributing to near-optimal adaptive behavior in real-life
              environments, while leading humans to make suboptimal choices in
              canonical decision-making tasks.",
  journal  = "bioRxiv",
  pages    = "799239",
  month    =  oct,
  year     =  2019,
  language = "en"
}

@ARTICLE{Datta2019-ph,
  title     = "Computational Neuroethology: A Call to Action",
  author    = "Datta, Sandeep Robert and Anderson, David J and Branson, Kristin
               and Perona, Pietro and Leifer, Andrew",
  abstract  = "The brain is worthy of study because it is in charge of
               behavior. A flurry of recent technical advances in measuring and
               quantifying naturalistic behaviors provide an important
               opportunity for advancing brain science. However, the problem of
               understanding unrestrained behavior in the context of neural
               recordings and manipulations remains unsolved, and developing
               approaches to addressing this challenge is critical. Here we
               discuss considerations in computational neuroethology---the
               science of quantifying naturalistic behaviors for understanding
               the brain---and propose strategies to evaluate progress. We
               point to open questions that require resolution and call upon
               the broader systems neuroscience community to further develop
               and leverage measures of naturalistic, unrestrained behavior,
               which will enable us to more effectively probe the richness and
               complexity of the brain.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  104,
  number    =  1,
  pages     = "11--24",
  month     =  oct,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Gomez-Marin2019-nv,
  title     = "The Life of Behavior",
  author    = "Gomez-Marin, Alex and Ghazanfar, Asif A",
  abstract  = "Neuroscience needs behavior. However, it is daunting to render
               the behavior of organisms intelligible without suppressing most,
               if not all, references to life. When animals are treated as
               passive stimulus-response, disembodied and identical machines,
               the life of behavior perishes. Here, we distill three biological
               principles (materiality, agency, and historicity), spell out
               their consequences for the study of animal behavior, and
               illustrate them with various examples from the literature. We
               propose to put behavior back into context, with the brain in a
               species-typical body and with the animal's body situated in the
               world; stamp Newtonian time with nested ontogenetic and
               phylogenetic processes that give rise to individuals with their
               own histories; and supplement linear cause-and-effect chains and
               information processing with circular loops of purpose and
               meaning. We believe that conceiving behavior in these ways is
               imperative for neuroscience.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  104,
  number    =  1,
  pages     = "25--36",
  month     =  oct,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Balleine2019-si,
  title     = "The Meaning of Behavior: Discriminating Reflex and Volition in
               the Brain",
  author    = "Balleine, Bernard W",
  abstract  = "The ability to establish behaviorally what psychological
               capacity an animal is deploying---to discern accurately what an
               animal is doing---is key to functional analyses of the brain.
               Our current understanding of these capacities suggests, however,
               that this task is complex; there is evidence that multiple
               capacities are engaged simultaneously and contribute
               independently to the control of behavior. As such, establishing
               the contribution of a cell, circuit, or neural system to any one
               function requires careful dissection of that role from its
               influence on other functions and, therefore, the careful
               selection and design of behavioral tasks fit for that purpose.
               Here I describe recent research that has sought to utilize
               behavioral tools to investigate the neural bases of instrumental
               conditioning, particularly the circuits and systems supporting
               the capacity for goal-directed action, as opposed to conditioned
               reflexes and habits, and how these sources of action control
               interact to generate adaptive behavior.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  104,
  number    =  1,
  pages     = "47--62",
  month     =  oct,
  year      =  2019,
  keywords  = "goal-directed action; habitual action; incentive learning;
               reward; reinforcement; experienced value; predicted value;
               corticostriatal circuits; behavioral analysis",
  language  = "en"
}

@ARTICLE{Keum2019-dz,
  title     = "Neural Basis of Observational Fear Learning: A Potential Model
               of Affective Empathy",
  author    = "Keum, Sehoon and Shin, Hee-Sup",
  abstract  = "Observational fear learning in rodents is a type of
               context-dependent fear conditioning in which an unconditioned
               stimulus (US) is provided vicariously by observing conspecific
               others receiving foot shocks. This suggests the involvement of
               affective empathy, with several recent studies showing many
               similarities between this behavior and human empathy.
               Neurobiologically, it is important to understand the neural
               mechanisms by which the vicarious US activates the fear circuit
               via the affective pain system, obviating the sensory pain
               pathway and eventually leading to fear memory formation. This
               paper reviews current studies on the neural mechanisms
               underlying observational fear learning and provides a
               perspective on future research on this subject.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  104,
  number    =  1,
  pages     = "78--86",
  month     =  oct,
  year      =  2019,
  keywords  = "empathy; observational fear learning; social fear; affective
               pain; and anterior cingulate cortex",
  language  = "en"
}

@ARTICLE{Ma2019-uk,
  title     = "Bayesian Decision Models: A Primer",
  author    = "Ma, Wei Ji",
  abstract  = "To understand decision-making behavior in simple, controlled
               environments, Bayesian models are often useful. First, optimal
               behavior is always Bayesian. Second, even when behavior deviates
               from optimality, the Bayesian approach offers candidate models
               to account for suboptimalities. Third, a realist interpretation
               of Bayesian models opens the door to studying the neural
               representation of uncertainty. In this tutorial, we review the
               principles of Bayesian models of decision making and then focus
               on five case studies with exercises. We conclude with
               reflections and future directions.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  104,
  number    =  1,
  pages     = "164--175",
  month     =  oct,
  year      =  2019,
  language  = "en"
}

@BOOK{Cooper_Jr2015-qw,
  title     = "Escaping From Predators: An Integrative View of Escape Decisions",
  author    = "Cooper (Jr., William and Cooper, Jr, William E and Blumstein,
               Daniel T",
  abstract  = "When a predator attacks, prey are faced with a series of 'if',
               'when' and 'how' escape decisions - these critical questions are
               the foci of this book. Cooper and Blumstein bring together a
               balance of theory and empirical research to summarise over fifty
               years of scattered research and benchmark current thinking in
               the rapidly expanding literature on the behavioural ecology of
               escaping. The book consolidates current and new behaviour models
               with taxonomically divided empirical chapters that demonstrate
               the application of escape theory to different groups. The
               chapters integrate behaviour with physiology, genetics and
               evolution to lead the reader through the complex decisions faced
               by prey during a predator attack, examining how these decisions
               interact with life history and individual variation. The chapter
               on best practice field methodology and the ideas for future
               research presented throughout, ensure this volume is practical
               as well as informative.",
  publisher = "Cambridge University Press",
  month     =  may,
  year      =  2015,
  keywords  = "books",
  language  = "en"
}

@ARTICLE{Zingg2017-bx,
  title    = "{AAV-Mediated} Anterograde Transsynaptic Tagging: Mapping
              Corticocollicular {Input-Defined} Neural Pathways for Defense
              Behaviors",
  author   = "Zingg, Brian and Chou, Xiao-Lin and Zhang, Zheng-Gang and Mesik,
              Lukas and Liang, Feixue and Tao, Huizhong Whit and Zhang, Li I",
  abstract = "To decipher neural circuits underlying brain functions, viral
              tracers are widely applied to map input and output connectivity
              of neuronal populations. Despite the successful application of
              retrograde transsynaptic viruses for identifying presynaptic
              neurons of transduced neurons, analogous anterograde
              transsynaptic tools for tagging postsynaptically targeted neurons
              remain under development. Here, we discovered that
              adeno-associated viruses (AAV1 and AAV9) exhibit anterograde
              transsynaptic spread properties. AAV1-Cre from transduced
              presynaptic neurons effectively and specifically drives
              Cre-dependent transgene expression in selected postsynaptic
              neuronal targets, thus allowing axonal tracing and functional
              manipulations of the latter input-defined neuronal population.
              Its application in superior colliculus (SC) reveals that SC
              neuron subpopulations receiving corticocollicular projections
              from auditory and visual cortex specifically drive flight and
              freezing, two different types of defense behavior, respectively.
              Together with an intersectional approach, AAV-mediated
              anterograde transsynaptic tagging can categorize neurons by their
              inputs and molecular identity, and allow forward screening of
              distinct functional neural pathways embedded in complex brain
              circuits.",
  journal  = "Neuron",
  volume   =  93,
  number   =  1,
  pages    = "33--47",
  month    =  jan,
  year     =  2017,
  keywords = "AAV serotypes; Cre and Flp system; corticofugal projection;
              defensive behavior; flight and freezing; intersectional strategy;
              mapping neural circuits; superior colliculus;
              transsynaptic/transneuronal tracer",
  language = "en"
}

@ARTICLE{White2019-do,
  title    = "The Future Is Open: {Open-Source} Tools for Behavioral
              Neuroscience Research",
  author   = "White, Samantha R and Amarante, Linda M and Kravitz, Alexxai V
              and Laubach, Mark",
  journal  = "eNeuro",
  volume   =  6,
  number   =  4,
  month    =  aug,
  year     =  2019,
  keywords = "behavior; designs; methods; open source; protocols; tools",
  language = "en"
}

@ARTICLE{Krumin2018-vd,
  title     = "Decision and navigation in mouse parietal cortex",
  author    = "Krumin, Michael and Lee, Julie J and Harris, Kenneth D and
               Carandini, Matteo",
  abstract  = "Posterior parietal cortex (PPC) has been implicated in
               navigation, in the control of movement, and in visually-guided
               decisions. To relate these views, we measured activity in PPC
               while mice performed a virtual navigation task driven by visual
               decisions. PPC neurons were selective for specific combinations
               of the animal's spatial position and heading angle. This
               selectivity closely predicted both the activity of individual
               PPC neurons, and the arrangement of their collective firing
               patterns in choice-selective sequences. These sequences
               reflected PPC encoding of the animal's navigation trajectory.
               Using decision as a predictor instead of heading yielded worse
               fits, and using it in addition to heading only slightly improved
               the fits. Alternative models based on visual or motor variables
               were inferior. We conclude that when mice use vision to choose
               their trajectories, a large fraction of parietal cortex activity
               can be predicted from simple attributes such as spatial position
               and heading.",
  journal   = "Elife",
  publisher = "cdn.elifesciences.org",
  volume    =  7,
  month     =  nov,
  year      =  2018,
  keywords  = "cortex; decision; mouse; navigation; neuroscience; visual
               processing",
  language  = "en"
}

@ARTICLE{Harvey2012-th,
  title    = "Choice-specific sequences in parietal cortex during a
              virtual-navigation decision task",
  author   = "Harvey, Christopher D and Coen, Philip and Tank, David W",
  abstract = "The posterior parietal cortex (PPC) has an important role in many
              cognitive behaviours; however, the neural circuit dynamics
              underlying PPC function are not well understood. Here we
              optically imaged the spatial and temporal activity patterns of
              neuronal populations in mice performing a PPC-dependent task that
              combined a perceptual decision and memory-guided navigation in a
              virtual environment. Individual neurons had transient activation
              staggered relative to one another in time, forming a sequence of
              neuronal activation spanning the entire length of a task trial.
              Distinct sequences of neurons were triggered on trials with
              opposite behavioural choices and defined divergent,
              choice-specific trajectories through a state space of neuronal
              population activity. Cells participating in the different
              sequences and at distinct time points in the task were
              anatomically intermixed over microcircuit length scales (<100
              micrometres). During working memory decision tasks, the PPC may
              therefore perform computations through sequence-based circuit
              dynamics, rather than long-lived stable states, implemented using
              anatomically intermingled microcircuits.",
  journal  = "Nature",
  volume   =  484,
  number   =  7392,
  pages    = "62--68",
  month    =  mar,
  year     =  2012,
  language = "en"
}

@ARTICLE{Whitlock2014-oa,
  title    = "Navigating actions through the rodent parietal cortex",
  author   = "Whitlock, Jonathan R",
  abstract = "The posterior parietal cortex (PPC) participates in a manifold of
              cognitive functions, including visual attention, working memory,
              spatial processing, and movement planning. Given the vast
              interconnectivity of PPC with sensory and motor areas, it is not
              surprising that neuronal recordings show that PPC often encodes
              mixtures of spatial information as well as the movements required
              to reach a goal. Recent work sought to discern the relative
              strength of spatial vs. motor signaling in PPC by recording
              single unit activity in PPC of freely behaving rats during
              selective changes in either the spatial layout of the local
              environment or in the pattern of locomotor behaviors executed
              during navigational tasks. The results revealed unequivocally a
              predominant sensitivity of PPC neurons to locomotor action
              structure, with subsets of cells even encoding upcoming movements
              more than 1 s in advance. In light of these and other recent
              findings in the field, I propose that one of the key
              contributions of PPC to navigation is the synthesis of
              goal-directed behavioral sequences, and that the rodent PPC may
              serve as an apt system to investigate cellular mechanisms for
              spatial motor planning as traditionally studied in humans and
              monkeys.",
  journal  = "Front. Hum. Neurosci.",
  volume   =  8,
  pages    = "293",
  month    =  may,
  year     =  2014,
  keywords = "cognitive motor function; parietal cortex; parieto-frontal
              network; rodent model; spatial navigation",
  language = "en"
}

@ARTICLE{Mitchell2018-wv,
  title    = "Retrosplenial cortex and its role in spatial cognition",
  author   = "Mitchell, Anna S and Czajkowski, Rafal and Zhang, Ningyu and
              Jeffery, Kate and Nelson, Andrew J D",
  abstract = "Retrosplenial cortex is a region within the posterior neocortical
              system, heavily interconnected with an array of brain networks,
              both cortical and subcortical, that is, engaged by a myriad of
              cognitive tasks. Although there is no consensus as to its precise
              function, evidence from both human and animal studies clearly
              points to a role in spatial cognition. However, the spatial
              processing impairments that follow retrosplenial cortex damage
              are not straightforward to characterise, leading to difficulties
              in defining the exact nature of its role. In this article, we
              review this literature and classify the types of ideas that have
              been put forward into three broad, somewhat overlapping classes:
              (1) learning of landmark location, stability and permanence; (2)
              integration between spatial reference frames; and (3)
              consolidation and retrieval of spatial knowledge (schemas). We
              evaluate these models and suggest ways to test them, before
              briefly discussing whether the spatial function may be a subset
              of a more general function in episodic memory.",
  journal  = "Brain Neurosci Adv",
  volume   =  2,
  pages    = "2398212818757098",
  month    =  mar,
  year     =  2018,
  keywords = "Learning; cingulate cortex; default mode network;
              electrophysiology; hippocampal formation; immediate-early genes;
              memory; neuroimaging; primate; thalamus",
  language = "en"
}

@ARTICLE{Kaufman2014-cw,
  title    = "Cortical activity in the null space: permitting preparation
              without movement",
  author   = "Kaufman, Matthew T and Churchland, Mark M and Ryu, Stephen I and
              Shenoy, Krishna V",
  abstract = "Neural circuits must perform computations and then selectively
              output the results to other circuits. Yet synapses do not change
              radically at millisecond timescales. A key question then is: how
              is communication between neural circuits controlled? In motor
              control, brain areas directly involved in driving movement are
              active well before movement begins. Muscle activity is some
              readout of neural activity, yet it remains largely unchanged
              during preparation. Here we find that during preparation, while
              the monkey holds still, changes in motor cortical activity cancel
              out at the level of these population readouts. Motor cortex can
              thereby prepare the movement without prematurely causing it.
              Further, we found evidence that this mechanism also operates in
              dorsal premotor cortex, largely accounting for how preparatory
              activity is attenuated in primary motor cortex. Selective use of
              'output-null' vs. 'output-potent' patterns of activity may thus
              help control communication to the muscles and between these brain
              areas.",
  journal  = "Nat. Neurosci.",
  volume   =  17,
  number   =  3,
  pages    = "440--448",
  month    =  mar,
  year     =  2014,
  language = "en"
}

@ARTICLE{Furth2018-lg,
  title    = "An interactive framework for whole-brain maps at cellular
              resolution",
  author   = "F{\"u}rth, Daniel and Vaissi{\`e}re, Thomas and Tzortzi, Ourania
              and Xuan, Yang and M{\"a}rtin, Antje and Lazaridis, Iakovos and
              Spigolon, Giada and Fisone, Gilberto and Tomer, Raju and
              Deisseroth, Karl and Carl{\'e}n, Marie and Miller, Courtney A and
              Rumbaugh, Gavin and Meletis, Konstantinos",
  abstract = "To deconstruct the architecture and function of brain circuits,
              it is necessary to generate maps of neuronal connectivity and
              activity on a whole-brain scale. New methods now enable
              large-scale mapping of the mouse brain at cellular and
              subcellular resolution. We developed a framework to automatically
              annotate, analyze, visualize and easily share whole-brain data at
              cellular resolution, based on a scale-invariant, interactive
              mouse brain atlas. This framework enables connectivity and
              mapping projects in individual laboratories and across imaging
              platforms, as well as multiplexed quantitative information on the
              molecular identity of single neurons. As a proof of concept, we
              generated a comparative connectivity map of five major neuron
              types in the corticostriatal circuit, as well as an
              activity-based map to identify hubs mediating the behavioral
              effects of cocaine. Thus, this computational framework provides
              the necessary tools to generate brain maps that integrate data
              from connectivity, neuron identity and function.",
  journal  = "Nat. Neurosci.",
  volume   =  21,
  number   =  1,
  pages    = "139--149",
  month    =  jan,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Huang2018-ny,
  title    = "High-throughput mapping of mesoscale connectomes in individual
              mice",
  author   = "Huang, Longwen and Kebschull, Justus M and Furth, Daniel and
              Musall, Simon and Kaufman, Matthew T and Churchland, Anne K and
              Zador, Anthony M",
  abstract = "Abstract Brain function is determined by connectivity among brain
              areas, and disruption of this connectivity leads to
              neuropsychiatric disorders. Understanding connectivity is
              essential to modern neuroscience, but mesoscale connectivity
              atlases are currently slow and expensive to generate, exist for
              few model systems, and require pooling across many brains. Here
              we present a method, muMAPseq (multisource Multiplexed Analysis
              of Projections by sequencing), which leverages barcoding and
              high-throughput sequencing to generate atlases from single
              animals rapidly and at low cost. We apply muMAPseq to tracing the
              neocortical connectome of individual mice, and demonstrate high
              reproducibility, and accuracy. Applying muMAPseq to the mutant
              BTBR mouse strain, which lacks a corpus callosum, we recapitulate
              its known connectopathies, and also uncover novel deficits.
              muMAPseq allows individual laboratories to generate atlases
              tailored to individuals, disease models, and new model species,
              and will facilitate quantitative comparative connectomics,
              permitting examination of how age, sex, environment, genetics and
              species affect neuronal wiring.",
  journal  = "bioRxiv",
  pages    = "422477",
  month    =  sep,
  year     =  2018,
  language = "en"
}

@ARTICLE{Wolpert2012-ch,
  title    = "Motor control is decision-making",
  author   = "Wolpert, Daniel M and Landy, Michael S",
  abstract = "Motor behavior may be viewed as a problem of maximizing the
              utility of movement outcome in the face of sensory, motor and
              task uncertainty. Viewed in this way, and allowing for the
              availability of prior knowledge in the form of a probability
              distribution over possible states of the world, the choice of a
              movement plan and strategy for motor control becomes an
              application of statistical decision theory. This point of view
              has proven successful in recent years in accounting for movement
              under risk, inferring the loss function used in motor tasks, and
              explaining motor behavior in a wide variety of circumstances.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "996--1003",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Wong2015-pi,
  title    = "Motor Planning",
  author   = "Wong, Aaron L and Haith, Adrian M and Krakauer, John W",
  abstract = "Motor planning colloquially refers to any process related to the
              preparation of a movement that occurs during the reaction time
              prior to movement onset. However, this broad definition
              encompasses processes that are not strictly motor-related, such
              as decision-making about the identity of task-relevant stimuli in
              the environment. Furthermore, the assumption that all
              motor-planning processes require processing time, and can
              therefore be studied behaviorally by measuring changes in the
              reaction time, needs to be reexamined. In this review, we take a
              critical look at the processes leading from perception to action
              and suggest a definition of motor planning that encompasses only
              those processes necessary for a movement to be executed-that is,
              processes that are strictly movement related. These processes
              resolve the ambiguity inherent in an abstract goal by defining a
              specific movement to achieve it. We propose that the majority of
              processes that meet this definition can be completed nearly
              instantaneously, which means that motor planning itself in fact
              consumes only a small fraction of the reaction time.",
  journal  = "Neuroscientist",
  volume   =  21,
  number   =  4,
  pages    = "385--398",
  month    =  aug,
  year     =  2015,
  keywords = "attention; decision making; dynamical systems model; motor
              control; motor goal; optimal control theory; reaction time",
  language = "en"
}

@ARTICLE{Mitrofanis2005-lq,
  title    = "Some certainty for the ``zone of uncertainty''? Exploring the
              function of the zona incerta",
  author   = "Mitrofanis, J",
  abstract = "The zona incerta (ZI), first described over a century ago by
              Auguste Forel as a ``region of which nothing certain can be
              said,'' forms a collection of cells that derives from the
              diencephalon. To this day, we are still not certain of the
              precise function of this ``zone of uncertainty'' although many
              have been proposed, from controlling visceral activity to
              shifting attention and from influencing arousal to maintaining
              posture and locomotion. In this review, I shall outline the
              recent advances in the understanding of the structure,
              connectivity and functions of the ZI. I will then focus on a
              possible and often neglected global role for the ZI, one that
              links its diverse functions together. In particular, I aim to
              highlight the idea that the ZI forms a primal center of the
              diencephalon for generating direct responses (visceral, arousal,
              attention and/or posture-locomotion) to a given sensory (somatic
              and/or visceral) stimulus. With this global role in mind, I will
              then address recent results indicating that abnormal ZI activity
              manifests in clinical symptoms of Parkinson disease.",
  journal  = "Neuroscience",
  volume   =  130,
  number   =  1,
  pages    = "1--15",
  year     =  2005,
  language = "en"
}

@ARTICLE{Chou2018-sq,
  title    = "Inhibitory gain modulation of defense behaviors by zona incerta",
  author   = "Chou, Xiao-Lin and Wang, Xiyue and Zhang, Zheng-Gang and Shen, Li
              and Zingg, Brian and Huang, Junxiang and Zhong, Wen and Mesik,
              Lukas and Zhang, Li I and Tao, Huizhong Whit",
  abstract = "Zona incerta (ZI) is a functionally mysterious subthalamic
              nucleus containing mostly inhibitory neurons. Here, we discover
              that GABAergic neurons in the rostral sector of ZI (ZIr) directly
              innervate excitatory but not inhibitory neurons in the
              dorsolateral and ventrolateral compartments of periaqueductal
              gray (PAG), which can drive flight and freezing behaviors
              respectively. Optogenetic activation of ZIr neurons or their
              projections to PAG reduces both sound-induced innate flight
              response and conditioned freezing response, while optogenetic
              suppression of these neurons enhances these defensive behaviors,
              likely through a mechanism of gain modulation. ZIr activity
              progressively increases during extinction of conditioned freezing
              response, and suppressing ZIr activity impairs the expression of
              fear extinction. Furthermore, ZIr is innervated by the medial
              prefrontal cortex (mPFC), and silencing mPFC prevents the
              increase of ZIr activity during extinction and the expression of
              fear extinction. Together, our results suggest that ZIr is
              engaged in modulating defense behaviors.",
  journal  = "Nat. Commun.",
  volume   =  9,
  number   =  1,
  pages    = "1151",
  month    =  mar,
  year     =  2018,
  language = "en"
}

@ARTICLE{Svoboda2018-rr,
  title    = "Neural mechanisms of movement planning: motor cortex and beyond",
  author   = "Svoboda, Karel and Li, Nuo",
  abstract = "Neurons in motor cortex and connected brain regions fire in
              anticipation of specific movements, long before movement occurs.
              This neural activity reflects internal processes by which the
              brain plans and executes volitional movements. The study of motor
              planning offers an opportunity to understand how the structure
              and dynamics of neural circuits support persistent internal
              states and how these states influence behavior. Recent advances
              in large-scale neural recordings are beginning to decipher the
              relationship of the dynamics of populations of neurons during
              motor planning and movements. New behavioral tasks in rodents,
              together with quantified perturbations, link dynamics in specific
              nodes of neural circuits to behavior. These studies reveal a
              neural network distributed across multiple brain regions that
              collectively supports motor planning. We review recent advances
              and highlight areas where further work is needed to achieve a
              deeper understanding of the mechanisms underlying motor planning
              and related cognitive processes.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  49,
  pages    = "33--41",
  month    =  apr,
  year     =  2018,
  language = "en"
}

@ARTICLE{Esposito2014-ls,
  title    = "Brainstem nucleus {MdV} mediates skilled forelimb motor tasks",
  author   = "Esposito, Maria Soledad and Capelli, Paolo and Arber, Silvia",
  abstract = "Translating the behavioural output of the nervous system into
              movement involves interaction between brain and spinal cord. The
              brainstem provides an essential bridge between the two
              structures, but circuit-level organization and function of this
              intermediary system remain poorly understood. Here we use
              intersectional virus tracing and genetic strategies in mice to
              reveal a selective synaptic connectivity matrix between brainstem
              substructures and functionally distinct spinal motor neurons that
              regulate limb movement. The brainstem nucleus medullary reticular
              formation ventral part (MdV) stands out as specifically targeting
              subpopulations of forelimb-innervating motor neurons. Its
              glutamatergic premotor neurons receive synaptic input from key
              upper motor centres and are recruited during motor tasks.
              Selective neuronal ablation or silencing experiments reveal that
              MdV is critically important specifically for skilled motor
              behaviour, including accelerating rotarod and single-food-pellet
              reaching tasks. Our results indicate that distinct premotor
              brainstem nuclei access spinal subcircuits to mediate
              task-specific aspects of motor programs.",
  journal  = "Nature",
  volume   =  508,
  number   =  7496,
  pages    = "351--356",
  month    =  apr,
  year     =  2014,
  language = "en"
}

@ARTICLE{Sul2011-yj,
  title    = "Role of rodent secondary motor cortex in value-based action
              selection",
  author   = "Sul, Jung Hoon and Jo, Suhyun and Lee, Daeyeol and Jung, Min Whan",
  abstract = "Despite widespread neural activity related to reward values,
              signals related to upcoming choice have not been clearly
              identified in the rodent brain. Here we examined neuronal
              activity in the lateral (AGl) and medial (AGm) agranular cortex,
              corresponding to the primary and secondary motor cortex,
              respectively, in rats performing a dynamic foraging task. Choice
              signals, before behavioral manifestation of the rat's choice,
              arose in the AGm earlier than in any other areas of the rat brain
              previously studied under free-choice conditions. The AGm also
              conveyed neural signals for decision value and chosen value. By
              contrast, upcoming choice signals arose later, and value signals
              were weaker, in the AGl. We also found that AGm lesions made the
              rats' choices less dependent on dynamically updated values. These
              results suggest that rodent secondary motor cortex might be
              uniquely involved in both representing and reading out value
              signals for flexible action selection.",
  journal  = "Nat. Neurosci.",
  volume   =  14,
  number   =  9,
  pages    = "1202--1208",
  month    =  aug,
  year     =  2011,
  keywords = "Locomotion;navigation",
  language = "en"
}

@ARTICLE{Wang2015-yh,
  title    = "Collateral pathways from the ventromedial hypothalamus mediate
              defensive behaviors",
  author   = "Wang, Li and Chen, Irene Z and Lin, Dayu",
  abstract = "The ventromedial hypothalamus (VMH) was thought to be essential
              for coping with threat, although its circuit mechanism remains
              unclear. To investigate this, we optogenetically activated
              steroidogenic factor 1 (SF1)-expressing neurons in the
              dorsomedial and central parts of the VMH (VMHdm/c), and observed
              a range of context-dependent somatomotor and autonomic responses
              resembling animals' natural defensive behaviors. By activating
              independent pathways emanating from the VMHdm/c, we demonstrated
              that VMHdm/c projection to the dorsolateral periaqueductal gray
              (dlPAG) induces inflexible immobility, while the VMHdm/c to
              anterior hypothalamic nucleus (AHN) pathway promotes avoidance.
              Consistent with the behavior changes induced by VMH to AHN
              pathway activation, direct activation of the AHN elicited
              avoidance and escape jumping, but not immobility. Retrograde
              tracing studies revealed that nearly 50\% of PAG-projecting
              VMHdm/c neurons send collateral projection to the AHN and vice
              versa. Thus, VMHdm/c neurons employ a one-to-many wiring
              configuration to orchestrate multiple aspects of defensive
              behaviors.",
  journal  = "Neuron",
  volume   =  85,
  number   =  6,
  pages    = "1344--1358",
  month    =  mar,
  year     =  2015,
  language = "en"
}

@ARTICLE{Ferreira-Pinto2018-kr,
  title     = "Connecting Circuits for Supraspinal Control of Locomotion",
  author    = "Ferreira-Pinto, Manuel J and Ruder, Ludwig and Capelli, Paolo
               and Arber, Silvia",
  abstract  = "Locomotion is regulated by distributed circuits and achieved by
               the concerted activation of body musculature. While the basic
               properties of executive circuits in the spinal cord are fairly
               well understood, the precise mechanisms by which the brain
               impacts locomotion are much less clear. This Review discusses
               recent work unraveling the cellular identity, connectivity, and
               function of supraspinal circuits. We focus on their involvement
               in the regulation of the different phases of locomotion and
               their interaction with spinal circuits. Dedicated neuronal
               populations in the brainstem carry locomotor instructions,
               including initiation, speed, and termination. To align
               locomotion with behavioral needs, brainstem output structures
               are recruited by midbrain and forebrain circuits that compute
               and infer volitional, innate, and context-dependent locomotor
               properties. We conclude that the emerging logic of supraspinal
               circuit organization helps to understand how locomotor programs
               from exploration to hunting and escape are regulated by the
               brain.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  100,
  number    =  2,
  pages     = "361--374",
  month     =  oct,
  year      =  2018,
  keywords  = "Locomotion",
  language  = "en"
}

@ARTICLE{Noga2003-nn,
  title     = "Mechanism for activation of locomotor centers in the spinal cord
               by stimulation of the mesencephalic locomotor region",
  author    = "Noga, Brian R and Kriellaars, Dean J and Brownstone, Robert M
               and Jordan, Larry M",
  abstract  = "The synaptic pathways of mesencephalic locomotor region
               (MLR)-evoked excitatory and inhibitory postsynaptic potentials
               (EPSPs and IPSPs) recorded from lumbar motoneurons of
               unanesthetized decerebrate cats during fictive locomotion were
               analyzed prior to, during, and after cold block of the medial
               reticular formation (MedRF) or the low thoracic ventral
               funiculus (VF). As others have shown, electrical stimulation of
               the MLR typically evoked short-latency excitatory or mixed
               excitatory/inhibitory PSPs in flexor and extensor motoneurons.
               The bulbospinal conduction velocities averaged approximately 88
               m/s (range: 62-145 m/s) and segmental latencies for EPSPs ranged
               from 1.2 to 10.9 ms. The histogram of segmental latencies showed
               three peaks, suggesting di-, tri-, and polysynaptic linkages.
               Segmental latencies for IPSPs suggested trisynaptic or
               polysynaptic transmission. Most EPSPs (69/77) were significantly
               larger during the depolarized phase of the intracellular
               locomotor drive potential (LDP), and most IPSPs (35/46) were
               larger during the corresponding hyperpolarized phase. Bilateral
               cooling of the MedRF reversibly abolished locomotion of both
               hindlimbs as measured from the electroneurogram (ENG) activity
               of muscle nerves and simultaneously abolished or diminished the
               motoneuron PSPs and LDPs. Unilateral cooling of the VF blocked
               locomotion ipsilaterally and diminished it contralaterally with
               concomitant loss or decrease the motoneuron PSPs and LDPs.
               Relative to the side of motoneuron recording, cooling of the
               ipsilateral VF sometimes uncovered longer-latency EPSPs, whereas
               cooling of the contralateral VF abolished longer-latency EPSPs.
               It is concluded that MLR stimulation activates a pathway that
               relays in the MedRF and descends bilaterally in the VF to
               contact spinal interneurons that project to motoneurons. Local
               segmental pathways that activate or inhibit motoneurons during
               MLR-evoked fictive locomotion appear to be both ipsilateral and
               contralateral.",
  journal   = "J. Neurophysiol.",
  publisher = "physiology.org",
  volume    =  90,
  number    =  3,
  pages     = "1464--1478",
  month     =  sep,
  year      =  2003,
  language  = "en"
}

@ARTICLE{Thompson2013-zi,
  title    = "Activity in mouse pedunculopontine tegmental nucleus reflects
              action and outcome in a decision-making task",
  author   = "Thompson, John A and Felsen, Gidon",
  abstract = "Recent studies across several mammalian species have revealed a
              distributed network of cortical and subcortical brain regions
              responsible for sensorimotor decision making. Many of these
              regions have been shown to be interconnected with the
              pedunculopontine tegmental nucleus (PPTg), a brain stem structure
              characterized by neuronal heterogeneity and thought to be
              involved in several cognitive and behavioral functions. However,
              whether this structure plays a general functional role in
              sensorimotor decision making is unclear. We hypothesized that, in
              the context of a sensorimotor task, activity in the PPTg would
              reflect task-related variables in a similar manner as do the
              cortical and subcortical regions with which it is anatomically
              associated. To examine this hypothesis, we recorded PPTg activity
              in mice performing an odor-cued spatial choice task requiring a
              stereotyped leftward or rightward orienting movement to obtain a
              reward. We studied single-neuron activity during epochs of the
              task related to movement preparation, execution, and outcome
              (i.e., whether or not the movement was rewarded). We found that a
              substantial proportion of neurons in the PPTg exhibited
              direction-selective activity during one or more of these epochs.
              In addition, an overlapping population of neurons reflected
              movement direction and reward outcome. These results suggest that
              the PPTg should be considered within the network of brain areas
              responsible for sensorimotor decision making and lay the
              foundation for future experiments to examine how the PPTg
              interacts with other regions to control sensory-guided motor
              output.",
  journal  = "J. Neurophysiol.",
  volume   =  110,
  number   =  12,
  pages    = "2817--2829",
  month    =  dec,
  year     =  2013,
  keywords = "basal ganglia; decision making; pedunculopontine tegmental
              nucleus; sensorimotor",
  language = "en"
}

@ARTICLE{Li2018-xo,
  title    = "Hypothalamic Circuits for Predation and Evasion",
  author   = "Li, Yi and Zeng, Jiawei and Zhang, Juen and Yue, Chenyu and
              Zhong, Weixin and Liu, Zhixiang and Feng, Qiru and Luo, Minmin",
  abstract = "The interactions between predator and prey represent some of the
              most dramatic events in nature and constitute a matter of life
              and death for both sides. The hypothalamus has been implicated in
              driving predation and evasion; however, the exact hypothalamic
              neural circuits underlying these behaviors remain poorly defined.
              Here, we demonstrate that inhibitory and excitatory projections
              from the mouse lateral hypothalamus (LH) to the periaqueductal
              gray (PAG) in the midbrain drive, respectively, predation and
              evasion. LH GABA neurons were activated during predation.
              Optogenetically stimulating PAG-projecting LH GABA neurons drove
              strong predatory attack, and inhibiting these cells reversibly
              blocked predation. In contrast, LH glutamate neurons were
              activated during evasion. Stimulating PAG-projecting LH glutamate
              neurons drove evasion and inhibiting them impeded predictive
              evasion. Therefore, the seemingly opposite behaviors of predation
              and evasion are tightly regulated by two dissociable modular
              command systems within a single neural projection from the LH to
              the PAG. VIDEO ABSTRACT.",
  journal  = "Neuron",
  volume   =  97,
  number   =  4,
  pages    = "911--924.e5",
  month    =  feb,
  year     =  2018,
  keywords = "GABA; chemogenetics; escape behavior; fiber photometry;
              glutamate; hunting behavior; lateral hypothalamus; optogenetics;
              periaqueductal gray",
  language = "en"
}

@ARTICLE{Sharma2019-bp,
  title    = "Towards a connectome of descending commands controlling
              locomotion",
  author   = "Sharma, Sandeep and Kim, Linda H and Whelan, Patrick J",
  abstract = "Understanding the neural basis for locomotion is of critical
              importance since it subserves many behaviours necessary for
              survival. The spinal cord contains all the elements required to
              produce the basic locomotor pattern. These elements which compose
              the central pattern generator for locomotion are activated and
              sculpted by descending inputs from the brainstem, subcortical and
              cortical structures. In this review, we examine the aspects of
              descending control of spinal cord circuits, focusing on the
              spinal cord, brainstem, and the diencephalon--hypothalamus. In
              this short review, we discuss recent data and consider
              opportunities for incorporating connectomics and optogenetic
              advances to continue the progress in deciphering the descending
              locomotor connectome.",
  journal  = "Current Opinion in Physiology",
  volume   =  8,
  pages    = "70--75",
  month    =  apr,
  year     =  2019,
  keywords = "Locomotion"
}

@ARTICLE{Roseberry2016-xm,
  title    = "{Cell-Type-Specific} Control of Brainstem Locomotor Circuits by
              Basal Ganglia",
  author   = "Roseberry, Thomas K and Lee, A Moses and Lalive, Arnaud L and
              Wilbrecht, Linda and Bonci, Antonello and Kreitzer, Anatol C",
  abstract = "The basal ganglia (BG) are critical for adaptive motor control,
              but the circuit principles underlying their pathway-specific
              modulation of target regions are not well understood. Here, we
              dissect the mechanisms underlying BG direct and indirect
              pathway-mediated control of the mesencephalic locomotor region
              (MLR), a brainstem target of BG that is critical for locomotion.
              We optogenetically dissect the locomotor function of the three
              neurochemically distinct cell types within the MLR:
              glutamatergic, GABAergic, and cholinergic neurons. We find that
              the glutamatergic subpopulation encodes locomotor state and
              speed, is necessary and sufficient for locomotion, and is
              selectively innervated by BG. We further show activation and
              suppression, respectively, of MLR glutamatergic neurons by direct
              and indirect pathways, which is required for bidirectional
              control of locomotion by BG circuits. These findings provide a
              fundamental understanding of how BG can initiate or suppress a
              motor program through cell-type-specific regulation of neurons
              linked to specific actions.",
  journal  = "Cell",
  volume   =  164,
  number   =  3,
  pages    = "526--537",
  month    =  jan,
  year     =  2016,
  language = "en"
}

@ARTICLE{Josset2018-oj,
  title    = "Distinct Contributions of Mesencephalic Locomotor Region Nuclei
              to Locomotor Control in the Freely Behaving Mouse",
  author   = "Josset, Nicolas and Roussel, Marie and Lemieux, Maxime and
              Lafrance-Zoubga, David and Rastqar, Ali and Bretzner, Frederic",
  abstract = "The mesencephalic locomotor region (MLR) has been initially
              identified as a supraspinal center capable of initiating and
              modulating locomotion. Whereas its functional contribution to
              locomotion has been widely documented throughout the phylogeny
              from the lamprey to humans, there is still debate about its exact
              organization. Combining kinematic and electrophysiological
              recordings in mouse genetics, our study reveals that
              glutamatergic neurons of the cuneiform nucleus initiate
              locomotion and induce running gaits, whereas glutamatergic and
              cholinergic neurons of the pedunculopontine nucleus modulate
              locomotor pattern and rhythm, contributing to slow-walking gaits.
              By initiating, modulating, and accelerating locomotion, our study
              identifies and characterizes distinct neuronal populations of
              this functional region important to locomotor command.",
  journal  = "Curr. Biol.",
  volume   =  28,
  number   =  6,
  pages    = "884--901.e3",
  month    =  mar,
  year     =  2018,
  keywords = "cuneiform nucleus; electrophysiology; glutamatergic and
              cholinergic neurons; kinematic analysis; locomotor command;
              locomotor pattern rhythm and gait; mesencephalic locomotor
              region; optogenetic tools; pedunculopontine nucleus;Locomotion",
  language = "en"
}

@ARTICLE{Kiehn2016-nj,
  title    = "Decoding the organization of spinal circuits that control
              locomotion",
  author   = "Kiehn, Ole",
  abstract = "Unravelling the functional operation of neuronal networks and
              linking cellular activity to specific behavioural outcomes are
              among the biggest challenges in neuroscience. In this broad field
              of research, substantial progress has been made in studies of the
              spinal networks that control locomotion. Through united efforts
              using electrophysiological and molecular genetic network
              approaches and behavioural studies in phylogenetically diverse
              experimental models, the organization of locomotor networks has
              begun to be decoded. The emergent themes from this research are
              that the locomotor networks have a modular organization with
              distinct transmitter and molecular codes and that their
              organization is reconfigured with changes to the speed of
              locomotion or changes in gait.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  17,
  number   =  4,
  pages    = "224--238",
  month    =  apr,
  year     =  2016,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Azim2014-xn,
  title     = "Skilled reaching relies on a V2a propriospinal internal copy
               circuit",
  author    = "Azim, Eiman and Jiang, Juan and Alstermark, Bror and Jessell,
               Thomas M",
  abstract  = "The precision of skilled forelimb movement has long been
               presumed to rely on rapid feedback corrections triggered by
               internally directed copies of outgoing motor commands, but the
               functional relevance of inferred internal copy circuits has
               remained unclear. One class of spinal interneurons implicated in
               the control of mammalian forelimb movement, cervical
               propriospinal neurons (PNs), has the potential to convey an
               internal copy of premotor signals through dual innervation of
               forelimb-innervating motor neurons and precerebellar neurons of
               the lateral reticular nucleus. Here we examine whether the PN
               internal copy pathway functions in the control of goal-directed
               reaching. In mice, PNs include a genetically accessible
               subpopulation of cervical V2a interneurons, and their targeted
               ablation perturbs reaching while leaving intact other elements
               of forelimb movement. Moreover, optogenetic activation of the PN
               internal copy branch recruits a rapid cerebellar feedback loop
               that modulates forelimb motor neuron activity and severely
               disrupts reaching kinematics. Our findings implicate V2a PNs as
               the focus of an internal copy pathway assigned to the rapid
               updating of motor output during reaching behaviour.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  508,
  number    =  7496,
  pages     = "357--363",
  month     =  apr,
  year      =  2014,
  language  = "en"
}

@ARTICLE{Reinhold2019-pr,
  title     = "Behavioral and neural correlates of hide-and-seek in rats",
  author    = "Reinhold, Annika Stefanie and Sanguinetti-Scheck, Juan Ignacio
               and Hartmann, Konstantin and Brecht, Michael",
  abstract  = "There is controversy regarding how widespread animal play
               behavior is and what its evolutionary function might be.
               Reinhold et al. demonstrated that rats can play hide-and-seek
               with a human. In the ``seek'' condition, rats learned to look
               for the hidden humans and kept seeking until they found them. In
               the ``hide'' condition, they learned to hide in one of several
               locations and waited there until being found. In both cases, the
               rats were rewarded by social interaction with the human. Rats
               vocalized when seeking and finding and were silent when hiding.
               Recordings in the medial prefrontal cortex detected neurons that
               were sensitive to the game structure. Science , this issue p.
               [1180][1] Evolutionary, cognitive, and neural underpinnings of
               mammalian play are not yet fully elucidated. We played
               hide-and-seek, an elaborate role-play game, with rats. We did
               not offer food rewards but engaged in playful interactions after
               finding or being found. Rats quickly learned the game and
               learned to alternate between hiding versus seeking roles. They
               guided seeking by vision and memories of past hiding locations
               and emitted game event--specific vocalizations. When hiding,
               rats vocalized infrequently and they preferred opaque over
               transparent hiding enclosures, a preference not observed during
               seeking. Neuronal recordings revealed intense prefrontal cortex
               activity that varied with game events and trial types (``hide''
               versus ``seek'') and might instruct role play. The elaborate
               cognitive capacities for hide-and-seek in rats suggest that this
               game might be evolutionarily old. [1]:
               /lookup/doi/10.1126/science.aax4705",
  journal   = "Science",
  publisher = "American Association for the Advancement of Science",
  volume    =  365,
  number    =  6458,
  pages     = "1180--1183",
  month     =  sep,
  year      =  2019,
  language  = "en"
}

@INCOLLECTION{May2006-kw,
  title     = "The mammalian superior colliculus: laminar structure and
               connections",
  booktitle = "Progress in Brain Research",
  author    = "May, Paul J",
  editor    = "B{\"u}ttner-Ennever, J A",
  abstract  = "The superior colliculus is a laminated midbrain structure that
               acts as one of the centers organizing gaze movements. This
               review will concentrate on sensory and motor inputs to the
               superior colliculus, on its internal circuitry, and on its
               connections with other brainstem gaze centers, as well as its
               extensive outputs to those structures with which it is
               reciprocally connected. This will be done in the context of its
               laminar arrangement. Specifically, the superficial layers
               receive direct retinal input, and are primarily visual sensory
               in nature. They project upon the visual thalamus and pretectum
               to influence visual perception. These visual layers also project
               upon the deeper layers, which are both multimodal, and premotor
               in nature. Thus, the deep layers receive input from both
               somatosensory and auditory sources, as well as from the basal
               ganglia and cerebellum. Sensory, association, and motor areas of
               cerebral cortex provide another major source of collicular
               input, particularly in more encephalized species. For example,
               visual sensory cortex terminates superficially, while the eye
               fields target the deeper layers. The deeper layers are
               themselves the source of a major projection by way of the
               predorsal bundle which contributes collicular target information
               to the brainstem structures containing gaze-related burst
               neurons, and the spinal cord and medullary reticular formation
               regions that produce head turning.",
  publisher = "Elsevier",
  volume    =  151,
  pages     = "321--378",
  month     =  jan,
  year      =  2006
}

@ARTICLE{Tovote2016-fr,
  title    = "Midbrain circuits for defensive behaviour",
  author   = "Tovote, Philip and Esposito, Maria Soledad and Botta, Paolo and
              Chaudun, Fabrice and Fadok, Jonathan P and Markovic, Milica and
              Wolff, Steffen B E and Ramakrishnan, Charu and Fenno, Lief and
              Deisseroth, Karl and Herry, Cyril and Arber, Silvia and
              L{\"u}thi, Andreas",
  abstract = "Survival in threatening situations depends on the selection and
              rapid execution of an appropriate active or passive defensive
              response, yet the underlying brain circuitry is not understood.
              Here we use circuit-based optogenetic, in vivo and in vitro
              electrophysiological, and neuroanatomical tracing methods to
              define midbrain periaqueductal grey circuits for specific
              defensive behaviours. We identify an inhibitory pathway from the
              central nucleus of the amygdala to the ventrolateral
              periaqueductal grey that produces freezing by disinhibition of
              ventrolateral periaqueductal grey excitatory outputs to pre-motor
              targets in the magnocellular nucleus of the medulla. In addition,
              we provide evidence for anatomical and functional interaction of
              this freezing pathway with long-range and local circuits
              mediating flight. Our data define the neuronal circuitry
              underlying the execution of freezing, an evolutionarily conserved
              defensive behaviour, which is expressed by many species including
              fish, rodents and primates. In humans, dysregulation of this
              'survival circuit' has been implicated in anxiety-related
              disorders.",
  journal  = "Nature",
  volume   =  534,
  number   =  7606,
  pages    = "206--212",
  month    =  jun,
  year     =  2016,
  language = "en"
}

@ARTICLE{Kim2017-mo,
  title    = "Integration of Descending Command Systems for the Generation of
              {Context-Specific} Locomotor Behaviors",
  author   = "Kim, Linda H and Sharma, Sandeep and Sharples, Simon A and Mayr,
              Kyle A and Kwok, Charlie H T and Whelan, Patrick J",
  abstract = "Over the past decade there has been a renaissance in our
              understanding of spinal cord circuits; new technologies are
              beginning to provide key insights into descending circuits which
              project onto spinal cord central pattern generators. By
              integrating work from both the locomotor and animal behavioral
              fields, we can now examine context-specific control of
              locomotion, with an emphasis on descending modulation arising
              from various regions of the brainstem. Here we examine approach
              and avoidance behaviors and the circuits that lead to the
              production and arrest of locomotion.",
  journal  = "Front. Neurosci.",
  volume   =  11,
  pages    = "581",
  month    =  oct,
  year     =  2017,
  keywords = "approach; aversion; descending; goal-directed; locomotor
              behavior; supraspinal",
  language = "en"
}

@ARTICLE{Capelli2017-hq,
  title    = "Locomotor speed control circuits in the caudal brainstem",
  author   = "Capelli, Paolo and Pivetta, Chiara and Soledad Esposito, Maria
              and Arber, Silvia",
  abstract = "Locomotion is a universal behaviour that provides animals with
              the ability to move between places. Classical experiments have
              used electrical microstimulation to identify brain regions that
              promote locomotion, but the identity of neurons that act as key
              intermediaries between higher motor planning centres and
              executive circuits in the spinal cord has remained controversial.
              Here we show that the mouse caudal brainstem encompasses
              functionally heterogeneous neuronal subpopulations that have
              differential effects on locomotion. These subpopulations are
              distinguishable by location, neurotransmitter identity and
              connectivity. Notably, glutamatergic neurons within the lateral
              paragigantocellular nucleus (LPGi), a small subregion in the
              caudal brainstem, are essential to support high-speed locomotion,
              and can positively tune locomotor speed through inputs from
              glutamatergic neurons of the upstream midbrain locomotor region.
              By contrast, glycinergic inhibitory neurons can induce different
              forms of behavioural arrest mapping onto distinct caudal
              brainstem regions. Anatomically, descending pathways of
              glutamatergic and glycinergic LPGi subpopulations communicate
              with distinct effector circuits in the spinal cord. Our results
              reveal that behaviourally opposing locomotor functions in the
              caudal brainstem were historically masked by the unexposed
              diversity of intermingled neuronal subpopulations. We demonstrate
              how specific brainstem neuron populations represent essential
              substrates to implement key parameters in the execution of motor
              programs.",
  journal  = "Nature",
  volume   =  551,
  number   =  7680,
  pages    = "373--377",
  month    =  nov,
  year     =  2017,
  keywords = "Locomotion",
  language = "en"
}

@INCOLLECTION{Knudsen2017-ji,
  title     = "1.21 - The Optic Tectum: A Structure Evolved for Stimulus
               Selection",
  booktitle = "Evolution of Nervous Systems (Second Edition)",
  author    = "Knudsen, E I and Schwarz, J S",
  editor    = "Kaas, Jon H",
  abstract  = "The core function of the optic tectum (OT) in all vertebrates is
               to collect information about the location and immediate
               relevance of stimuli in the environment and, based on this
               information, to compute the ``highest priority'' stimulus at
               each moment in time. The OT transmits the location of this
               stimulus to the forebrain to help direct spatial attention and,
               when appropriate, to the brain stem and spinal cord to guide
               immediate orienting or defensive behaviors. This chapter
               describes how a stimulus selection network in the midbrain
               generates the OT signal that identifies the location of the
               ``highest priority'' stimulus.",
  publisher = "Academic Press",
  pages     = "387--408",
  month     =  jan,
  year      =  2017,
  address   = "Oxford",
  keywords  = "Amphibians; Attention; Birds; Fish; Gamma oscillations; Gaze
               control; Isthmic nuclei; Mammals; Orienting response; Primates;
               Reptiles; Retinotectal; Selective attention; Superior
               colliculus; Visual pathways"
}

@UNPUBLISHED{Cregg2019-ah,
  title    = "Brainstem Neurons that Command {Left/Right} Locomotor Asymmetries",
  author   = "Cregg, Jared M and Leiras, Roberto and Montalant, Alexia and
              Wickersham, Ian R and Kiehn, Ole",
  abstract = "Descending command neurons instruct spinal networks to execute
              basic locomotor functions, such as which gait and what speed. The
              command functions for gait and speed are symmetric, implying that
              a separate unknown system directs asymmetric movements---the
              ability to move left or right. Here we report the discovery that
              Chx10-lineage reticulospinal neurons act to control the direction
              of locomotor movements in mammals. Chx10 neurons exhibit
              ipsilateral projection, and can decrease spinal limb-based
              locomotor activity ipsilaterally. This circuit mechanism acts as
              the basis for left or right locomotor movements in freely moving
              animals: selective unilateral activation of Chx10 neurons causes
              ipsilateral movements whereas inhibition causes contralateral
              movements. Spontaneous forward locomotion is thus transformed
              into an ipsilateral movement by braking locomotion on the
              ipsilateral side. We identify sensorimotor brain regions that
              project onto Chx10 reticulospinal neurons, and demonstrate that
              their unilateral activation can impart left/right directional
              commands. Together these data identify the descending motor
              system which commands left/right locomotor asymmetries in
              mammals.",
  journal  = "bioRxiv",
  pages    = "754812",
  month    =  sep,
  year     =  2019,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Comer2009-mh,
  title    = "Behavioral biology: inside the mind of proteus?",
  author   = "Comer, Christopher",
  abstract = "A new study of the escape behavior of the cockroach has found
              that its spatial variability is based on some underlying
              regularity. This constrained variability may maximise the
              effectiveness of the escape strategy.",
  journal  = "Curr. Biol.",
  volume   =  19,
  number   =  1,
  pages    = "R27--8",
  month    =  jan,
  year     =  2009,
  language = "en"
}

@ARTICLE{Arnott1999-vi,
  title    = "Escape trajectories of the brown shrimp crangon crangon, and a
              theoretical consideration of initial escape angles from predators",
  author   = "Arnott, S A and Neil, D M and Ansell, A D",
  abstract = "Tail-flip escape trajectories of the brown shrimp Crangon crangon
              have been investigated in response to a natural predator, the cod
              Gadus morhua, and an artificial stimulus. Shrimps escaped by
              rolling to their left or right during the initial tail-flip of a
              response, and thereafter swam on their side. As a result of the
              laterally directed first tail-flip, initial escape angles always
              lay between 75 degrees and 156 degrees with respect to the
              (pre-escape) longitudinal axis (anterior=0 degrees) of the
              shrimp. Symmetrical attacks from either head-on or tail-on
              produced escapes to the shrimp's left or right in equal
              proportions, although a contralateral bias did occur if the
              shrimp experienced a looming object from one side before a
              symmetrical attack was applied. Lateral attacks produced a
              significantly greater proportion of contralateral responses than
              ipsilateral ones. Empirical and theoretical analyses indicate
              that the initial escape direction is influenced by an interaction
              between the range of first tail-flip escape angles that the
              shrimp is capable of performing and the risk of being intercepted
              by a predator during the initial stage of an escape. Thus, the
              unpredictability ('protean behaviour') of the response may be
              affected by the conditions of the interaction. Subsequent
              tail-flips of an escape usually directed the response away from
              the stimulus, but sometimes escapes were instead steered to the
              side of the stimulus and then behind it. The probability of each
              type of escape occurring changed with attack direction. The
              elements of protean behaviour that have been identified in both
              the initial and subsequent stages of the escape may prevent
              predators from learning a fixed pattern of response, but a
              trade-off occurs when escape trajectories infringe upon zones of
              high capture risk.",
  journal  = "J. Exp. Biol.",
  volume   = "202 (Pt 2)",
  pages    = "193--209",
  month    =  jan,
  year     =  1999,
  language = "en"
}

@ARTICLE{Poucet2004-wh,
  title    = "Spatial navigation and hippocampal place cell firing: the problem
              of goal encoding",
  author   = "Poucet, B and Lenck-Santini, P P and Hok, V and Save, E and
              Banquet, J P and Gaussier, P and Muller, R U",
  abstract = "Place cells are hippocampal neurons whose discharge is strongly
              related to a rat's location in the environment. The existence of
              such cells, combined with the reliable impairments seen in
              spatial tasks after hippocampal damage, has led to the proposal
              that place cells form part of an integrated neural system
              dedicated to spatial navigation. This hypothesis is supported by
              the strong relationships between place cell activity and spatial
              problem solving, which indicate that the place cell
              representation must be both functional and in register with the
              surroundings for the animal to perform correctly in spatial
              tasks. The place cell system nevertheless requires other
              essential elements to be competent, such as a component that
              specifies the overall goal of the animal and computes the path
              required to take the rat from its current location to the goal.
              Here, we propose a model of the neural network responsible for
              spatial navigation that includes goal coding and path selection.
              In this model, the hippocampal formation allows for place
              recognition, and stores the set of places that can be accessed
              from each position in the environment. The prefrontal cortex is
              responsible for encoding goal location and for route planning.
              The nucleus accumbens translates paths in neural space into
              appropriate locomotor activity that moves the animal towards the
              goal in real space. The complete model assumes that the
              hippocampal output to nucleus accumbens and prefrontal cortex
              provides information for generating solutions to spatial
              problems. In support of this model, we finally present
              preliminary evidence that the goal representation necessary for
              path planning might be encoded in the prelimbic/infralimbic
              region of the medial prefrontal cortex.",
  journal  = "Rev. Neurosci.",
  volume   =  15,
  number   =  2,
  pages    = "89--107",
  year     =  2004,
  language = "en"
}

@ARTICLE{Alyan1994-ev,
  title    = "Short-range homing in the house mouse, Mus musculus: stages in
              the learning of directions",
  author   = "Alyan, Sofyan and Jander, Rudolf",
  abstract = "Abstract. Female house mice readily learn to retrieve their pups
              50 cm from the centre of an open arena and take them to their
              nest outside the arena's periphery. Experimental manipulation to
              reveal the spatial-orientation constituents of this behaviour
              disclosed thus submechanisms. Guided orientation, the direct
              response to objects. Path integration, the continuous monitoring
              of spatial displacements combined with computation of the
              locomotor vector to the starting point of the path. Landmark
              navigation, the movement by means of distal visual cues toward a
              goal not directly perceived. Learning to home passes through
              three stages. First, the exploring mouse is directly guided to
              objects of interest. Second, the homing mouse adds path
              integration; that is, it keeps a running, integrated spatial
              record derived from locomotion. Finally (circumstances
              permitting) the homing mouse links path integration with spatial
              references to distal visual landmarks. Sparse comparative
              evidence from other species of rodents suggests that such a
              system of short-range topographical orientation is universal
              among rodents.",
  journal  = "Anim. Behav.",
  volume   =  48,
  number   =  2,
  pages    = "285--298",
  month    =  aug,
  year     =  1994
}

@ARTICLE{Ito2015-ld,
  title    = "A prefrontal-thalamo-hippocampal circuit for goal-directed
              spatial navigation",
  author   = "Ito, Hiroshi T and Zhang, Sheng-Jia and Witter, Menno P and
              Moser, Edvard I and Moser, May-Britt",
  abstract = "Spatial navigation requires information about the relationship
              between current and future positions. The activity of hippocampal
              neurons appears to reflect such a relationship, representing not
              only instantaneous position but also the path towards a goal
              location. However, how the hippocampus obtains information about
              goal direction is poorly understood. Here we report a
              prefrontal-thalamic neural circuit that is required for
              hippocampal representation of routes or trajectories through the
              environment. Trajectory-dependent firing was observed in medial
              prefrontal cortex, the nucleus reuniens of the thalamus, and the
              CA1 region of the hippocampus in rats. Lesioning or optogenetic
              silencing of the nucleus reuniens substantially reduced
              trajectory-dependent CA1 firing. Trajectory-dependent activity
              was almost absent in CA3, which does not receive nucleus reuniens
              input. The data suggest that projections from medial prefrontal
              cortex, via the nucleus reuniens, are crucial for representation
              of the future path during goal-directed behaviour and point to
              the thalamus as a key node in networks for long-range
              communication between cortical regions involved in navigation.",
  journal  = "Nature",
  volume   =  522,
  number   =  7554,
  pages    = "50--55",
  month    =  jun,
  year     =  2015,
  language = "en"
}

@ARTICLE{Vedder2017-qz,
  title    = "Retrosplenial Cortical Neurons Encode Navigational Cues,
              Trajectories and Reward Locations During Goal Directed Navigation",
  author   = "Vedder, Lindsey C and Miller, Adam M P and Harrison, Marc B and
              Smith, David M",
  abstract = "The retrosplenial cortex (RSC) plays an important role in memory
              and spatial navigation. It shares functional similarities with
              the hippocampus, including the presence of place fields and
              lesion-induced impairments in spatial navigation, and the RSC is
              an important source of visual-spatial input to the hippocampus.
              Recently, the RSC has been the target of intense scrutiny among
              investigators of human memory and navigation. fMRI and lesion
              data suggest an RSC role in the ability to use landmarks to
              navigate to goal locations. However, no direct neurophysiological
              evidence of encoding navigational cues has been reported so the
              specific RSC contribution to spatial cognition has been
              uncertain. To examine this, we trained rats on a T-maze task in
              which the reward location was explicitly cued by a flashing light
              and we recorded RSC neurons as the rats learned. We found that
              RSC neurons rapidly encoded the light cue. Additionally, RSC
              neurons encoded the reward and its location, and they showed
              distinct firing patterns along the left and right trajectories to
              the goal. These responses may provide key information for
              goal-directed navigation, and the loss of these signals may
              underlie navigational impairments in subjects with RSC damage.",
  journal  = "Cereb. Cortex",
  volume   =  27,
  number   =  7,
  pages    = "3713--3723",
  month    =  jul,
  year     =  2017,
  keywords = "cingulate cortex; landmark; learning and memory; visual cue",
  language = "en"
}

@ARTICLE{Feierstein2006-hs,
  title    = "Representation of spatial goals in rat orbitofrontal cortex",
  author   = "Feierstein, Claudia E and Quirk, Michael C and Uchida, Naoshige
              and Sosulski, Dara L and Mainen, Zachary F",
  abstract = "The orbitofrontal cortex (OFC) is thought to participate in
              making and evaluating goal-directed decisions. In rodents,
              spatial navigation is a major mode of goal-directed behavior, and
              anatomical and lesion studies implicate the OFC in spatial
              processing, but there is little direct evidence for coding of
              spatial or motor variables. Here, we recorded from ventrolateral
              and lateral OFC in an odor-cued two-alternative choice task
              requiring orientation and approach to spatial goal ports. In this
              context, over half of OFC neurons encoded choice direction or
              goal port location. A subset of neurons was jointly selective for
              the trial outcome and port location, information useful for the
              selection or evaluation of spatial goals. These observations show
              that the rodent OFC not only encodes information relating to
              general motivational significance, as shown previously, but also
              encodes spatiomotor variables needed to define specific
              behavioral goals and the locomotor actions required to attain
              them.",
  journal  = "Neuron",
  volume   =  51,
  number   =  4,
  pages    = "495--507",
  month    =  aug,
  year     =  2006,
  language = "en"
}

@ARTICLE{Domenici2008-so,
  title    = "Cockroaches keep predators guessing by using preferred escape
              trajectories",
  author   = "Domenici, Paolo and Booth, David and Blagburn, Jonathan M and
              Bacon, Jonathan P",
  abstract = "Antipredator behavior is vital for most animals and calls for
              accurate timing and swift motion. Whereas fast reaction times [1]
              and predictable, context-dependent escape-initiation distances
              [2] are common features of most escape systems, previous work has
              highlighted the need for unpredictability in escape directions,
              in order to prevent predators from learning a repeated, fixed
              pattern [3-5]. Ultimate unpredictability would result from random
              escape trajectories. Although this strategy would deny any
              predictive power to the predator, it would also result in some
              escape trajectories toward the threat. Previous work has shown
              that escape trajectories are in fact generally directed away from
              the threat, although with a high variability [5-8]. However, the
              rules governing this variability are largely unknown. Here, we
              demonstrate that individual cockroaches (Periplaneta americana, a
              much-studied model prey species [9-14]) keep each escape
              unpredictable by running along one of a set of preferred
              trajectories at fixed angles from the direction of the
              threatening stimulus. These results provide a new paradigm for
              understanding the behavioral strategies for escape responses,
              underscoring the need to revisit the neural mechanisms
              controlling escape directions in the cockroach and similar animal
              models, and the evolutionary forces driving unpredictable, or
              ``protean''[3], antipredator behavior.",
  journal  = "Curr. Biol.",
  volume   =  18,
  number   =  22,
  pages    = "1792--1796",
  month    =  nov,
  year     =  2008,
  language = "en"
}

@ARTICLE{Moore2017-ge,
  title    = "Unpredictability of escape trajectory explains predator evasion
              ability and microhabitat preference of desert rodents",
  author   = "Moore, Talia Y and Cooper, Kimberly L and Biewener, Andrew A and
              Vasudevan, Ramanarayan",
  abstract = "Mechanistically linking movement behaviors and ecology is key to
              understanding the adaptive evolution of locomotion. Predator
              evasion, a behavior that enhances fitness, may depend upon short
              bursts or complex patterns of locomotion. However, such movements
              are poorly characterized by existing biomechanical metrics. We
              present methods based on the entropy measure of randomness from
              Information Theory to quantitatively characterize the
              unpredictability of non-steady-state locomotion. We then apply
              the method by examining sympatric rodent species whose escape
              trajectories differ in dimensionality. Unlike the speed-regulated
              gait use of cursorial animals to enhance locomotor economy,
              bipedal jerboa (family Dipodidae) gait transitions likely enhance
              maneuverability. In field-based observations, jerboa trajectories
              are significantly less predictable than those of quadrupedal
              rodents, likely increasing predator evasion ability. Consistent
              with this hypothesis, jerboas exhibit lower anxiety in open
              fields than quadrupedal rodents, a behavior that varies inversely
              with predator evasion ability. Our unpredictability metric
              expands the scope of quantitative biomechanical studies to
              include non-steady-state locomotion in a variety of evolutionary
              and ecologically significant contexts.Biomechanical understanding
              of animal gait and maneuverability has primarily been limited to
              species with more predictable, steady-state movement patterns.
              Here, the authors develop a method to quantify movement
              predictability, and apply the method to study escape-related
              movement in several species of desert rodents.",
  journal  = "Nat. Commun.",
  volume   =  8,
  number   =  1,
  pages    = "440",
  month    =  sep,
  year     =  2017,
  language = "en"
}

@ARTICLE{Card2012-fz,
  title    = "Escape behaviors in insects",
  author   = "Card, Gwyneth M",
  abstract = "Escape behaviors are, by necessity, fast and robust, making them
              excellent systems with which to study the neural basis of
              behavior. This is especially true in insects, which have
              comparatively tractable nervous systems and members who are
              amenable to manipulation with genetic tools. Recent technical
              developments in high-speed video reveal that, despite their short
              duration, insect escape behaviors are more complex than
              previously appreciated. For example, before initiating an escape
              jump, a fly performs sophisticated posture and stimulus-dependent
              preparatory leg movements that enable it to jump away from a
              looming threat. This newfound flexibility raises the question of
              how the nervous system generates a behavior that is both rapid
              and flexible. Recordings from the cricket nervous system suggest
              that synchrony between the activity of specific interneuron pairs
              may provide a rapid cue for the cricket to detect the direction
              of an approaching predator and thus which direction it should
              run. Technical advances make possible wireless recording from
              neurons while locusts escape from a looming threat, enabling, for
              the first time, a direct correlation between the activity of
              multiple neurons and the time-course of an insect escape
              behavior.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  2,
  pages    = "180--186",
  month    =  apr,
  year     =  2012,
  language = "en"
}

@INCOLLECTION{Balakrishnan2014-zj,
  title     = "Escape Trajectory",
  booktitle = "Wiley {StatsRef}: Statistics Reference Online",
  editor    = "Balakrishnan, N and Colton, Theodore and Everitt, Brian and
               Piegorsch, Walter and Ruggeri, Fabrizio and Teugels, Jozef L",
  abstract  = "Abstract Escape responses consist of sudden accelerations as
               reactions to threatening stimuli and are present in most animals
               as a means of avoiding predation. Escape responses are currently
               receiving increased attention as valuable models for animal
               behavior, ecology, and neurobiology. The path along which an
               animal moves during an escape response (its escape trajectory)
               has attracted the interest of ecologists and behaviorists in
               relation to its functional role in predator?prey interactions.
               Escape trajectories (ETs) as considered in this article refer to
               the initial prey response to a predator's attack. Such a
               trajectory should be measured at the end of the main rotational
               motion present during the escape response, which usually
               corresponds to a specific kinematic stage of the animal's
               locomotion. Beyond this stage, prey may continue escaping along
               a zigzag path, especially if predators follow up their attack
               with a chase.",
  publisher = "John Wiley \& Sons, Ltd",
  volume    =  200,
  pages     = "1",
  month     =  apr,
  year      =  2014,
  address   = "Chichester, UK"
}

@ARTICLE{Domenici2011-op,
  title    = "Animal escapology {II}: escape trajectory case studies",
  author   = "Domenici, Paolo and Blagburn, Jonathan M and Bacon, Jonathan P",
  abstract = "Escape trajectories (ETs; measured as the angle relative to the
              direction of the threat) have been studied in many taxa using a
              variety of methodologies and definitions. Here, we provide a
              review of methodological issues followed by a survey of ET
              studies across animal taxa, including insects, crustaceans,
              molluscs, lizards, fish, amphibians, birds and mammals.
              Variability in ETs is examined in terms of ecological
              significance and morpho-physiological constraints. The survey
              shows that certain escape strategies (single ETs and highly
              variable ETs within a limited angular sector) are found in most
              taxa reviewed here, suggesting that at least some of these ET
              distributions are the result of convergent evolution. High
              variability in ETs is found to be associated with multiple
              preferred trajectories in species from all taxa, and is suggested
              to provide unpredictability in the escape response. Random ETs
              are relatively rare and may be related to constraints in the
              manoeuvrability of the prey. Similarly, reports of the effect of
              refuges in the immediate environment are relatively uncommon, and
              mainly confined to lizards and mammals. This may be related to
              the fact that work on ETs carried out in laboratory settings has
              rarely provided shelters. Although there are a relatively large
              number of examples in the literature that suggest trends in the
              distribution of ETs, our understanding of animal escape
              strategies would benefit from a standardization of the analytical
              approach in the study of ETs, using circular statistics and
              related tests, in addition to the generation of large data sets.",
  journal  = "J. Exp. Biol.",
  volume   =  214,
  number   = "Pt 15",
  pages    = "2474--2494",
  month    =  aug,
  year     =  2011,
  language = "en"
}

@ARTICLE{Humphries1970-rt,
  title    = "Protean defence by prey animals",
  author   = "Humphries, D A and Driver, P M",
  abstract = "Attention is drawn to the widespread occurrence ofprotean
              phenomena, in which the appearance and behaviour of prey animals
              are rendered variable and irregular, as a weapon in the
              biological arms race between predators and their prey. Protean
              behaviour is defined as that behaviour which is sufficiently
              unsystematic to prevent a reactor predicting in detail the
              position or actions of the actor.Single prey animals frequently
              flee from a predator in an irregular manner, zigzagging,
              spinning, looping, or bouncing. Thissingle erratic display occurs
              widely in the Animal Kingdom, and may also be utilised in
              everyday movements of potential prey as insurance against
              possible attack. Examples are given.In a group of prey animals
              the protean aspect of escape is enhanced by the effect of
              numbers. In scatter reactions the effect is of multiple choice
              and of the simultaneous operation of several single erratics. In
              mobbing displays there are also successive changes in the actors'
              behavioural role. In protean deterrence the shuffling of
              individuals within a tightly packed group prevents a predator
              from singling one out for attack.In many species the confusing
              effect of changes in movement and behavioural role is enhanced by
              rapid changes in appearance, particularly colour.It is suggested
              that those prey individuals which employ escape patterns
              unfamiliar to the predator will tend to be at a selective
              advantage. During phylogeny this is likely to lead to
              intra-specific and inter-specific increase in the number and
              diversity of escape behaviours. Apostatic polymorphism is seen as
              a special case of protean variation within populations.There is
              evidence that protean displays operate by arousing neurological
              conflict, thereby delaying the predator's reactions and reducing
              the effectiveness of predatory mechanisms. Also they insure
              against learned countermeasures by incorporating irregularities
              as a basic principle. It is stressed that the irregular
              variability of protean displays is not accidental but has been
              selected for in phylogeny. A number of poorly understood
              behavioural aspects of the ecology of predator-prey relationships
              are thus united in a single theory.",
  journal  = "Oecologia",
  volume   =  5,
  number   =  4,
  pages    = "285--302",
  month    =  dec,
  year     =  1970,
  language = "en"
}

@ARTICLE{Card2008-kq,
  title    = "Visually mediated motor planning in the escape response of
              Drosophila",
  author   = "Card, Gwyneth and Dickinson, Michael H",
  abstract = "A key feature of reactive behaviors is the ability to spatially
              localize a salient stimulus and act accordingly. Such
              sensory-motor transformations must be particularly fast and well
              tuned in escape behaviors, in which both the speed and accuracy
              of the evasive response determine whether an animal successfully
              avoids predation [1]. We studied the escape behavior of the fruit
              fly, Drosophila, and found that flies can use visual information
              to plan a jump directly away from a looming threat. This is
              surprising, given the architecture of the pathway thought to
              mediate escape [2, 3]. Using high-speed videography, we found
              that approximately 200 ms before takeoff, flies begin a series of
              postural adjustments that determine the direction of their
              escape. These movements position their center of mass so that leg
              extension will push them away from the expanding visual stimulus.
              These preflight movements are not the result of a simple
              feed-forward motor program because their magnitude and direction
              depend on the flies' initial postural state. Furthermore, flies
              plan a takeoff direction even in instances when they choose not
              to jump. This sophisticated motor program is evidence for a form
              of rapid, visually mediated motor planning in a genetically
              accessible model organism.",
  journal  = "Curr. Biol.",
  volume   =  18,
  number   =  17,
  pages    = "1300--1307",
  month    =  sep,
  year     =  2008,
  language = "en"
}

@ARTICLE{Santer2005-km,
  title    = "Motor activity and trajectory control during escape jumping in
              the locust Locusta migratoria",
  author   = "Santer, Roger D and Yamawaki, Yoshifumi and Rind, F Claire and
              Simmons, Peter J",
  abstract = "We investigated the escape jumps that locusts produce in response
              to approaching objects. Hindleg muscular activity during an
              escape jump is similar to that during a defensive kick. Locusts
              can direct their escape jumps up to 50 degrees either side of the
              direction of their long axis at the time of hindleg flexion,
              allowing them to consistently jump away from the side towards
              which an object is approaching. Variation in jump trajectory is
              achieved by rolling and yawing movements of the body that are
              controlled by the fore- and mesothoracic legs. During hindleg
              flexion, a locust flexes the foreleg ipsilateral to its eventual
              jump trajectory and then extends the contralateral foreleg. These
              foreleg movements continue throughout co-contraction of the
              hindleg tibial muscles, pivoting the locust's long axis towards
              its eventual jump trajectory. However, there are no bilateral
              differences in the motor programs of the left and right hindlegs
              that correlate with jump trajectory. Foreleg movements enable a
              locust to control its jump trajectory independent of the hindleg
              motor program, allowing a decision on jump trajectory to be made
              after the hindlegs have been cocked in preparation for a jump.",
  journal  = "J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol.",
  volume   =  191,
  number   =  10,
  pages    = "965--975",
  month    =  oct,
  year     =  2005,
  language = "en"
}

@ARTICLE{Juechems2019-kv,
  title    = "Where Does Value Come From?",
  author   = "Juechems, Keno and Summerfield, Christopher",
  abstract = "The computational framework of reinforcement learning (RL) has
              allowed us to both understand biological brains and build
              successful artificial agents. However, in this opinion, we
              highlight open challenges for RL as a model of animal behaviour
              in natural environments. We ask how the external reward function
              is designed for biological systems, and how we can account for
              the context sensitivity of valuation. We summarise both old and
              new theories proposing that animals track current and desired
              internal states and seek to minimise the distance to a goal
              across multiple value dimensions. We suggest that this framework
              readily accounts for canonical phenomena observed in the fields
              of psychology, behavioural ecology, and economics, and recent
              findings from brain-imaging studies of value-guided
              decision-making.",
  journal  = "Trends Cogn. Sci.",
  month    =  sep,
  year     =  2019,
  keywords = "goal-directed decision-making; homeostasis; medial prefrontal
              cortex; reinforcement learning; reward; value",
  language = "en"
}

@ARTICLE{Fanselow2018-bx,
  title    = "The Role of Learning in Threat Imminence and Defensive Behaviors",
  author   = "Fanselow, Michael S",
  abstract = "Life threatening situations as urgent as defending against a
              predator precludes the use of slow trial and error strategies.
              Natural selection has led to the evolution of a behavioral system
              that has 3 critical elements. 1) When it is activated it limits
              the behaviors available to the organism to a set of prewired
              responses that have proven over phylogeny to be effective at
              defense. 2) A rapid learning system, called Pavlovian fear
              conditioning, that has the ability to immediately identify
              threats and promote prewired defensive behaviors. 3) That
              learning system has the ability to integrate several
              informational dimensions to determine threat imminence and this
              allows the organism to match the most effective defensive
              behavior to the current situation. The adaptive significance of
              conscious experiential states is also considered.",
  journal  = "Curr Opin Behav Sci",
  volume   =  24,
  pages    = "44--49",
  month    =  dec,
  year     =  2018,
  keywords = "Anxiety; Defensive Behavior; Fear; Fear Conditioning; Innate
              Fear; Panic; Predatory Imminence; Threat Imminence; amygdala;
              avoidance; consciousness; freezing; selective association",
  language = "en"
}

@ARTICLE{Dunn2016-xl,
  title     = "Brain-wide mapping of neural activity controlling zebrafish
               exploratory locomotion",
  author    = "Dunn, Timothy W and Mu, Yu and Narayan, Sujatha and Randlett,
               Owen and Naumann, Eva A and Yang, Chao-Tsung and Schier,
               Alexander F and Freeman, Jeremy and Engert, Florian and Ahrens,
               Misha B",
  abstract  = "In the absence of salient sensory cues to guide behavior,
               animals must still execute sequences of motor actions in order
               to forage and explore. How such successive motor actions are
               coordinated to form global locomotion trajectories is unknown.
               We mapped the structure of larval zebrafish swim trajectories in
               homogeneous environments and found that trajectories were
               characterized by alternating sequences of repeated turns to the
               left and to the right. Using whole-brain light-sheet imaging, we
               identified activity relating to the behavior in specific neural
               populations that we termed the anterior rhombencephalic turning
               region (ARTR). ARTR perturbations biased swim direction and
               reduced the dependence of turn direction on turn history,
               indicating that the ARTR is part of a network generating the
               temporal correlations in turn direction. We also find suggestive
               evidence for ARTR mutual inhibition and ARTR projections to
               premotor neurons. Finally, simulations suggest the observed turn
               sequences may underlie efficient exploration of local
               environments.",
  journal   = "Elife",
  publisher = "cdn.elifesciences.org",
  volume    =  5,
  pages     = "e12741",
  month     =  mar,
  year      =  2016,
  keywords  = "exploration strategies; higher-order motor control; larval
               zebrafish; neural basis of behavior; neuroscience; spontaneous
               brain activity; whole-brain functional imaging; zebrafish",
  language  = "en"
}

@UNPUBLISHED{Bolton2019-kt,
  title    = "Elements of a stochastic {3D} prediction engine in larval
              zebrafish prey capture",
  author   = "Bolton, Andrew D and Haesemeyer, Martin and Jordi, Josua and
              Schaechtle, Ulrich and Saad, Feras and Mansinghka, Vikash K and
              Tenenbaum, Joshua B and Engert, Florian",
  abstract = "Many predatory animals rely on accurate sensory perception,
              predictive models, and precise pursuits to catch moving prey.
              Larval zebrafish intercept paramecia during their hunting
              behavior, but the precise trajectories of their prey have never
              been recorded in relation to fish movements in three dimensions.
              As a means of uncovering what a simple organism understands about
              its physical world, we have constructed a 3D-imaging setup to
              simultaneously record the behavior of larval zebrafish, as well
              as their moving prey, during hunting. We show that zebrafish
              robustly transform their 3D displacement and rotation according
              to the position of their prey while modulating both of these
              variables depending on prey velocity. This is true for both
              azimuth and altitude, but particulars of the hunting algorithm in
              the two planes are slightly different to accommodate an
              asymmetric strike zone. We show that the combination of position
              and velocity perception provides the fish with a preferred future
              positional estimate, indicating an ability to project
              trajectories forward in time. Using computational models, we show
              that this projection ability is critical for prey capture
              efficiency and success. Further, we demonstrate that fish use a
              graded stochasticity algorithm where the variance around the mean
              result of each swim scales with distance from the target.
              Notably, this strategy provides the animal with a considerable
              improvement over equivalent noise-free strategies. In sum, our
              quantitative and probabilistic modeling shows that zebrafish are
              equipped with a stochastic recursive algorithm that embodies an
              implicit predictive model of the world. This algorithm, built by
              a simple set of behavioral rules, allows the fish to optimize
              their hunting strategy in a naturalistic three-dimensional
              environment.",
  journal  = "bioRxiv",
  pages    = "755777",
  month    =  sep,
  year     =  2019,
  language = "en"
}

@ARTICLE{Neftci2019-pw,
  title    = "Reinforcement learning in artificial and biological systems",
  author   = "Neftci, Emre O and Averbeck, Bruno B",
  abstract = "There is and has been a fruitful flow of concepts and ideas
              between studies of learning in biological and artificial systems.
              Much early work that led to the development of reinforcement
              learning (RL) algorithms for artificial systems was inspired by
              learning rules first developed in biology by Bush and Mosteller,
              and Rescorla and Wagner. More recently, temporal-difference RL,
              developed for learning in artificial agents, has provided a
              foundational framework for interpreting the activity of dopamine
              neurons. In this Review, we describe state-of-the-art work on RL
              in biological and artificial agents. We focus on points of
              contact between these disciplines and identify areas where future
              research can benefit from information flow between these fields.
              Most work in biological systems has focused on simple learning
              problems, often embedded in dynamic environments where
              flexibility and ongoing learning are important, similar to
              real-world learning problems faced by biological systems. In
              contrast, most work in artificial agents has focused on learning
              a single complex problem in a static environment. Moving forward,
              work in each field will benefit from a flow of ideas that
              represent the strengths within each discipline.",
  journal  = "Nature Machine Intelligence",
  volume   =  1,
  number   =  3,
  pages    = "133--143",
  month    =  mar,
  year     =  2019
}

@BOOK{Burkhardt2005-ej,
  title     = "Patterns of Behavior: Konrad Lorenz, Niko Tinbergen, and the
               Founding of Ethology",
  author    = "Burkhardt, Richard W",
  abstract  = "It is hard to imagine, by their very name, the life sciences not
               involving the study of living things, but until the twentieth
               century much of what was known in the field was based primarily
               on specimens that had long before taken their last breaths. Only
               in the last century has ethology---the study of animal
               behavior---emerged as a major field of the life sciences. In
               Patterns of Behavior, Richard W. Burkhardt Jr. traces the
               scientific theories, practices, subjects, and settings integral
               to the construction of a discipline pivotal to our understanding
               of the diversity of life. Central to this tale are Konrad Lorenz
               and Niko Tinbergen, 1973 Nobel laureates whose research helped
               legitimize the field of ethology and bring international
               attention to the culture of behavioral research. Demonstrating
               how matters of practice, politics, and place all shaped
               ``ethology's ecologies,'' Burkhardt's book offers a sensitive
               reading of the complex interplay of the field's celebrated
               pioneers and a richly textured reconstruction of ethology's
               transformation from a quiet backwater of natural history to the
               forefront of the biological sciences. Winner of the 2006 Pfizer
               Awad from the History of Science Society",
  publisher = "University of Chicago Press",
  month     =  mar,
  year      =  2005,
  language  = "en"
}


@ARTICLE{Swartz2006-xa,
  title     = "Inverse Decision Theory",
  author    = "Swartz, Richard J and Cox, Dennis D and Cantor, Scott B and
               Davies, Kalatu and Follen, Michele",
  abstract  = "Identifying an optimal decision rule using Bayesian decision
               theory requires priors, likelihoods, and losses. In many medical
               settings, we can develop priors and likelihoods, but specifying
               losses can be difficult, especially when considering both
               patient outcomes and economic costs. If there is a widely
               accepted treatment strategy, then we can consider the inverse
               problem and find a region in the space of losses where the
               procedure is optimal. We call this approach inverse decision
               theory (IDT). We apply IDT to the standard of care for diagnosis
               and treatment of precancerous lesions of the cervix, and
               consider an alternative procedure that has been proposed. We use
               a Bayesian approach to estimate the probabilities associated
               with the diagnostic tests and make inferences about the region
               in loss space where these medical procedures are optimal. In
               particular, we find evidence supporting the current standard of
               care.",
  journal   = "J. Am. Stat. Assoc.",
  publisher = "Taylor \& Francis",
  volume    =  101,
  number    =  473,
  pages     = "1--8",
  month     =  mar,
  year      =  2006
}

@ARTICLE{Richards1974-wh,
  title     = "The Innate and the Learned: The Evolution of Konrad Lorenz's
               Theory of Instinct",
  author    = "Richards, Robert J",
  journal   = "Philos. Soc. Sci.",
  publisher = "SAGE Publications Inc",
  volume    =  4,
  number    = "2-3",
  pages     = "111--133",
  month     =  jun,
  year      =  1974
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@BOOK{Belew2018-rz,
  title     = "Adaptive individuals in evolving populations: models and
               algorithms",
  author    = "Belew, Richard K",
  abstract  = "A Model of Individual Adaptive Behavior in a Fluctuating
               Environment Individual behavioral strategies that use
               conditional probabilities for future environments and
               information about past environments are studied. The
               environments are random and Markovian. The individual uses the
               available information to prepare for the next environmental
               state in order to increase its fitness. The fitness depends on
               the discrepancy between the realized environment and that for
               which the individual is prepared. Additive and multiplicative …",
  publisher = "Routledge",
  year      =  2018
}

@ARTICLE{Turney1996-uv,
  title     = "Evolution, Learning, and Instinct: 100 Years of the Baldwin
               Effect",
  author    = "Turney, Peter and Whitley, Darrell and Anderson, Russell W",
  journal   = "Evol. Comput.",
  publisher = "MIT Press",
  volume    =  4,
  number    =  3,
  pages     = "iv--viii",
  month     =  sep,
  year      =  1996
}


@ARTICLE{Zador2019-wh,
  title     = "A critique of pure learning and what artificial neural networks
               can learn from animal brains",
  author    = "Zador, Anthony M",
  abstract  = "Artificial neural networks (ANNs) have undergone a revolution,
               catalyzed by better supervised learning algorithms. However, in
               stark contrast to young animals (including humans), training
               such networks requires enormous numbers of labeled examples,
               leading to the belief that animals must rely instead mainly on
               unsupervised learning. Here we argue that most animal behavior
               is not the result of clever learning algorithms-supervised or
               unsupervised-but is encoded in the genome. Specifically, animals
               are born with highly structured brain connectivity, which
               enables them to learn very rapidly. Because the wiring diagram
               is far too complex to be specified explicitly in the genome, it
               must be compressed through a ``genomic bottleneck''. The genomic
               bottleneck suggests a path toward ANNs capable of rapid
               learning.",
  journal   = "Nat. Commun.",
  publisher = "nature.com",
  volume    =  10,
  number    =  1,
  pages     = "3770",
  month     =  aug,
  year      =  2019,
  language  = "en"
}

@BOOK{Hebb2005-wq,
  title     = "The Organization of Behavior: A Neuropsychological Theory",
  author    = "Hebb, D O",
  abstract  = "Since its publication in 1949, D.O. Hebb's, The Organization of
               Behavior has been one of the most influential books in the
               fields of psychology and neuroscience. However, the original
               edition has been unavailable since 1966, ensuring that Hebb's
               comment that a classic normally means ``cited but not read'' is
               true in his case. This new edition rectifies a long-standing
               problem for behavioral neuroscientists--the inability to obtain
               one of the most cited publications in the field. The
               Organization of Behavior played a significant part in
               stimulating the investigation of the neural foundations of
               behavior and continues to be inspiring because it provides a
               general framework for relating behavior to synaptic organization
               through the dynamics of neural networks. D.O. Hebb was also the
               first to examine the mechanisms by which environment and
               experience can influence brain structure and function, and his
               ideas formed the basis for work on enriched environments as
               stimulants for behavioral development. References to Hebb, the
               Hebbian cell assembly, the Hebb synapse, and the Hebb rule
               increase each year. These forceful ideas of 1949 are now applied
               in engineering, robotics, and computer science, as well as
               neurophysiology, neuroscience, and psychology--a tribute to
               Hebb's foresight in developing a foundational neuropsychological
               theory of the organization of behavior.",
  publisher = "Psychology Press",
  month     =  apr,
  year      =  2005,
  language  = "en"
}


@BOOK{Kirk2012-ji,
  title     = "Optimal Control Theory: An Introduction",
  author    = "Kirk, Donald E",
  abstract  = "Optimal control theory is the science of maximizing the returns
               from and minimizing the costs of the operation of physical,
               social, and economic processes. Geared toward upper-level
               undergraduates, this text introduces three aspects of optimal
               control theory: dynamic programming, Pontryagin's minimum
               principle, and numerical techniques for trajectory
               optimization.Chapters 1 and 2 focus on describing systems and
               evaluating their performances. Chapter 3 deals with dynamic
               programming. The calculus of variations and Pontryagin's minimum
               principle are the subjects of chapters 4 and 5, and chapter 6
               examines iterative numerical techniques for finding optimal
               controls and trajectories. Numerous problems, intended to
               introduce additional topics as well as to illustrate basic
               concepts, appear throughout the text.",
  publisher = "Courier Corporation",
  month     =  apr,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Vicente2019-kq,
  title         = "The many faces of deep learning",
  author        = "Vicente, Raul",
  abstract      = "Deep learning has sparked a network of mutual interactions
                   between different disciplines and AI. Naturally, each
                   discipline focuses and interprets the workings of deep
                   learning in different ways. This diversity of perspectives
                   on deep learning, from neuroscience to statistical physics,
                   is a rich source of inspiration that fuels novel
                   developments in the theory and applications of machine
                   learning. In this perspective, we collect and synthesize
                   different intuitions scattered across several communities as
                   for how deep learning works. In particular, we will briefly
                   discuss the different perspectives that disciplines across
                   mathematics, physics, computation, and neuroscience take on
                   how deep learning does its tricks. Our discussion on each
                   perspective is necessarily shallow due to the multiple views
                   that had to be covered. The deepness in this case should
                   come from putting all these faces of deep learning together
                   in the reader's mind, so that one can look at the same
                   problem from different angles.",
  month         =  aug,
  year          =  2019,
  archivePrefix = "arXiv",
  primaryClass  = "cs.LG",
  eprint        = "1908.10206"
}

@ARTICLE{Stephens2008-um,
  title    = "Decision ecology: foraging and the ecology of animal decision
              making",
  author   = "Stephens, David W",
  abstract = "In this article, I review the approach taken by behavioral
              ecologists to the study of animal foraging behavior and explore
              connections with general analyses of decision making. I use the
              example of patch exploitation decisions in this article in order
              to develop several key points about the properties of naturally
              occurring foraging decisions. First, I argue that experimental
              preparations based on binary, mutually exclusive choice are not
              good models of foraging decisions. Instead, foraging choices have
              a sequential foreground-background structure, in which one option
              is in the background of all other options. Second, behavioral
              ecologists view foraging as a hierarchy of decisions that range
              from habitat selection to food choice. Finally, data suggest that
              foraging animals are sensitive to several important trade-offs.
              These trade-offs include the effects of competitors and group
              mates, as well as the problem of predator avoidance.",
  journal  = "Cogn. Affect. Behav. Neurosci.",
  volume   =  8,
  number   =  4,
  pages    = "475--484",
  month    =  dec,
  year     =  2008,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Pezzulo2014-up,
  title     = "The principles of goal-directed decision-making: from neural
               mechanisms to computation and robotics",
  author    = "Pezzulo, Giovanni and Verschure, Paul F M J and Balkenius,
               Christian and Pennartz, Cyriel M A",
  abstract  = "… Verschure et al … Footnotes. One contribution of 18 to a Theme
               Issue 'The principles of goal-directed decision - making : from
               neural mechanisms to computation and robotics'. \copyright{}
               2014 The Author(s) Published by the Royal Society. All rights
               reserved. References …",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "royalsocietypublishing.org",
  volume    =  369,
  number    =  1655,
  month     =  nov,
  year      =  2014,
  keywords  = "computational model; decision-making; goal-directed; neural
               mechanism; prediction; robotics",
  language  = "en"
}

@ARTICLE{Bogacz2006-lr,
  title     = "The physics of optimal decision making: a formal analysis of
               models of performance in two-alternative forced-choice tasks",
  author    = "Bogacz, Rafal and Brown, Eric and Moehlis, Jeff and Holmes,
               Philip and Cohen, Jonathan D",
  abstract  = "In this article, the authors consider optimal decision making in
               two-alternative forced-choice (TAFC) tasks. They begin by
               analyzing 6 models of TAFC decision making and show that all but
               one can be reduced to the drift diffusion model, implementing
               the statistically optimal algorithm (most accurate for a given
               speed or fastest for a given accuracy). They prove further that
               there is always an optimal trade-off between speed and accuracy
               that maximizes various reward functions, including reward rate
               (percentage of correct responses per unit time), as well as
               several other objective functions, including ones weighted for
               accuracy. They use these findings to address empirical data and
               make novel predictions about performance under optimality.",
  journal   = "Psychol. Rev.",
  publisher = "psycnet.apa.org",
  volume    =  113,
  number    =  4,
  pages     = "700--765",
  month     =  oct,
  year      =  2006,
  language  = "en"
}

@ARTICLE{Cande2018-le,
  title    = "Optogenetic dissection of descending behavioral control in
              Drosophila",
  author   = "Cande, Jessica and Namiki, Shigehiro and Qiu, Jirui and Korff,
              Wyatt and Card, Gwyneth M and Shaevitz, Joshua W and Stern, David
              L and Berman, Gordon J",
  abstract = "In most animals, the brain makes behavioral decisions that are
              transmitted by descending neurons to the nerve cord circuitry
              that produces behaviors. In insects, only a few descending
              neurons have been associated with specific behaviors. To explore
              how descending neurons control an insect's movements, we
              developed a novel method to systematically assay the behavioral
              effects of activating individual neurons on freely behaving
              terrestrial D. melanogaster. We calculated a two-dimensional
              representation of the entire behavior space explored by these
              flies, and we associated descending neurons with specific
              behaviors by identifying regions of this space that were visited
              with increased frequency during optogenetic activation. Applying
              this approach across a large collection of descending neurons, we
              found that (1) activation of most of the descending neurons drove
              stereotyped behaviors, (2) in many cases multiple descending
              neurons activated similar behaviors, and (3) optogenetically
              activated behaviors were often dependent on the behavioral state
              prior to activation.",
  journal  = "Elife",
  volume   =  7,
  month    =  jun,
  year     =  2018,
  keywords = "D. melanogaster; behavior; descending interneurons; neuroscience;
              optogenetics",
  language = "en"
}

@INCOLLECTION{Gomez-Marin2017-xa,
  title     = "Causal Circuit Explanations of Behavior: Are Necessity and
               Sufficiency Necessary and Sufficient?",
  booktitle = "Decoding Neural Circuit Structure and Function: Cellular
               Dissection Using Genetic Model Organisms",
  author    = "Gomez-Marin, Alex",
  editor    = "{\c C}elik, Arzu and Wernet, Mathias F",
  abstract  = "In the current advent of technological innovation allowing for
               precise neural manipulations and copious data collection, it is
               hardly questioned that the explanation of behavioral processes
               is to be chiefly found in neural circuits. Such belief, rooted
               in the exhausted dualism of cause and effect, is enacted by a
               methodology that promotes ``necessity and sufficiency'' claims
               as the goal-standard in neuroscience, thus instructing young
               students on what shall reckon as explanation. Here I wish to
               deconstruct and explicate the difference between what is done,
               what is said, and what is meant by such causal circuit
               explanations of behavior. Well-known to most philosophers, yet
               ignored or at least hardly ever made explicit by
               neuroscientists, the original grand claim of ``understanding the
               brain'' is imperceptibly substituted by the methodologically
               sophisticated task of empirically establishing counterfactual
               dependencies. But for the twenty-first century neuroscientist,
               after so much pride, this is really an excess of humility. I
               argue that to upgrade intervention to explanation is prone to
               logical fallacies, interpretational leaps and carries a weak
               explanatory force, thus settling and maintaining low standards
               for intelligibility in neuroscience. To claim that behavior is
               explained by a ``necessary and sufficient'' neural circuit is,
               at best, misleading. In that, my critique (rather than
               criticism) is indeed mainly negative. Positively, I briefly
               suggest some available alternatives for conceptual progress,
               such as adopting circular causality (rather than lineal
               causality in the flavor of top-down reductionism), searching for
               principles of behavior (rather than taking an arbitrary
               definition of behavior and rushing to dissect its ``underlying''
               neural mechanisms), and embracing process philosophy (rather
               than substance-mechanistic ontologies). Overall, if the goal of
               neuroscience is to understand the relation between brain and
               behavior then, in addition to excruciating neural studies (one
               pillar), we will need a strong theory of behavior (the other
               pillar) and a solid foundation to establish their relation (the
               bridge).",
  publisher = "Springer International Publishing",
  pages     = "283--306",
  year      =  2017,
  address   = "Cham"
}

@UNPUBLISHED{Fakhar2019-ew,
  title    = "Neuronal Causes and Behavioural Effects: a Review on Logical,
              Methodological, and Technical Issues With Respect to Causal
              Explanations of Behaviour in Neuroscience",
  author   = "Fakhar, Kayson and Gonschorek, Dominic and Schmors, Lisa and
              Bielczyk, Natalia Z",
  abstract = "Elucidating causal, neurobiological underpinnings of behaviour is
              an ultimate goal of every neuroscientific study. However, due to
              the complexity of the brain as well as the complexity of the
              human environment, finding a~causal architecture that underlies
              behaviour remains a~formidable challenge. In this manuscript, we
              review the logical and conceptual issues with respect to causal
              research in neuroscience. First, we review the state of the art
              interventional and computational approaches to infer causal
              brain-behaviour relationships. We provide an~overview of
              potential issues, flaws, and confounds in these studies. We
              conclude that studies on the causal structure underlying
              behaviour should be performed by accumulating evidence coming
              from several lines of experimental and modelling studies. Lastly,
              we also propose computational models including artificial
              neuronal networks and simulated animats as a~potential
              breakthrough to causal brain-behaviour investigations.",
  month    =  aug,
  year     =  2019,
  keywords = "brain-behaviour relations; brain interventions; causal inference;
              causality; cause and effect; computational models; Necessity and
              Sufficiency"
}

@ARTICLE{Carey2019-gk,
  title    = "Reward revaluation biases hippocampal replay content away from
              the preferred outcome",
  author   = "Carey, Alyssa A and Tanaka, Youki and van der Meer, Matthijs A A",
  abstract = "The rodent hippocampus spontaneously generates bursts of neural
              activity (replay) that can depict spatial trajectories to reward
              locations, suggesting a role in model-based behavioral control. A
              largely separate literature emphasizes reward revaluation as the
              litmus test for such control, yet the content of hippocampal
              replay under revaluation conditions is unknown. We examined the
              content of awake replay events following motivational shifts
              between hunger and thirst. On a T-maze offering free choice
              between food and water outcomes, rats shifted their behavior
              toward the restricted outcome, but replay content was shifted
              away from the restricted outcome. This effect preceded experience
              on the task each day and did not reverse with experience. These
              results demonstrate that replay content is not limited to
              reflecting recent experience or trajectories toward the preferred
              goal and suggest a role for motivational states in determining
              replay content.",
  journal  = "Nat. Neurosci.",
  month    =  aug,
  year     =  2019
}

@ARTICLE{Pouget2003-qe,
  title    = "Inference and computation with population codes",
  author   = "Pouget, Alexandre and Dayan, Peter and Zemel, Richard S",
  abstract = "In the vertebrate nervous system, sensory stimuli are typically
              encoded through the concerted activity of large populations of
              neurons. Classically, these patterns of activity have been
              treated as encoding the value of the stimulus (e.g., the
              orientation of a contour), and computation has been formalized in
              terms of function approximation. More recently, there have been
              several suggestions that neural computation is akin to a Bayesian
              inference process, with population activity patterns representing
              uncertainty about stimuli in the form of probability
              distributions (e.g., the probability density function over the
              orientation of a contour). This paper reviews both approaches,
              with a particular emphasis on the latter, which we see as a very
              promising framework for future modeling and experimental work.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  26,
  pages    = "381--410",
  month    =  apr,
  year     =  2003,
  language = "en"
}

@ARTICLE{Garrett_undated-lg,
  title  = "Biased belief updating and suboptimal choice in foraging decisions",
  author = "Garrett, Neil and Daw, Nathaniel D"
}

@ARTICLE{Edwards1954-hk,
  title    = "The theory of decision making",
  author   = "Edwards, W",
  journal  = "Psychol. Bull.",
  volume   =  51,
  number   =  4,
  pages    = "380--417",
  month    =  jul,
  year     =  1954,
  keywords = "THINKING",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{McNamara2014-xz,
  title     = "Natural selection can favour `irrational'behaviour",
  author    = "McNamara, John M and Trimmer, Pete C and Houston, A I",
  abstract  = "Understanding decisions is the fundamental aim of the
               behavioural sciences. The theory of rational choice is based on
               axiomatic principles such as transitivity and independence of
               irrelevant alternatives (IIA). Empirical studies have
               demonstrated that the behaviour of humans and other animals
               often seems irrational; there can be a lack of transitivity in
               choice and seemingly irrelevant alternatives can alter
               decisions. These violations of transitivity and IIA undermine
               rational choice theory. However, we show that an individual that
               is …",
  journal   = "Biol. Lett.",
  publisher = "The Royal Society",
  volume    =  10,
  number    =  1,
  pages     = "20130935",
  year      =  2014
}

@UNPUBLISHED{Gupta2019-hk,
  title    = "A context-free grammar for Caenorhabditis elegans behavior",
  author   = "Gupta, Saurabh and Gomez-Marin, Alex",
  abstract = "Hierarchy is a candidate organizing principle of ethology, where
              actions grouped into higher order chunks combine in specific ways
              to generate adaptive behavior. However, demonstrations of
              hierarchical organization in behavior have been scarce. Moreover,
              it remains unclear how such underlying organization allows for
              behavioral flexibility. Here we uncover the hierarchical and
              flexible nature of Caenorhabditis elegans behavior. By describing
              worm locomotion as a sequence of discrete postural templates, we
              identified chunks containing mutually substitutable postures
              along the dynamics. We then elucidated the rules governing their
              interactions. We found that stereotypical roaming can be
              described by a specific sequence of postural chunks, which
              exhibit flexibility at the lowest postural level. The same chunks
              get combined differently to produce dwelling, capturing
              non-stereotypical actions across timescales. We show that worm
              foraging is organized hierarchically ---a feature not explainable
              via Markovian dynamics---, and derive a context-free grammar
              governing its behavior ---which is different than a regular
              grammar, or a hidden Markov chain. In sum, in making the analogy
              with human language concrete (but not literal) our work
              demonstrates, in line with the foundational insights of classical
              ethologists, that spontaneous behavior is orderly flexible. Once
              more, investigating the humble nematode suggests that everything
              human has its roots in lower animal behavior. ![Figure][1]
              Graphical abstract [1]: pending:yes",
  journal  = "bioRxiv",
  pages    = "708891",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@ARTICLE{Gershman_undated-ml,
  title  = "The generative adversarial brain",
  author = "Gershman, Samuel J"
}

@ARTICLE{Iwanir2019-dw,
  title    = "Irrational behavior in C. elegans arises from asymmetric
              modulatory effects within single sensory neurons",
  author   = "Iwanir, Shachar and Ruach, Rotem and Itskovits, Eyal and Pritz,
              Christian O and Bokman, Eduard and Zaslaver, Alon",
  abstract = "C. elegans worms exhibit a natural chemotaxis towards food cues.
              This provides a potential platform to study the interactions
              between stimulus valence and innate behavioral preferences. Here
              we perform a comprehensive set of choice assays to measure worms'
              relative preference towards various attractants. Surprisingly, we
              find that when facing a combination of choices, worms'
              preferences do not always follow value-based hierarchy. In fact,
              the innate chemotaxis behavior in worms robustly violates key
              rationality paradigms of transitivity, independence of irrelevant
              alternatives and regularity. These violations arise due to
              asymmetric modulatory effects between the presented options.
              Functional analysis of the entire chemosensory system at a
              single-neuron resolution, coupled with analyses of mutants,
              defective in individual neurons, reveals that these asymmetric
              effects originate in specific sensory neurons.",
  journal  = "Nat. Commun.",
  volume   =  10,
  number   =  1,
  pages    = "3202",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Trueblood2019-vi,
  title    = "Urgency, Leakage, and the Relative Nature of Information
              Processing in Decision-making",
  author   = "Trueblood, Jennifer S and Heathcote, Andrew and Evans, Nathan J
              and Holmes, William R",
  abstract = "Over the last decade, there has been a robust debate in decision
              neuroscience and psychology about what mechanism governs the time
              course of decision making. Historically, the most prominent
              hypothesis is that neural architectures accumulate information
              over time until some threshold is met, the so-called Evidence
              Accumulation hypothesis. However, most applications of this
              theory rely on simplifying assumptions, belying a number of
              potential complexities. Is changing stimulus information
              perceived and processed in an independent manner or is there a
              relative component? Does urgency play a role? What about evidence
              leakage? Although the latter questions have been the subject of
              recent investigations, most studies to date have been piecemeal
              in nature, addressing one aspect of the decision process or
              another. Here we develop a modeling framework, an extension of
              the Urgency Gating Model, in conjunction with a changing
              information experimental paradigm to simultaneously probe these
              aspects of the decision process. Using state-of-the-art Bayesian
              methods to perform parameter-based inference, we find that 1)
              information processing is relative with early information
              influencing the perception of late information, 2) time varying
              urgency and evidence accumulation are of roughly equal importance
              in the decision process, and 3) leakage is present with a time
              scale of ~200-250ms. To our knowledge, this is the first
              comprehensive study to utilize a changing information paradigm to
              jointly and quantitatively estimate the temporal dynamics of
              human decision-making.",
  journal  = "bioRxiv",
  pages    = "706291",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@ARTICLE{Sohn2019-kc,
  title    = "Bayesian Computation through Cortical Latent Dynamics",
  author   = "Sohn, Hansem and Narain, Devika and Meirhaeghe, Nicolas and
              Jazayeri, Mehrdad",
  abstract = "Statistical regularities in the environment create prior beliefs
              that we rely on to optimize our behavior when sensory information
              is uncertain. Bayesian theory formalizes how prior beliefs can be
              leveraged and has had a major impact on models of perception,
              sensorimotor function, and cognition. However, it is not known
              how recurrent interactions among neurons mediate Bayesian
              integration. By using a time-interval reproduction task in
              monkeys, we found that prior statistics warp neural
              representations in the frontal cortex, allowing the mapping of
              sensory inputs to motor outputs to incorporate prior statistics
              in accordance with Bayesian inference. Analysis of recurrent
              neural network models performing the task revealed that this
              warping was enabled by a low-dimensional curved manifold and
              allowed us to further probe the potential causal underpinnings of
              this computational strategy. These results uncover a simple and
              general principle whereby prior beliefs exert their influence on
              behavior by sculpting cortical latent dynamics.",
  journal  = "Neuron",
  month    =  jul,
  year     =  2019,
  keywords = "Bayesian inference; Bayesian integration; frontal cortex; neural
              manifold; neural trajectories; recurrent neural networks",
  language = "en"
}

@ARTICLE{Draft2018-dk,
  title    = "Carpenter ants use diverse antennae sampling strategies to track
              odor trails",
  author   = "Draft, Ryan W and McGill, Matthew R and Kapoor, Vikrant and
              Murthy, Venkatesh N",
  abstract = "Directed and meaningful animal behavior depends on the ability to
              sense key features in the environment. Among the different
              environmental signals, olfactory cues are critically important
              for foraging, navigation and social communication in many
              species, including ants. Ants use their two antennae to explore
              the olfactory world, but how they do so remains largely unknown.
              In this study, we used high-resolution videography to
              characterize the antennae dynamics of carpenter ants (Camponotus
              pennsylvanicus). Antennae are highly active during both odor
              tracking and exploratory behavior. When tracking, ants used
              several distinct behavioral strategies with stereotyped antennae
              sampling patterns (which we call 'sinusoidal', 'probing' and
              'trail following'). In all behaviors, left and right antennae
              movements were anti-correlated, and tracking ants exhibited
              biases in the use of left versus right antenna to sample the odor
              trail. These results suggest non-redundant roles for the two
              antennae. In one of the behavioral modules (trail following),
              ants used both antennae to detect trail edges and direct
              subsequent turns, suggesting a specialized form of tropotaxis.
              Lastly, removal of an antenna resulted not only in less accurate
              tracking but also in changes in the sampling pattern of the
              remaining antenna. Our quantitative characterization of odor
              trail tracking lays a foundation to build better models of
              olfactory sensory processing and sensorimotor behavior in
              terrestrial insects.",
  journal  = "J. Exp. Biol.",
  volume   =  221,
  number   = "Pt 22",
  month    =  nov,
  year     =  2018,
  keywords = "Behavior; Camponotus; Navigation; Olfaction; Pheromone; Trail
              tracking",
  language = "en"
}

@MISC{Hyvonen2019-se,
  title        = "Bayesian Inference 2019",
  author       = "Hyv{\"o}nen, Ville and Tolonen, Topias",
  abstract     = "Lecture notes for Bayesian Inference course lectured at
                  University of Helsinki Spring 2019",
  month        =  mar,
  year         =  2019,
  howpublished = "\url{https://vioshyvo.github.io/Bayesian_inference/index.html}",
  note         = "Accessed: 2019-7-15",
  keywords     = "books;Books"
}

@UNPUBLISHED{Mohl2019-dl,
  title    = "Sensitivity and specificity of a Bayesian single trial analysis
              for time varying neural signals",
  author   = "Mohl, Jeff T and Caruso, Valeria C and Tokdar, Surya T and Groh,
              J M",
  abstract = "We recently reported the existence of fluctuations in neural
              signals that may permit neurons to code multiple simultaneous
              stimuli sequentially across time[1][1]. This required deploying a
              novel statistical approach to permit investigation of neural
              activity at the scale of individual trials. Here we present tests
              using synthetic data to assess the sensitivity and specificity of
              this analysis. Data sets were fabricated to match each of several
              potential response patterns derived from single-stimulus response
              distributions. In particular, we simulated dual stimulus trial
              spike counts that reflected fluctuating mixtures of the single
              stimulus spike counts, stable intermediate averages, single
              stimulus winner-take-all, or response distributions that were
              outside the range defined by the single stimulus responses (such
              as summation or suppression). We then assessed how well the
              analysis recovered the correct response pattern as a function of
              the number of simulated trials and the difference between the
              simulated responses to each ``stimulus'' alone. We found
              excellent recovery of the mixture, intermediate, and outside
              categories (>97\% correct), and good recovery of the
              single/winner-take-all category (>90\% correct) when the number
              of trials was >20 and the single-stimulus response rates were
              50Hz and 20Hz respectively. Both larger numbers of trials and
              greater separation between the single stimulus firing rates
              improved categorization accuracy. The results provide a valid
              benchmark, and guidelines for data collection, for use of this
              method to investigate coding of multiple items at the
              individual-trial time scale. [1]: \#ref-1",
  journal  = "bioRxiv",
  pages    = "690958",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@ARTICLE{Bari2019-iw,
  title    = "Stable Representations of Decision Variables for Flexible
              Behavior",
  author   = "Bari, Bilal A and Grossman, Cooper D and Lubin, Emily E and
              Rajagopalan, Adithya E and Cressy, Jianna I and Cohen, Jeremiah Y",
  abstract = "Decisions occur in dynamic environments. In the framework of
              reinforcement learning, the probability of performing an action
              is influenced by decision variables. Discrepancies between
              predicted and obtained rewards (reward prediction errors) update
              these variables, but they are otherwise stable between decisions.
              Although reward prediction errors have been mapped to midbrain
              dopamine neurons, it is unclear how the brain represents decision
              variables themselves. We trained mice on a dynamic foraging task
              in which they chose between alternatives that delivered reward
              with changing probabilities. Neurons in the medial prefrontal
              cortex, including projections to the dorsomedial striatum,
              maintained persistent firing rate changes over long timescales.
              These changes stably represented relative action values (to bias
              choices) and total action values (to bias response times) with
              slow decay. In contrast, decision variables were weakly
              represented in the anterolateral motor cortex, a region necessary
              for generating choices. Thus, we define a stable neural mechanism
              to drive flexible behavior.",
  journal  = "Neuron",
  month    =  jun,
  year     =  2019,
  language = "en"
}

@ARTICLE{noauthor_undated-eq,
  title = "Decision Field Theory"
}

@ARTICLE{Japyassu2017-rx,
  title    = "Extended spider cognition",
  author   = "Japyass{\'u}, Hilton F and Laland, Kevin N",
  abstract = "There is a tension between the conception of cognition as a
              central nervous system (CNS) process and a view of cognition as
              extending towards the body or the contiguous environment. The
              centralised conception requires large or complex nervous systems
              to cope with complex environments. Conversely, the extended
              conception involves the outsourcing of information processing to
              the body or environment, thus making fewer demands on the
              processing power of the CNS. The evolution of extended cognition
              should be particularly favoured among small, generalist predators
              such as spiders, and here, we review the literature to evaluate
              the fit of empirical data with these contrasting models of
              cognition. Spiders do not seem to be cognitively limited,
              displaying a large diversity of learning processes, from
              habituation to contextual learning, including a sense of
              numerosity. To tease apart the central from the extended
              cognition, we apply the mutual manipulability criterion, testing
              the existence of reciprocal causal links between the putative
              elements of the system. We conclude that the web threads and
              configurations are integral parts of the cognitive systems. The
              extension of cognition to the web helps to explain some puzzling
              features of spider behaviour and seems to promote evolvability
              within the group, enhancing innovation through cognitive
              connectivity to variable habitat features. Graded changes in
              relative brain size could also be explained by outsourcing
              information processing to environmental features. More generally,
              niche-constructed structures emerge as prime candidates for
              extending animal cognition, generating the selective pressures
              that help to shape the evolving cognitive system.",
  journal  = "Anim. Cogn.",
  volume   =  20,
  number   =  3,
  pages    = "375--395",
  month    =  may,
  year     =  2017,
  keywords = "Evolvability; Extended cognition; Modular cognition; Niche
              construction; Web building",
  language = "en"
}

@ARTICLE{Globus1992-on,
  title     = "Toward a noncomputational cognitive neuroscience",
  author    = "Globus, G G",
  abstract  = "The near universally accepted theory that the brain processes
               information persists in current neural network theory where
               there is ``subsymbolic'' computation (Smolensky, 1988) on
               distributed representations. This theory of brain information
               processing may suffice for simplifying models simulated in
               silicon but not for living neural nets where there is ongoing
               chemical tuning of the input/output transfer function at the
               nodes, connection weights, network parameters, and connectivity.
               Here the brain continually changes itself as it intersects with
               information from the outside. An alternative theory to
               information processing is developed in which the brain permits
               and supports ``participation'' of self and other as constraints
               on the dynamically evolving, self-organizing whole. The
               noncomputational process of ``differing and deferring'' in
               nonlinear dynamic neural systems is contrasted with Black's
               (1991) account of molecular information processing. State
               hyperspace for the noncomputational process of nonlinear
               dynamical systems, unlike classical systems, has a fractal
               dimension. The noncomputational model is supported by suggestive
               evidence for fractal properties of the brain.",
  journal   = "J. Cogn. Neurosci.",
  publisher = "MIT Press",
  volume    =  4,
  number    =  4,
  pages     = "299--300",
  year      =  1992,
  language  = "en"
}

@ARTICLE{Turchin1992-ad,
  title     = "Complex Dynamics in Ecological Time Series",
  author    = "Turchin, Peter and Taylor, Andrew D",
  abstract  = "Although the possibility of complex dynamical behaviors?limit
               cycles, quasiperodic oscillations, and aperiodic chaos?has been
               recognized theoretically, most ecologists are skeptical of their
               importance in nature. In this paper we develop a methodology for
               reconstructing endogenous (or deterministic) dynamics from
               ecological time series. Our method consists of fitting a
               response surface to the yearly population change as a function
               of lagged population densities. Using the version of the model
               that includes two lags, we fitted time?series data for 14 insect
               and 22 vertebrate populations. The 14 insect populations were
               classified as: unregulated (1 case), exponentially stable (three
               cases), damped oscillations (six cases), limit cycles (one
               case), quasiperiodic oscillations (two cases), and chaos (one
               case). The vertebrate examples exhibited a similar spectrum of
               dynamics, although there were no cases of chaos. We tested the
               results of the response?surface methodology by calculating
               autocorrelation functions for each time series. Autocorrelation
               patterns were in agreement with our findings of periodic
               behaviors (damped oscillations, limit cycles, and
               quasiperiodicity). On the basis of these results, we conclude
               that the complete spectrum of dynamical behaviors, ranging from
               exponential stability to chaos, is likely to be found among
               natural populations.",
  journal   = "Ecology",
  publisher = "Wiley Online Library",
  volume    =  73,
  number    =  1,
  pages     = "289--305",
  month     =  feb,
  year      =  1992
}

@INPROCEEDINGS{Koza1991-pg,
  title     = "Evolution and co-evolution of computer programs to control
               independently-acting agents",
  booktitle = "Proceedings of the First International Conference on Simulation
               of Adaptive Behavior: From Animals to Animats. {MIT} Press,
               Cambridge, {MA}",
  author    = "Koza, John R",
  abstract  = "This paper describes the recently developed`` genetic
               programming'' paradigm which genetically breeds populations of
               computer programs to solve problems. In genetic programming, the
               individuals in the population are hierarchical computer programs
               of various sizes and shapes. This paper also extends the genetic
               programming paradigm to a`` co-evolution'' algorithm which
               operates simultaneously on two populations of independently-
               acting hierarchical computer programs of various sizes and
               shapes.",
  publisher = "sci.brooklyn.cuny.edu",
  pages     = "366--375",
  year      =  1991
}

@ARTICLE{Pereira2019-ym,
  title    = "Fast animal pose estimation using deep neural networks",
  author   = "Pereira, Talmo D and Aldarondo, Diego E and Willmore, Lindsay and
              Kislin, Mikhail and Wang, Samuel S-H and Murthy, Mala and
              Shaevitz, Joshua W",
  abstract = "The need for automated and efficient systems for tracking full
              animal pose has increased with the complexity of behavioral data
              and analyses. Here we introduce LEAP (LEAP estimates animal
              pose), a deep-learning-based method for predicting the positions
              of animal body parts. This framework consists of a graphical
              interface for labeling of body parts and training the network.
              LEAP offers fast prediction on new data, and training with as few
              as 100 frames results in 95\% of peak performance. We validated
              LEAP using videos of freely behaving fruit flies and tracked 32
              distinct points to describe the pose of the head, body, wings and
              legs, with an error rate of <3\% of body length. We recapitulated
              reported findings on insect gait dynamics and demonstrated LEAP's
              applicability for unsupervised behavioral classification.
              Finally, we extended the method to more challenging imaging
              situations and videos of freely moving mice.",
  journal  = "Nat. Methods",
  volume   =  16,
  number   =  1,
  pages    = "117--125",
  month    =  jan,
  year     =  2019,
  language = "en"
}

@ARTICLE{Garamszegi2011-vk,
  title    = "Information-theoretic approaches to statistical analysis in
              behavioural ecology: an introduction",
  author   = "Garamszegi, L{\'a}szl{\'o} Zsolt",
  abstract = "Scientific thinking may require the consideration of multiple
              hypotheses, which often call for complex statistical models at
              the level of data analysis. The aim of this introduction is to
              provide a brief overview on how competing hypotheses are
              evaluated statistically in behavioural ecological studies and to
              offer potentially fruitful avenues for future methodological
              developments. Complex models have traditionally been treated by
              model selection approaches using threshold-based removal of
              terms, i.e. stepwise selection. A recently introduced method for
              model selection applies an information-theoretic (IT) approach,
              which simultaneously evaluates hypotheses by balancing between
              model complexity and goodness of fit. The IT method has been
              increasingly propagated in the field of ecology, while a
              literature survey shows that its spread in behavioural ecology
              has been much slower, and model simplification using stepwise
              selection is still more widespread than IT-based model selection.
              Why has the use of IT methods in behavioural ecology lagged
              behind other disciplines? This special issue examines the
              suitability of the IT method for analysing data with multiple
              predictors, which researchers encounter in our field. The volume
              brings together different viewpoints to aid behavioural
              ecologists in understanding the method, with the hope of
              enhancing the statistical integration of our discipline.",
  journal  = "Behav. Ecol. Sociobiol.",
  volume   =  65,
  number   =  1,
  pages    = "1--11",
  month    =  jan,
  year     =  2011
}

@ARTICLE{Panzeri2007-vl,
  title     = "Correcting for the sampling bias problem in spike train
               information measures",
  author    = "Panzeri, Stefano and Senatore, Riccardo and Montemurro, Marcelo
               A and Petersen, Rasmus S",
  abstract  = "Information Theory enables the quantification of how much
               information a neuronal response carries about external stimuli
               and is hence a natural analytic framework for studying neural
               coding. The main difficulty in its practical application to
               spike train analysis is that estimates of neuronal information
               from experimental data are prone to a systematic error (called
               ``bias''). This bias is an inevitable consequence of the limited
               number of stimulus-response samples that it is possible to
               record in a real experiment. In this paper, we first explain the
               origin and the implications of the bias problem in spike train
               analysis. We then review and evaluate some recent
               general-purpose methods to correct for sampling bias: the
               Panzeri-Treves, Quadratic Extrapolation, Best Universal Bound,
               Nemenman-Shafee-Bialek procedures, and a recently proposed
               shuffling bias reduction procedure. Finally, we make practical
               recommendations for the accurate computation of information from
               spike trains. Our main recommendation is to estimate information
               using the shuffling bias reduction procedure in combination with
               one of the other four general purpose bias reduction procedures
               mentioned in the preceding text. This provides information
               estimates with acceptable variance and which are unbiased even
               when the number of trials per stimulus is as small as the number
               of possible discrete neuronal responses.",
  journal   = "J. Neurophysiol.",
  publisher = "physiology.org",
  volume    =  98,
  number    =  3,
  pages     = "1064--1072",
  month     =  sep,
  year      =  2007,
  language  = "en"
}

@ARTICLE{Quian_Quiroga2009-gj,
  title     = "Extracting information from neuronal populations: information
               theory and decoding approaches",
  author    = "Quian Quiroga, Rodrigo and Panzeri, Stefano",
  abstract  = "To a large extent, progress in neuroscience has been driven by
               the study of single-cell responses averaged over several
               repetitions of stimuli or behaviours. However,the brain
               typically makes decisions based on single events by evaluating
               the activity of large neuronal populations. Therefore, to
               further understand how the brain processes information, it is
               important to shift from a single-neuron, multiple-trial
               framework to multiple-neuron, single-trial methodologies. Two
               related approaches--decoding and information theory--can be used
               to extract single-trial information from the activity of
               neuronal populations. Such population analysis can give us more
               information about how neurons encode stimulus features than
               traditional single-cell studies.",
  journal   = "Nat. Rev. Neurosci.",
  publisher = "nature.com",
  volume    =  10,
  number    =  3,
  pages     = "173--185",
  month     =  mar,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Treves1995-zx,
  title     = "The Upward Bias in Measures of Information Derived from Limited
               Data Samples",
  author    = "Treves, Alessandro and Panzeri, Stefano",
  abstract  = "Extracting information measures from limited experimental
               samples, such as those normally available when using data
               recorded in vivo from mammalian cortical neurons, is known to be
               plagued by a systematic error, which tends to bias the estimate
               upward. We calculate here the average of the bias, under certain
               conditions, as an asymptotic expansion in the inverse of the
               size of the data sample. The result agrees with numerical
               simulations, and is applicable, as an additive correction term,
               to measurements obtained under such conditions. Moreover, we
               discuss the implications for measurements obtained through other
               usual procedures.",
  journal   = "Neural Comput.",
  publisher = "MIT Press",
  volume    =  7,
  number    =  2,
  pages     = "399--407",
  month     =  mar,
  year      =  1995
}

@ARTICLE{Dimitrov2011-fm,
  title    = "Information theory in neuroscience",
  author   = "Dimitrov, Alexander G and Lazar, Aurel A and Victor, Jonathan D",
  journal  = "J. Comput. Neurosci.",
  volume   =  30,
  number   =  1,
  pages    = "1--5",
  month    =  feb,
  year     =  2011,
  language = "en"
}

@INCOLLECTION{Nadel2006-ld,
  title     = "Information Theory",
  booktitle = "Encyclopedia of Cognitive Science",
  editor    = "Nadel, Lynn",
  abstract  = "Abstract Information theory is a mathematical theory defining
               the limits and possibilities of communication. It provides a
               quantitative measure of the information content of a message,
               which is independent of the meaning of the message, in terms of
               the reduction of uncertainty resulting from receiving the
               message.",
  publisher = "John Wiley \& Sons, Ltd",
  volume    =  61,
  pages     = "183",
  month     =  jan,
  year      =  2006,
  address   = "Chichester"
}

@ARTICLE{Borst1999-st,
  title    = "Information theory and neural coding",
  author   = "Borst, A and Theunissen, F E",
  abstract = "Information theory quantifies how much information a neural
              response carries about the stimulus. This can be compared to the
              information transferred in particular models of the
              stimulus-response function and to maximum possible information
              transfer. Such comparisons are crucial because they validate
              assumptions present in any neurophysiological analysis. Here we
              review information-theory basics before demonstrating its use in
              neural coding. We show how to use information theory to validate
              simple stimulus-response models of neural coding of dynamic
              stimuli. Because these models require specification of spike
              timing precision, they can reveal which time scales contain
              information in neural coding. This approach shows that dynamic
              stimuli can be encoded efficiently by single neurons and that
              each spike contributes to information transmission. We argue,
              however, that the data obtained so far do not suggest a temporal
              code, in which the placement of spikes relative to each other
              yields additional information.",
  journal  = "Nat. Neurosci.",
  volume   =  2,
  number   =  11,
  pages    = "947--957",
  month    =  nov,
  year     =  1999,
  language = "en"
}

@ARTICLE{noauthor_undated-vy,
  title = "mataric.pdf"
}

@ARTICLE{Peek2016-wi,
  title    = "Comparative approaches to escape",
  author   = "Peek, Martin Y and Card, Gwyneth M",
  abstract = "Neural circuits mediating visually evoked escape behaviors are
              promising systems in which to dissect the neural basis of
              behavior. Behavioral responses to predator-like looming stimuli,
              and their underlying neural computations, are remarkably similar
              across species. Recently, genetic tools have been applied in this
              classical paradigm, revealing novel non-cortical pathways that
              connect loom processing to defensive behaviors in mammals and
              demonstrating that loom encoding models from locusts also fit
              vertebrate neural responses. In both invertebrates and
              vertebrates, relative spike-timing in descending pathways is a
              mechanism for escape behavior choice. Current findings suggest
              that experimentally tractable systems, such as Drosophila, may be
              applicable models for sensorimotor processing and persistent
              states in higher organisms.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  41,
  pages    = "167--173",
  month    =  dec,
  year     =  2016,
  language = "en"
}

@ARTICLE{Ache2019-jc,
  title    = "Neural Basis for Looming Size and Velocity Encoding in the
              Drosophila Giant Fiber Escape Pathway",
  author   = "Ache, Jan M and Polsky, Jason and Alghailani, Shada and Parekh,
              Ruchi and Breads, Patrick and Peek, Martin Y and Bock, Davi D and
              von Reyn, Catherine R and Card, Gwyneth M",
  abstract = "Identified neuron classes in vertebrate cortical [1-4] and
              subcortical [5-8] areas and invertebrate peripheral [9-11] and
              central [12-14] brain neuropils encode specific visual features
              of a panorama. How downstream neurons integrate these features to
              control vital behaviors, like escape, is unclear [15]. In
              Drosophila, the timing of a single spike in the giant fiber (GF)
              descending neuron [16-18] determines whether a fly uses a short
              or long takeoff when escaping a looming predator [13]. We
              previously proposed that GF spike timing results from summation
              of two visual features whose detection is highly conserved across
              animals [19]: an object's subtended angular size and its angular
              velocity [5-8, 11, 20, 21]. We attributed velocity encoding to
              input from lobula columnar type 4 (LC4) visual projection
              neurons, but the size-encoding source remained unknown. Here, we
              show that lobula plate/lobula columnar, type 2 (LPLC2) visual
              projection neurons anatomically specialized to detect looming
              [22] provide the entire GF size component. We find LPLC2 neurons
              to be necessary for GF-mediated escape and show that LPLC2 and
              LC4 synapse directly onto the GF via reconstruction in a fly
              brain electron microscopy (EM) volume [23]. LPLC2 silencing
              eliminates the size component of the GF looming response in
              patch-clamp recordings, leaving only the velocity component. A
              model summing a linear function of angular velocity (provided by
              LC4) and a Gaussian function of angular size (provided by LPLC2)
              replicates GF looming response dynamics and predicts the peak
              response time. We thus present an identified circuit in which
              information from looming feature-detecting neurons is combined by
              a common post-synaptic target to determine behavioral output.",
  journal  = "Curr. Biol.",
  volume   =  29,
  number   =  6,
  pages    = "1073--1081.e4",
  month    =  mar,
  year     =  2019,
  keywords = "Drosophila; descending neuron; electrophysiology; escape; in vivo
              patch clamp; neural circuit reconstruction; sensorimotor
              integration; visual feature detection; visual looming; visual
              projection neuron",
  language = "en"
}

@ARTICLE{Domenici2011-ex,
  title    = "Animal escapology I: theoretical issues and emerging trends in
              escape trajectories",
  author   = "Domenici, Paolo and Blagburn, Jonathan M and Bacon, Jonathan P",
  abstract = "Escape responses are used by many animal species as their main
              defence against predator attacks. Escape success is determined by
              a number of variables; important are the directionality (the
              percentage of responses directed away from the threat) and the
              escape trajectories (ETs) measured relative to the threat.
              Although logic would suggest that animals should always turn away
              from a predator, work on various species shows that these away
              responses occur only approximately 50-90\% of the time. A small
              proportion of towards responses may introduce some
              unpredictability and may be an adaptive feature of the escape
              system. Similar issues apply to ETs. Theoretically, an optimal ET
              can be modelled on the geometry of predator-prey encounters.
              However, unpredictability (and hence high variability) in
              trajectories may be necessary for preventing predators from
              learning a simple escape pattern. This review discusses the
              emerging trends in escape trajectories, as well as the modulating
              key factors, such as the surroundings and body design. The main
              ET patterns identified are: (1) high ET variability within a
              limited angular sector (mainly 90-180 deg away from the threat;
              this variability is in some cases based on multiple peaks of
              ETs), (2) ETs that allow sensory tracking of the threat and (3)
              ETs towards a shelter. These characteristic features are observed
              across various taxa and, therefore, their expression may be
              mainly related to taxon-independent animal design features and to
              the environmental context in which prey live - for example
              whether the immediate surroundings of the prey provide potential
              refuges.",
  journal  = "J. Exp. Biol.",
  volume   =  214,
  number   = "Pt 15",
  pages    = "2463--2473",
  month    =  aug,
  year     =  2011,
  language = "en"
}

@ARTICLE{Schaefer2001-fc,
  title    = "Descending influences on escape behavior and motor pattern in the
              cockroach",
  author   = "Schaefer, P L and Ritzmann, R E",
  abstract = "The escape behavior of the cockroach is a ballistic behavior with
              well characterized kinematics. The circuitry known to control the
              behavior lies in the thoracic ganglia, abdominal ganglia, and
              abdominal nerve cord. Some evidence suggests inputs may occur
              from the brain or suboesophageal ganglion. We tested this notion
              by decapitating cockroaches, removing all descending inputs, and
              evoking escape responses. The decapitated cockroaches exhibited
              directionally appropriate escape turns. However, there was a
              front-to-back gradient of change: the front legs moved little if
              at all, the middle legs moved in the proper direction but with
              reduced excursion, and the rear legs moved normally. The same
              pattern was seen when only inputs from the brain were removed,
              the suboesophageal ganglion remaining intact and connected to the
              thoracic ganglia. Electromyogram (EMG) analysis showed that the
              loss of or reduction in excursion was accompanied by a loss of or
              reduction in fast motor neuron activity. The loss of fast motor
              neuron activity was also observed in a reduced preparation in
              which descending neural signals were reversibly blocked via an
              isotonic sucrose solution superfusing the neck connectives,
              indicating that the changes seen were not due to trauma. Our data
              demonstrate that while the thoracic circuitry is sufficient to
              produce directional escape, lesion or blockage of the connective
              affects the excitability of components of the escape circuitry.
              Because of the rapidity of the escape response, such effects are
              likely due to the elimination of tonic descending inputs.",
  journal  = "J. Neurobiol.",
  volume   =  49,
  number   =  1,
  pages    = "9--28",
  month    =  oct,
  year     =  2001,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@INPROCEEDINGS{Attias2003-wk,
  title     = "Planning by probabilistic inference",
  booktitle = "{AISTATS}",
  author    = "Attias, Hagai",
  abstract  = "This paper presents and demonstrates a new approach to the
               problem of planning under uncertainty. Actions are treated as
               hidden variables, with their own prior distributions, in a
               probabilistic generative model involving actions and states.
               Planning is done by computing …",
  publisher = "pdfs.semanticscholar.org",
  year      =  2003
}

@ARTICLE{Boutilier2011-ui,
  title     = "{Decision-Theoretic} Planning: Structural Assumptions and
               Computational Leverage",
  author    = "Boutilier, C and Dean, T and Hanks, S",
  abstract  = "Planning under uncertainty is a central problem in the study of",
  journal   = "arXiv e-prints",
  publisher = "adsabs.harvard.edu",
  month     =  may,
  year      =  2011,
  keywords  = "Computer Science - Artificial Intelligence"
}

@ARTICLE{Grush2004-db,
  title     = "The emulation theory of representation: motor control, imagery,
               and perception",
  author    = "Grush, Rick",
  abstract  = "The emulation theory of representation is developed and explored
               as a framework that can revealingly synthesize a wide variety of
               representational functions of the brain. The framework is based
               on constructs from control theory (forward models) and signal
               processing (Kalman filters). The idea is that in addition to
               simply engaging with the body and environment, the brain
               constructs neural circuits that act as models of the body and
               environment. During overt sensorimotor engagement, these models
               are driven by efference copies in parallel with the body and
               environment, in order to provide expectations of the sensory
               feedback, and to enhance and process sensory information. These
               models can also be run off-line in order to produce imagery,
               estimate outcomes of different actions, and evaluate and develop
               motor plans. The framework is initially developed within the
               context of motor control, where it has been shown that inner
               models running in parallel with the body can reduce the effects
               of feedback delay problems. The same mechanisms can account for
               motor imagery as the off-line driving of the emulator via
               efference copies. The framework is extended to account for
               visual imagery as the off-line driving of an emulator of the
               motor-visual loop. I also show how such systems can provide for
               amodal spatial imagery. Perception, including visual perception,
               results from such models being used to form expectations of, and
               to interpret, sensory input. I close by briefly outlining other
               cognitive functions that might also be synthesized within this
               framework, including reasoning, theory of mind phenomena, and
               language.",
  journal   = "Behav. Brain Sci.",
  publisher = "cambridge.org",
  volume    =  27,
  number    =  3,
  pages     = "377--96; discussion 396--442",
  month     =  jun,
  year      =  2004,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Murphy2002-fs,
  title     = "Dynamic bayesian networks: representation, inference and
               learning",
  author    = "Murphy, Kevin Patrick and Russell, Stuart",
  abstract  = "Sequential data arises in many areas of science and engineering.
               The data may either be a time series, generated by a dynamical
               system, or a sequence generated by a 1-dimensional spatial
               process, eg, biosequences. One may be interested either in
               online analysis, where the data arrives in real-time, or in
               offline analysis, where all the data has already been collected.
               In online analysis, one common task is to predict future
               observations, given all the observations up to the present time,
               which we will denote by y1: t=(y1,..., yt).(In this thesis …",
  publisher = "University of California, Berkeley Dissertation",
  year      =  2002
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Toussaint2009-ac,
  title     = "Probabilistic inference as a model of planned behavior",
  author    = "Toussaint, Marc",
  abstract  = "The problem of planning and goal-directed behavior has been
               addressed in computer science for many years, typically based on
               classical concepts like Bellman's optimality principle, dynamic
               programming, or Reinforcement Learning methods--but is this the
               only way to address the problem? Recently there is growing
               interest in using probabilistic inference methods for decision
               making and planning. Promising about such approaches is that
               they naturally extend to distributed state representations and
               efficiently cope with …",
  journal   = "KI",
  publisher = "researchgate.net",
  volume    =  23,
  number    =  3,
  pages     = "23--29",
  year      =  2009
}

@ARTICLE{Muller2017-ag,
  title    = "What Is Morphological Computation? On How the Body Contributes to
              Cognition and Control",
  author   = "M{\"u}ller, Vincent C and Hoffmann, Matej",
  abstract = "The contribution of the body to cognition and control in natural
              and artificial agents is increasingly described as ``offloading
              computation from the brain to the body,'' where the body is said
              to perform ``morphological computation.'' Our investigation of
              four characteristic cases of morphological computation in animals
              and robots shows that the ``offloading'' perspective is
              misleading. Actually, the contribution of body morphology to
              cognition and control is rarely computational, in any useful
              sense of the word. We thus distinguish (1) morphology that
              facilitates control, (2) morphology that facilitates perception,
              and the rare cases of (3) morphological computation proper, such
              as reservoir computing, where the body is actually used for
              computation. This result contributes to the understanding of the
              relation between embodiment and computation: The question for
              robot design and cognitive science is not whether computation is
              offloaded to the body, but to what extent the body facilitates
              cognition and control-how it contributes to the overall
              orchestration of intelligent behavior.",
  journal  = "Artif. Life",
  volume   =  23,
  number   =  1,
  pages    = "1--24",
  month    =  jan,
  year     =  2017,
  keywords = "Body; cognition; computation; control; embodiment; soft robotics",
  language = "en"
}

@ARTICLE{Pezzulo2017-xp,
  title     = "{Model-Based} Approaches to Active Perception and Control",
  author    = "Pezzulo, Giovanni and Donnarumma, Francesco and Iodice,
               Pierpaolo and Maisto, Domenico and Stoianov, Ivilin",
  abstract  = "There is an on-going debate in cognitive (neuro) science and
               philosophy between classical cognitive theory and embodied,
               embedded, extended, and enactive (``4-Es'') views of
               cognition---a family of theories that emphasize the role of the
               body in cognition and the importance of brain-body-environment
               interaction over and above internal representation. This debate
               touches foundational issues, such as whether the brain
               internally represents the external environment, and ``infers''
               or ``computes'' something. Here we focus on two (4-Es-based)
               criticisms to traditional cognitive theories---to the notions of
               passive perception and of serial information processing---and
               discuss alternative ways to address them, by appealing to
               frameworks that use, or do not use, notions of internal
               modelling and inference. Our analysis illustrates that: an
               explicitly inferential framework can capture some key aspects of
               embodied and enactive theories of cognition; some claims of
               computational and dynamical theories can be reconciled rather
               than seen as alternative explanations of cognitive phenomena;
               and some aspects of cognitive processing (e.g., detached
               cognitive operations, such as planning and imagination) that are
               sometimes puzzling to explain from enactive and
               non-representational perspectives can, instead, be captured
               nicely from the perspective that internal generative models and
               predictive processing mediate adaptive control loops.",
  journal   = "Entropy",
  publisher = "Multidisciplinary Digital Publishing Institute",
  volume    =  19,
  number    =  6,
  pages     = "266",
  month     =  jun,
  year      =  2017,
  language  = "en"
}

@ARTICLE{Milkowski2018-bi,
  title     = "Morphological Computation: Nothing but Physical Computation",
  author    = "Mi{\l}kowski, Marcin",
  abstract  = "The purpose of this paper is to argue against the claim that
               morphological computation is substantially different from other
               kinds of physical computation. I show that some (but not all)
               purported cases of morphological computation do not count as
               specifically computational, and that those that do are solely
               physical computational systems. These latter cases are not,
               however, specific enough: all computational systems, not only
               morphological ones, may (and sometimes should) be studied in
               various ways, including their energy efficiency, cost,
               reliability, and durability. Second, I critically analyze the
               notion of ``offloading'' computation to the morphology of an
               agent or robot, by showing that, literally, computation is
               sometimes not offloaded but simply avoided. Third, I point out
               that while the morphology of any agent is indicative of the
               environment that it is adapted to, or informative about that
               environment, it does not follow that every agent has access to
               its morphology as the model of its environment.",
  journal   = "Entropy",
  publisher = "Multidisciplinary Digital Publishing Institute",
  volume    =  20,
  number    =  12,
  pages     = "942",
  month     =  dec,
  year      =  2018,
  language  = "en"
}

@UNPUBLISHED{Calhoun2019-qk,
  title    = "Unsupervised identification of the internal states that shape
              natural behavior",
  author   = "Calhoun, Adam J and Pillow, Jonathan and Murthy, Mala",
  abstract = "Internal states can shape stimulus responses and decision-making,
              but we lack methods to identify internal states and how they
              evolve over time. To address this gap, we have developed an
              unsupervised method to identify internal states from behavioral
              data, and have applied it to the study of a dynamic social
              interaction. During courtship, Drosophila melanogaster males
              pattern their songs using feedback cues from their partner. Our
              model uncovers three latent states underlying this behavior, and
              is able to predict the moment-to-moment variation in natural song
              patterning decisions. These distinct behavioral states correspond
              to different sensorimotor strategies, each of which is
              characterized by different mappings from feedback cues to song
              modes. Using the model, we show that a pair of neurons previously
              thought to be command neurons for song production are sufficient
              to drive switching between states. Our results reveal how animals
              compose behavior from previously unidentified internal states, a
              necessary step for quantitative descriptions of animal behavior
              that link environmental cues, internal needs, neuronal activity,
              and motor outputs.",
  journal  = "bioRxiv",
  pages    = "691196",
  month    =  jul,
  year     =  2019,
  language = "en"
}

@ARTICLE{Gallego2017-bn,
  title    = "Neural Manifolds for the Control of Movement",
  author   = "Gallego, Juan A and Perich, Matthew G and Miller, Lee E and
              Solla, Sara A",
  abstract = "The analysis of neural dynamics in several brain cortices has
              consistently uncovered low-dimensional manifolds that capture a
              significant fraction of neural variability. These neural
              manifolds are spanned by specific patterns of correlated neural
              activity, the ``neural modes.'' We discuss a model for neural
              control of movement in which the time-dependent activation of
              these neural modes is the generator of motor behavior. This
              manifold-based view of motor cortex may lead to a better
              understanding of how the brain controls movement.",
  journal  = "Neuron",
  volume   =  94,
  number   =  5,
  pages    = "978--984",
  month    =  jun,
  year     =  2017,
  language = "en"
}

@ARTICLE{Hinman2019-nx,
  title    = "Neuronal representation of environmental boundaries in egocentric
              coordinates",
  author   = "Hinman, James R and Chapman, G William and Hasselmo, Michael E",
  abstract = "Movement through space is a fundamental behavior for all animals.
              Cognitive maps of environments are encoded in the hippocampal
              formation in an allocentric reference frame, but motor movements
              that comprise physical navigation are represented within an
              egocentric reference frame. Allocentric navigational plans must
              be converted to an egocentric reference frame prior to
              implementation as overt behavior. Here we describe an egocentric
              spatial representation of environmental boundaries in the
              dorsomedial striatum.",
  journal  = "Nat. Commun.",
  volume   =  10,
  number   =  1,
  pages    = "2772",
  month    =  jun,
  year     =  2019,
  language = "en"
}

@ARTICLE{Groman2019-xc,
  title    = "Orbitofrontal Circuits Control Multiple {Reinforcement-Learning}
              Processes",
  author   = "Groman, Stephanie M and Keistler, Colby and Keip, Alex J and
              Hammarlund, Emma and DiLeone, Ralph J and Pittenger, Christopher
              and Lee, Daeyeol and Taylor, Jane R",
  abstract = "Adaptive decision making in dynamic environments requires
              multiple reinforcement-learning steps that may be implemented by
              dissociable neural circuits. Here, we used a novel directionally
              specific viral ablation approach to investigate the function of
              several anatomically defined orbitofrontal cortex (OFC) circuits
              during adaptive, flexible decision making in rats trained on a
              probabilistic reversal learning task. Ablation of OFC neurons
              projecting to the nucleus accumbens selectively disrupted
              performance following a reversal, by disrupting the use of
              negative outcomes to guide subsequent choices. Ablation of
              amygdala neurons projecting to the OFC also impaired reversal
              performance, but due to disruptions in the use of positive
              outcomes to guide subsequent choices. Ablation of OFC neurons
              projecting to the amygdala, by contrast, enhanced reversal
              performance by destabilizing action values. Our data are
              inconsistent with a unitary function of the OFC in decision
              making. Rather, distinct OFC-amygdala-striatal circuits mediate
              distinct components of the action-value updating and maintenance
              necessary for decision making.",
  journal  = "Neuron",
  month    =  jun,
  year     =  2019,
  keywords = "amygdala; decision making; nucleus accumbens; orbitofrontal
              cortex; reinforcement learning",
  language = "en"
}

@UNPUBLISHED{Johnson2019-wt,
  title    = "Probabilistic Models of Larval Zebrafish Behavior: Structure on
              Many Scales",
  author   = "Johnson, Robert Evan and Linderman, Scott and Panier, Thomas and
              Wee, Caroline Lei and Song, Erin and Herrera, Kristian Joseph and
              Miller, Andrew and Engert, Florian",
  abstract = "Nervous systems have evolved to combine environmental information
              with internal state to select and generate adaptive behavioral
              sequences. To better understand these computations and their
              implementation in neural circuits, natural behavior must be
              carefully measured and quantified. Here, we collect high spatial
              resolution video of single zebrafish larvae swimming in a
              naturalistic environment and develop models of their action
              selection across exploration and hunting. Zebrafish larvae swim
              in punctuated bouts separated by longer periods of rest called
              interbout intervals. We take advantage of this structure by
              categorizing bouts into discrete types and representing their
              behavior as labeled sequences of bout-types emitted over time. We
              then construct probabilistic models - specifically, marked
              renewal processes - to evaluate how bout-types and interbout
              intervals are selected by the fish as a function of its internal
              hunger state, behavioral history, and the locations and
              properties of nearby prey. Finally, we evaluate the models by
              their predictive likelihood and their ability to generate
              realistic trajectories of virtual fish swimming through simulated
              environments. Our simulations capture multiple timescales of
              structure in larval zebrafish behavior and expose many ways in
              which hunger state influences their action selection to promote
              food seeking during hunger and safety during satiety.",
  journal  = "bioRxiv",
  pages    = "672246",
  month    =  jun,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{De_Groot2019-zn,
  title    = "{NINscope}: a versatile miniscope for multi-region circuit
              investigations",
  author   = "de Groot, Andres and van den Boom, Bastijn J G and van Genderen,
              Romano M and Coppens, Joris and van Veldhuijzen, John and Bos,
              Joop and Hoedemaker, Hugo and Negrello, Mario and Wiluhn, Ingo
              and De Zeeuw, Chris I and Hoogland, Tycho M",
  abstract = "Miniaturized fluorescence microscopes (miniscopes) have been
              instrumental to monitor neural activity during unrestrained
              behavior and their open-source versions have helped to distribute
              them at an affordable cost. Generally, the footprint and weight
              of open-source miniscopes is sacrificed for added functionality.
              Here, we present NINscope: a light-weight, small footprint
              open-source miniscope that incorporates a high-sensitivity image
              sensor, an inertial measurement unit (IMU), and an LED driver for
              an external optogenetic probe. We highlight the advantages of
              NINscope by performing the first simultaneous cellular resolution
              (dual scope) recordings from cerebellum and cerebral cortex in
              unrestrained mice, revealing that the activity of both regions
              generally precede the onset of behavioral acceleration. At the
              same time, we demonstrate the optogenetic stimulation
              capabilities of NINscope and show that cerebral cortical activity
              can be driven strongly by cerebellar stimulation. Finally, we
              combine optogenetic stimulation of cortex with imaging in the
              dorsal striatum and replicate previous studies that show action
              space is encoded by neurons in this subcortical region. In
              combination with cross-platform control software NINscope is a
              versatile addition to the expanding toolbox of open-source
              miniscopes and will aid multi-region circuit investigations
              during unrestrained behavior.",
  journal  = "bioRxiv",
  pages    = "685909",
  month    =  jun,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Vertechi2019-bo,
  title    = "Inference based decisions in a hidden state foraging task:
              differential contributions of prefrontal cortical areas",
  author   = "Vertechi, Pietro and Lottem, Eran and Sarra, Dario and Godinho,
              Beatriz and Treves, Isaac and Quendera, Tiago and Lohuis,
              Matthijs Nicolai Oude and Mainen, Zachary F",
  abstract = "Essential features of the world are often hidden and must be
              inferred by constructing internal models based on indirect
              evidence. Here, to study the mechanisms of inference we
              established a foraging task that is naturalistic and easily
              learned, yet can distinguish inference from simpler strategies
              such as the direct integration of sensory data. We show that both
              mice and humans learn a strategy consistent with optimal
              inference of a hidden state. However, humans acquire this
              strategy more than an order of magnitude faster than mice. Using
              optogenetics in mice we show that orbitofrontal and anterior
              cingulate cortex inactivation impact task performance, but only
              orbitofrontal inactivation reverts mice from an inference-based
              to a stimulus-bound decision strategy. These results establish a
              cross-species paradigm for studying the problem of
              inference-based decision-making and begin to dissect the network
              of brain regions crucial for its performance.",
  journal  = "bioRxiv",
  pages    = "679142",
  month    =  jun,
  year     =  2019,
  language = "en"
}

@MISC{noauthor_undated-pm,
  title    = "Refactoring {UI} v1.0.1.pdf",
  keywords = "books"
}

@ARTICLE{Etienne2004-dr,
  title    = "Path integration in mammals",
  author   = "Etienne, Ariane S and Jeffery, Kathryn J",
  abstract = "It is often assumed that navigation implies the use, by animals,
              of landmarks indicating the location of the goal. However, many
              animals (including humans) are able to return to the starting
              point of a journey, or to other goal sites, by relying on
              self-motion cues only. This process is known as path integration,
              and it allows an agent to calculate a route without making use of
              landmarks. We review the current literature on path integration
              and its interaction with external, location-based cues. Special
              importance is given to the correlation between observable
              behavior and the activity pattern of particular neural cell
              populations that implement the internal representation of space.
              In mammals, the latter may well be the first high-level cognitive
              representation to be understood at the neural level.",
  journal  = "Hippocampus",
  volume   =  14,
  number   =  2,
  pages    = "180--192",
  year     =  2004,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Tarsitano1997-jo,
  title    = "Araneophagic jumping spiders discriminate between detour routes
              that do and do not lead to prey",
  author   = "Tarsitano, Michael S and Jackson, Robert R",
  abstract = "In a laboratory study, 12 different experimental set-ups were
              used to examine the ability ofPortia fimbriataa web-invading
              araneophagic jumping spider from Queensland, Australia, to choose
              between two detour paths, only one of which led to a lure (a
              dead, dried spider). Regardless of set-up, the spider could see
              the lure when on the starting platform of the apparatus, but not
              after leaving the starting platform. The spider consistently
              chose the `correct route' (the route that led to the lure) more
              often than the `wrong route' (the route that did not lead to the
              lure). In these tests, the spider was able to make detours that
              required walking about 180° away from the lure and walking past
              where the incorrect route began. There was also a pronounced
              relationship between time of day when tests were carried out and
              the spider's tendency to choose a route. Furthermore, those
              spiders that chose the wrong route abandoned the detour more
              frequently than those that chose the correct route, despite both
              groups being unable to see the lure when the decision was made to
              abandon the detour.",
  journal  = "Anim. Behav.",
  volume   =  53,
  number   =  2,
  pages    = "257--266",
  month    =  feb,
  year     =  1997
}

@ARTICLE{Todorov2004-re,
  title    = "Optimality principles in sensorimotor control",
  author   = "Todorov, Emanuel",
  abstract = "The sensorimotor system is a product of evolution, development,
              learning and adaptation-which work on different time scales to
              improve behavioral performance. Consequently, many theories of
              motor function are based on 'optimal performance': they quantify
              task goals as cost functions, and apply the sophisticated tools
              of optimal control theory to obtain detailed behavioral
              predictions. The resulting models, although not without
              limitations, have explained more empirical phenomena than any
              other class. Traditional emphasis has been on optimizing desired
              movement trajectories while ignoring sensory feedback. Recent
              work has redefined optimality in terms of feedback control laws,
              and focused on the mechanisms that generate behavior online. This
              approach has allowed researchers to fit previously unrelated
              concepts and observations into what may become a unified
              theoretical framework for interpreting motor function. At the
              heart of the framework is the relationship between high-level
              goals, and the real-time sensorimotor control strategies most
              suitable for accomplishing those goals.",
  journal  = "Nat. Neurosci.",
  volume   =  7,
  number   =  9,
  pages    = "907--915",
  month    =  sep,
  year     =  2004,
  language = "en"
}

@ARTICLE{Todorov2009-gp,
  title    = "Efficient computation of optimal actions",
  author   = "Todorov, Emanuel",
  abstract = "Optimal choice of actions is a fundamental problem relevant to
              fields as diverse as neuroscience, psychology, economics,
              computer science, and control engineering. Despite this broad
              relevance the abstract setting is similar: we have an agent
              choosing actions over time, an uncertain dynamical system whose
              state is affected by those actions, and a performance criterion
              that the agent seeks to optimize. Solving problems of this kind
              remains hard, in part, because of overly generic formulations.
              Here, we propose a more structured formulation that greatly
              simplifies the construction of optimal control laws in both
              discrete and continuous domains. An exhaustive search over
              actions is avoided and the problem becomes linear. This yields
              algorithms that outperform Dynamic Programming and Reinforcement
              Learning, and thereby solve traditional problems more
              efficiently. Our framework also enables computations that were
              not possible before: composing optimal control laws by mixing
              primitives, applying deterministic methods to stochastic systems,
              quantifying the benefits of error tolerance, and inferring goals
              from behavioral data via convex optimization. Development of a
              general class of easily solvable problems tends to accelerate
              progress--as linear systems theory has done, for example. Our
              framework may have similar impact in fields where optimal choice
              of actions is relevant.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  106,
  number   =  28,
  pages    = "11478--11483",
  month    =  jul,
  year     =  2009,
  language = "en"
}

@ARTICLE{Sanfey2006-em,
  title    = "Neuroeconomics: cross-currents in research on decision-making",
  author   = "Sanfey, Alan G and Loewenstein, George and McClure, Samuel M and
              Cohen, Jonathan D",
  abstract = "Despite substantial advances, the question of how we make
              decisions and judgments continues to pose important challenges
              for scientific research. Historically, different disciplines have
              approached this problem using different techniques and
              assumptions, with few unifying efforts made. However, the field
              of neuroeconomics has recently emerged as an inter-disciplinary
              effort to bridge this gap. Research in neuroscience and
              psychology has begun to investigate neural bases of decision
              predictability and value, central parameters in the economic
              theory of expected utility. Economics, in turn, is being
              increasingly influenced by a multiple-systems approach to
              decision-making, a perspective strongly rooted in psychology and
              neuroscience. The integration of these disparate theoretical
              approaches and methodologies offers exciting potential for the
              construction of more accurate models of decision-making.",
  journal  = "Trends Cogn. Sci.",
  volume   =  10,
  number   =  3,
  pages    = "108--116",
  month    =  mar,
  year     =  2006,
  language = "en"
}

@ARTICLE{Padoa-Schioppa2006-ps,
  title     = "Neurons in the orbitofrontal cortex encode economic value",
  author    = "Padoa-Schioppa, Camillo and Assad, John A",
  abstract  = "Economic choice is the behaviour observed when individuals
               select one among many available options. There is no
               intrinsically 'correct' answer: economic choice depends on
               subjective preferences. This behaviour is traditionally the
               object of economic analysis and is also of primary interest in
               psychology. However, the underlying mental processes and
               neuronal mechanisms are not well understood. Theories of human
               and animal choice have a cornerstone in the concept of 'value'.
               Consider, for example, a monkey offered one raisin versus one
               piece of apple: behavioural evidence suggests that the animal
               chooses by assigning values to the two options. But where and
               how values are represented in the brain is unclear. Here we show
               that, during economic choice, neurons in the orbitofrontal
               cortex (OFC) encode the value of offered and chosen goods.
               Notably, OFC neurons encode value independently of visuospatial
               factors and motor responses. If a monkey chooses between A and
               B, neurons in the OFC encode the value of the two goods
               independently of whether A is presented on the right and B on
               the left, or vice versa. This trait distinguishes the OFC from
               other brain areas in which value modulates activity related to
               sensory or motor processes. Our results have broad implications
               for possible psychological models, suggesting that economic
               choice is essentially choice between goods rather than choice
               between actions. In this framework, neurons in the OFC seem to
               be a good candidate network for value assignment underlying
               economic choice.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  441,
  number    =  7090,
  pages     = "223--226",
  month     =  may,
  year      =  2006,
  language  = "en"
}

@ARTICLE{Clark_undated-kw,
  title    = "Putting Brain, Body, and World Together Again",
  author   = "Clark, Andy",
  keywords = "Books"
}

@UNPUBLISHED{Obaid2019-jn,
  title    = "Massively Parallel Microwire Arrays Integrated with {CMOS} chips
              for Neural Recording",
  author   = "Obaid, Abdulmalik and Hanna, Mina-Elraheb and Wu, Yu-Wei and
              Kollo, Mihaly and Racz, Romeo and Angle, Matthew R and
              M{\"u}ller, Jan and Brackbill, Nora and Wray, William and Franke,
              Felix and Chichilinsky, E J and Hierlemann, Andreas and Ding, Jun
              B and Schaefer, Andreas T and Melosh, Nicholas A",
  abstract = "Abstract Multiple-channel count neural recordings of brain
              activity are a powerful technique that is increasingly uncovering
              new aspects of neural communication, computation, and prosthetic
              interfaces. However, while silicon CMOS devices continue to scale
              rapidly in number and power in planar geometries, this scaling
              has not been followed for large-scale mapping along three
              dimensions. Here, we present a new strategy to interface
              CMOS-based devices with a three-dimensional microwire array,
              providing the link between rapidly-developing electronics, and
              high density neural interfaces. The system consists of a bundle
              of insulated and spaced microwires perpendicularly mated to a
              commercial large-scale CMOS microelectrode array, such as a
              camera chip. The modular nature of the design enables a variety
              of microwire types and sizes to be integrated with different
              types of silicon-based arrays, allowing channel counts to be
              scaled from a few dozen to thousands of electrodes using the same
              fundamental platform. This system has excellent recording
              performance, demonstrated via single unit and local-field
              potential recordings in isolated retina, and in the motor cortex
              and striatum of awake moving mice. This concept links the rapid
              progress and power of commercial multiplexing, digitisation and
              data acquisition hardware together with a three-dimensional
              neural interface.",
  journal  = "bioRxiv",
  pages    = "573295",
  month    =  mar,
  year     =  2019,
  language = "en"
}

@ARTICLE{Gold2007-tn,
  title     = "The neural basis of decision making",
  author    = "Gold, Joshua I and Shadlen, Michael N",
  abstract  = "The study of decision making spans such varied fields as
               neuroscience, psychology, economics, statistics, political
               science, and computer science. Despite this diversity of
               applications, most decisions share common elements including
               deliberation and commitment. Here we evaluate recent progress in
               understanding how these basic elements of decision formation are
               implemented in the brain. We focus on simple decisions that can
               be studied in the laboratory but emphasize general principles
               likely to extend to other settings.",
  journal   = "Annu. Rev. Neurosci.",
  publisher = "annualreviews.org",
  volume    =  30,
  pages     = "535--574",
  year      =  2007,
  language  = "en"
}

@ARTICLE{Smith2004-ti,
  title    = "Psychology and neurobiology of simple decisions",
  author   = "Smith, Philip L and Ratcliff, Roger",
  abstract = "Patterns of neural firing linked to eye movement decisions show
              that behavioral decisions are predicted by the differential
              firing rates of cells coding selected and nonselected stimulus
              alternatives. These results can be interpreted using models
              developed in mathematical psychology to model behavioral
              decisions. Current models assume that decisions are made by
              accumulating noisy stimulus information until sufficient
              information for a response is obtained. Here, the models, and the
              techniques used to test them against response-time distribution
              and accuracy data, are described. Such models provide a
              quantitative link between the time-course of behavioral decisions
              and the growth of stimulus information in neural firing data.",
  journal  = "Trends Neurosci.",
  volume   =  27,
  number   =  3,
  pages    = "161--168",
  month    =  mar,
  year     =  2004,
  language = "en"
}

@ARTICLE{Gold2002-rg,
  title    = "Banburismus and the brain: decoding the relationship between
              sensory stimuli, decisions, and reward",
  author   = "Gold, Joshua I and Shadlen, Michael N",
  abstract = "This article relates a theoretical framework developed by British
              codebreakers in World War II to the neural computations thought
              to be responsible for forming categorical decisions about sensory
              stimuli. In both, a weight of evidence is computed and
              accumulated to support or oppose the alternative interpretations.
              A decision is reached when the evidence reaches a threshold
              value. In the codebreaking scheme, the threshold determined the
              speed and accuracy of the decision process. Here we propose that
              in the brain, the threshold may be controlled by neural circuits
              that calculate the rate of reward.",
  journal  = "Neuron",
  volume   =  36,
  number   =  2,
  pages    = "299--308",
  month    =  oct,
  year     =  2002,
  language = "en"
}

@ARTICLE{Constantinople2019-hd,
  title    = "An Analysis of Decision under Risk in Rats",
  author   = "Constantinople, Christine M and Piet, Alex T and Brody, Carlos D",
  abstract = "In 1979, Daniel Kahneman and Amos Tversky published a
              ground-breaking paper titled ``Prospect Theory: An Analysis of
              Decision under Risk,'' which presented a behavioral economic
              theory that accounted for the ways in which humans deviate from
              economists' normative workhorse model, Expected Utility Theory
              [1, 2]. For example, people exhibit probability distortion (they
              overweight low probabilities), loss aversion (losses loom larger
              than gains), and reference dependence (outcomes are evaluated as
              gains or losses relative to an internal reference point). We
              found that rats exhibited many of these same biases, using a task
              in which rats chose between guaranteed and probabilistic rewards.
              However, prospect theory assumes stable preferences in the
              absence of learning, an assumption at odds with alternative
              frameworks such as animal learning theory and reinforcement
              learning [3-7]. Rats also exhibited trial history effects,
              consistent with ongoing learning. A reinforcement learning model
              in which state-action values were updated by the subjective value
              of outcomes according to prospect theory reproduced rats'
              nonlinear utility and probability weighting functions and also
              captured trial-by-trial learning dynamics.",
  journal  = "Curr. Biol.",
  volume   =  29,
  number   =  12,
  pages    = "2066--2074.e5",
  month    =  jun,
  year     =  2019,
  keywords = "computational model; decision-making; prospect theory; rat
              behavior; reinforcement learning; reward; subjective value",
  language = "en"
}

@ARTICLE{Trommershauser2003-gp,
  title     = "Statistical decision theory and the selection of rapid,
               goal-directed movements",
  author    = "Trommersh{\"a}user, Julia and Maloney, Laurence T and Landy,
               Michael S",
  abstract  = "We present two experiments that test the range of applicability
               of a movement planning model (MEGaMove) based on statistical
               decision theory. Subjects attempted to earn money by rapidly
               touching a green target region on a computer screen while
               avoiding nearby red penalty regions. In two experiments we
               varied the magnitudes of penalties, the degree of overlap of
               target and penalty regions, and the number of penalty regions.
               Overall, subjects acted so as to maximize gain in a wide variety
               of stimulus configurations, in good agreement with predictions
               of the model.",
  journal   = "J. Opt. Soc. Am. A Opt. Image Sci. Vis.",
  publisher = "osapublishing.org",
  volume    =  20,
  number    =  7,
  pages     = "1419--1433",
  month     =  jul,
  year      =  2003,
  language  = "en"
}

@ARTICLE{Vilares2011-lp,
  title    = "Bayesian models: the structure of the world, uncertainty,
              behavior, and the brain",
  author   = "Vilares, Iris and Kording, Konrad",
  abstract = "Experiments on humans and other animals have shown that
              uncertainty due to unreliable or incomplete information affects
              behavior. Recent studies have formalized uncertainty and asked
              which behaviors would minimize its effect. This formalization
              results in a wide range of Bayesian models that derive from
              assumptions about the world, and it often seems unclear how these
              models relate to one another. In this review, we use the concept
              of graphical models to analyze differences and commonalities
              across Bayesian approaches to the modeling of behavioral and
              neural data. We review behavioral and neural data associated with
              each type of Bayesian model and explain how these models can be
              related. We finish with an overview of different theories that
              propose possible ways in which the brain can represent
              uncertainty.",
  journal  = "Ann. N. Y. Acad. Sci.",
  volume   =  1224,
  pages    = "22--39",
  month    =  apr,
  year     =  2011,
  language = "en"
}

@ARTICLE{Kording2004-ii,
  title    = "The loss function of sensorimotor learning",
  author   = "K{\"o}rding, Konrad Paul and Wolpert, Daniel M",
  abstract = "Motor learning can be defined as changing performance so as to
              optimize some function of the task, such as accuracy. The measure
              of accuracy that is optimized is called a loss function and
              specifies how the CNS rates the relative success or cost of a
              particular movement outcome. Models of pointing in sensorimotor
              control and learning usually assume a quadratic loss function in
              which the mean squared error is minimized. Here we develop a
              technique for measuring the loss associated with errors. Subjects
              were required to perform a task while we experimentally
              controlled the skewness of the distribution of errors they
              experienced. Based on the change in the subjects' average
              performance, we infer the loss function. We show that people use
              a loss function in which the cost increases approximately
              quadratically with error for small errors and significantly less
              than quadratically for large errors. The system is thus robust to
              outliers. This suggests that models of sensorimotor control and
              learning that have assumed minimizing squared error are a good
              approximation but tend to penalize large errors excessively.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  101,
  number   =  26,
  pages    = "9839--9842",
  month    =  jun,
  year     =  2004,
  language = "en"
}

@ARTICLE{Ortega_Pedro_A2013-ub,
  title     = "Thermodynamics as a theory of decision-making with
               information-processing costs",
  author    = "{Ortega Pedro A.} and {Braun Daniel A.}",
  journal   = "Proceedings of the Royal Society A: Mathematical, Physical and
               Engineering Sciences",
  publisher = "Royal Society",
  volume    =  469,
  number    =  2153,
  pages     = "20120683",
  month     =  may,
  year      =  2013
}

@ARTICLE{Kording2004-ui,
  title    = "A neuroeconomics approach to inferring utility functions in
              sensorimotor control",
  author   = "K{\"o}rding, Konrad P and Fukunaga, Izumi and Howard, Ian S and
              Ingram, James N and Wolpert, Daniel M",
  abstract = "Making choices is a fundamental aspect of human life. For over a
              century experimental economists have characterized the decisions
              people make based on the concept of a utility function. This
              function increases with increasing desirability of the outcome,
              and people are assumed to make decisions so as to maximize
              utility. When utility depends on several variables, indifference
              curves arise that represent outcomes with identical utility that
              are therefore equally desirable. Whereas in economics utility is
              studied in terms of goods and services, the sensorimotor system
              may also have utility functions defining the desirability of
              various outcomes. Here, we investigate the indifference curves
              when subjects experience forces of varying magnitude and
              duration. Using a two-alternative forced-choice paradigm, in
              which subjects chose between different magnitude-duration
              profiles, we inferred the indifference curves and the utility
              function. Such a utility function defines, for example, whether
              subjects prefer to lift a 4-kg weight for 30 s or a 1-kg weight
              for a minute. The measured utility function depends nonlinearly
              on the force magnitude and duration and was remarkably conserved
              across subjects. This suggests that the utility function, a
              central concept in economics, may be applicable to the study of
              sensorimotor control.",
  journal  = "PLoS Biol.",
  volume   =  2,
  number   =  10,
  pages    = "e330",
  month    =  oct,
  year     =  2004,
  language = "en"
}

@ARTICLE{Kording2006-ty,
  title    = "Bayesian decision theory in sensorimotor control",
  author   = "K{\"o}rding, Konrad P and Wolpert, Daniel M",
  abstract = "Action selection is a fundamental decision process for us, and
              depends on the state of both our body and the environment.
              Because signals in our sensory and motor systems are corrupted by
              variability or noise, the nervous system needs to estimate these
              states. To select an optimal action these state estimates need to
              be combined with knowledge of the potential costs or rewards of
              different action outcomes. We review recent studies that have
              investigated the mechanisms used by the nervous system to solve
              such estimation and decision problems, which show that human
              behaviour is close to that predicted by Bayesian Decision Theory.
              This theory defines optimal behaviour in a world characterized by
              uncertainty, and provides a coherent way of describing
              sensorimotor processes.",
  journal  = "Trends Cogn. Sci.",
  volume   =  10,
  number   =  7,
  pages    = "319--326",
  month    =  jul,
  year     =  2006,
  language = "en"
}

@ARTICLE{McNamara2006-sr,
  title    = "Bayes' theorem and its applications in animal behaviour",
  author   = "McNamara, John M and Green, Richard F and Olsson, Ola",
  abstract = "Bayesian decision theory can be used to model animal behaviour.
              In this paper we give an overview of the theoretical concepts in
              such models. We also review the biological contexts in which
              Bayesian models have been applied, and outline some directions
              where future studies would be useful. Bayesian decision theory,
              when applied to animal behaviour, is based on the assumption that
              the individual has some sort of ?prior opinion? of the possible
              states of the world. This may, for example, be a previously
              experienced distribution of qualities of food patches, or
              qualities of potential mates. The animal is then assumed to be
              able use sampling information to arrive at a ?posterior opinion?,
              concerning e.g. the quality of a given food patch, or the average
              qualities of mates in a year. A correctly formulated Bayesian
              model predicts how animals may combine previous experience with
              sampling information to make optimal decisions. We argue that the
              assumption that animals may have ?prior opinions? is reasonable.
              Their priors may come from one or both of two sources: either
              from their own individual experience, gained while sampling the
              environment, or from an adaptation to the environment experienced
              by previous generations. This means that we should often expect
              to see ?Bayesian-like? decision-making in nature.",
  journal  = "Oikos",
  volume   =  112,
  number   =  2,
  pages    = "243--251",
  month    =  feb,
  year     =  2006
}

@ARTICLE{Bogacz2007-hx,
  title    = "Optimal decision-making theories: linking neurobiology with
              behaviour",
  author   = "Bogacz, Rafal",
  abstract = "This article reviews recently proposed theories postulating that,
              during simple choices, the brain performs statistically optimal
              decision making. These theories are ecologically motivated by
              evolutionary pressures to optimize the speed and accuracy of
              decisions and to maximize the rate of receiving rewards for
              correct choices. This article suggests that the models of
              decision making that are proposed on different levels of
              abstraction can be linked by virtue of the same optimal
              computation. Also reviewed here are recent observations that many
              aspects of the circuit that involves the cortex and basal ganglia
              are the same as those that are required to perform statistically
              optimal choice. This review illustrates how optimal-decision
              theories elucidate current data and provide experimental
              predictions that concern both neurobiology and behaviour.",
  journal  = "Trends Cogn. Sci.",
  volume   =  11,
  number   =  3,
  pages    = "118--125",
  month    =  mar,
  year     =  2007,
  language = "en"
}

@ARTICLE{Clarke2015-kk,
  title    = "Human and machine learning in non-Markovian decision making",
  author   = "Clarke, Aaron Michael and Friedrich, Johannes and Tartaglia,
              Elisa M and Marchesotti, Silvia and Senn, Walter and Herzog,
              Michael H",
  abstract = "Humans can learn under a wide variety of feedback conditions.
              Reinforcement learning (RL), where a series of rewarded decisions
              must be made, is a particularly important type of learning.
              Computational and behavioral studies of RL have focused mainly on
              Markovian decision processes, where the next state depends on
              only the current state and action. Little is known about
              non-Markovian decision making, where the next state depends on
              more than the current state and action. Learning is
              non-Markovian, for example, when there is no unique mapping
              between actions and feedback. We have produced a model based on
              spiking neurons that can handle these non-Markovian conditions by
              performing policy gradient descent [1]. Here, we examine the
              model's performance and compare it with human learning and a
              Bayes optimal reference, which provides an upper-bound on
              performance. We find that in all cases, our population of spiking
              neurons model well-describes human performance.",
  journal  = "PLoS One",
  volume   =  10,
  number   =  4,
  pages    = "e0123105",
  month    =  apr,
  year     =  2015,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{McNamara1980-xn,
  title     = "The application of statistical decision theory to animal
               behaviour",
  author    = "McNamara, J and Houston, A",
  abstract  = "Statistical decision theory is discussed as a general framework
               for analysing how animals should learn. Attention is focused on
               optimal foraging behaviour in stochastic environments. We
               emphasise the distinction between the mathematical procedure
               that can be used to find optimal solutions and the mechanism an
               animal might use to implement such solutions. The mechanisms
               might be specific to a restricted class of problems and produce
               suboptimal behaviour when faced with problems outside this
               class. We illustrate this point by an …",
  journal   = "J. Theor. Biol.",
  publisher = "Elsevier",
  volume    =  85,
  number    =  4,
  pages     = "673--690",
  month     =  aug,
  year      =  1980,
  language  = "en"
}

@INPROCEEDINGS{Rothkopf2011-xk,
  title     = "Preference Elicitation and Inverse Reinforcement Learning",
  booktitle = "Machine Learning and Knowledge Discovery in Databases",
  author    = "Rothkopf, Constantin A and Dimitrakakis, Christos",
  abstract  = "We state the problem of inverse reinforcement learning in terms
               of preference elicitation, resulting in a principled (Bayesian)
               statistical formulation. This generalises previous work on
               Bayesian inverse reinforcement learning and allows us to obtain
               a posterior distribution on the agent's preferences, policy and
               optionally, the obtained reward sequence, from observations. We
               examine the relation of the resulting approach to other
               statistical methods for inverse reinforcement learning via
               analysis and experimental results. We show that preferences can
               be determined accurately, even if the observed agent's policy is
               sub-optimal with respect to its own preferences. In that case,
               significantly improved policies with respect to the agent's
               preferences are obtained, compared to both other methods and to
               the performance of the demonstrated policy.",
  publisher = "Springer Berlin Heidelberg",
  pages     = "34--48",
  year      =  2011
}

@ARTICLE{McFarland1977-gm,
  title    = "Decision making in animals",
  author   = "McFarland, D J",
  abstract = "Animals must make decisions about when to feed, when to court,
              when to sleep, and so on, in such a way as to maximise as far as
              possible their chances of survival and reproductive success. It
              is possible to formulate in mathematical terms the optimal
              strategy for an animal to pursue. The theoretical optimum
              behaviour can be compared with the actual behaviour of the
              animal, and perhaps shed some light on the evolution of
              behaviour.",
  journal  = "Nature",
  volume   =  269,
  number   =  5623,
  pages    = "15--21",
  month    =  sep,
  year     =  1977
}

@ARTICLE{Daunizeau2010-kj,
  title    = "Observing the observer (I): meta-bayesian models of learning and
              decision-making",
  author   = "Daunizeau, Jean and den Ouden, Hanneke E M and Pessiglione,
              Matthias and Kiebel, Stefan J and Stephan, Klaas E and Friston,
              Karl J",
  abstract = "In this paper, we present a generic approach that can be used to
              infer how subjects make optimal decisions under uncertainty. This
              approach induces a distinction between a subject's perceptual
              model, which underlies the representation of a hidden ``state of
              affairs'' and a response model, which predicts the ensuing
              behavioural (or neurophysiological) responses to those inputs. We
              start with the premise that subjects continuously update a
              probabilistic representation of the causes of their sensory
              inputs to optimise their behaviour. In addition, subjects have
              preferences or goals that guide decisions about actions given the
              above uncertain representation of these hidden causes or state of
              affairs. From a Bayesian decision theoretic perspective,
              uncertain representations are so-called ``posterior'' beliefs,
              which are influenced by subjective ``prior'' beliefs. Preferences
              and goals are encoded through a ``loss'' (or ``utility'')
              function, which measures the cost incurred by making any
              admissible decision for any given (hidden) state of affair. By
              assuming that subjects make optimal decisions on the basis of
              updated (posterior) beliefs and utility (loss) functions, one can
              evaluate the likelihood of observed behaviour. Critically, this
              enables one to ``observe the observer'', i.e. identify (context-
              or subject-dependent) prior beliefs and utility-functions using
              psychophysical or neurophysiological measures. In this paper, we
              describe the main theoretical components of this meta-Bayesian
              approach (i.e. a Bayesian treatment of Bayesian decision
              theoretic predictions). In a companion paper ('Observing the
              observer (II): deciding when to decide'), we describe a concrete
              implementation of it and demonstrate its utility by applying it
              to simulated and real reaction time data from an associative
              learning task.",
  journal  = "PLoS One",
  volume   =  5,
  number   =  12,
  pages    = "e15554",
  month    =  dec,
  year     =  2010,
  language = "en"
}

@ARTICLE{noauthor_undated-nr,
  title = "Goal Inference as Inverse Planning"
}

@ARTICLE{J_Valone2006-fh,
  title    = "Are animals capable of Bayesian updating? An empirical review",
  author   = "J. Valone, Thomas",
  abstract = "Numerous behavioral models assume individuals combine knowledge
              in the form of a prior distribution with current sample
              information using Bayesian updating to estimate the quality of
              environmental parameters. I examine this assumption by reviewing
              11 empirical studies. Six studies compared observed behavior to
              predictions of Bayesian and non-Bayesian models, while five
              studies manipulated prior distributions directly and observed how
              such manipulations altered behavior. Eight species of birds,
              three mammals, one fish and one insect exhibited behavior
              consistent with Bayesian updating models; one studied bird
              species failed to show evidence of Bayesian updating. Most
              studies examined how individuals estimated food patch quality but
              two investigated mating decisions. These studies suggest a
              variety of animals in different ecological contexts behave in
              manners consistent with predictions of Bayesian updating models.
              Future work on decision-making should focus on understanding how
              animals learn prior distributions and on decision-making in
              additional ecological contexts.",
  journal  = "Oikos",
  volume   =  112,
  number   =  2,
  pages    = "252--259",
  month    =  feb,
  year     =  2006
}

@ARTICLE{Franks2006-ul,
  title     = "Not everything that counts can be counted: ants use multiple
               metrics for a single nest trait",
  author    = "Franks, Nigel R and Dornhaus, Anna and Metherell, Bonnie G and
               Nelson, Toby R and Lanfear, Sophie A J and Symes, William S",
  abstract  = "There are claims in the literature that certain insects can
               count. We question the generality of these claims and suggest
               that summation rather than counting (sensu stricto) is a more
               likely explanation. We show that Temnothorax albipennis ant
               colonies can discriminate between potential nest sites with
               different numbers of entrances. However, our experiments suggest
               that the ants use ambient light levels within the nest cavity to
               assess the abundance of nest entrances rather than counting per
               se. Intriguingly, Weber's Law cannot explain the ants'
               inaccuracy. The ants also use a second metric, independent of
               light, to assess and discriminate against wide entrances. Thus,
               these ants use at least two metrics to evaluate one nest trait:
               the configuration of the portals to their potential homes.",
  journal   = "Proc. Biol. Sci.",
  publisher = "royalsocietypublishing.org",
  volume    =  273,
  number    =  1583,
  pages     = "165--169",
  month     =  jan,
  year      =  2006,
  language  = "en"
}

@ARTICLE{Trimmer_Pete_C2008-ht,
  title     = "Mammalian choices: combining fast-but-inaccurate and
               slow-but-accurate decision-making systems",
  author    = "{Trimmer Pete C} and {Houston Alasdair I} and {Marshall James
               A.R} and {Bogacz Rafal} and {Paul Elizabeth S} and {Mendl Mike
               T} and {McNamara John M}",
  journal   = "Proceedings of the Royal Society B: Biological Sciences",
  publisher = "Royal Society",
  volume    =  275,
  number    =  1649,
  pages     = "2353--2361",
  month     =  oct,
  year      =  2008
}

@ARTICLE{Trimmer2011-pv,
  title     = "Decision-making under uncertainty: biases and Bayesians",
  author    = "Trimmer, Pete C and Houston, Alasdair I and Marshall, James A R
               and Mendl, Mike T and Paul, Elizabeth S and McNamara, John M",
  abstract  = "Animals (including humans) often face circumstances in which the
               best choice of action is not certain. Environmental cues may be
               ambiguous, and choices may be risky. This paper reviews the
               theoretical side of decision-making under uncertainty,
               particularly with regard to unknown risk (ambiguity). We use
               simple models to show that, irrespective of pay-offs, whether it
               is optimal to bias probability estimates depends upon how those
               estimates have been generated. In particular, if estimates have
               been calculated in a Bayesian framework with a sensible prior,
               it is best to use unbiased estimates. We review the extent of
               evidence for and against viewing animals (including humans) as
               Bayesian decision-makers. We pay particular attention to the
               Ellsberg Paradox, a classic result from experimental economics,
               in which human subjects appear to deviate from optimal
               decision-making by demonstrating an apparent aversion to
               ambiguity in a choice between two options with equal expected
               rewards. The paradox initially seems to be an example where
               decision-making estimates are biased relative to the Bayesian
               optimum. We discuss the extent to which the Bayesian paradigm
               might be applied to the evolution of decision-makers and how the
               Ellsberg Paradox may, with a deeper understanding, be resolved.",
  journal   = "Anim. Cogn.",
  publisher = "Springer",
  volume    =  14,
  number    =  4,
  pages     = "465--476",
  month     =  jul,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Kording2007-va,
  title    = "Decision theory: what ``should'' the nervous system do?",
  author   = "K{\"o}rding, Konrad",
  abstract = "The purpose of our nervous system is to allow us to successfully
              interact with our environment. This normative idea is formalized
              by decision theory that defines which choices would be most
              beneficial. We live in an uncertain world, and each decision may
              have many possible outcomes; choosing the best decision is thus
              complicated. Bayesian decision theory formalizes these problems
              in the presence of uncertainty and often provides compact models
              that predict observed behavior. With its elegant formalization of
              the problems faced by the nervous system, it promises to become a
              major inspiration for studies in neuroscience.",
  journal  = "Science",
  volume   =  318,
  number   =  5850,
  pages    = "606--610",
  month    =  oct,
  year     =  2007,
  language = "en"
}

@ARTICLE{Seth_Anil_K2007-vj,
  title     = "The ecology of action selection: insights from artificial life",
  author    = "{Seth Anil K}",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "Royal Society",
  volume    =  362,
  number    =  1485,
  pages     = "1545--1558",
  month     =  sep,
  year      =  2007
}

@ARTICLE{Bogacz_Rafal2007-kq,
  title     = "Extending a biologically inspired model of choice:
               multi-alternatives, nonlinearity and value-based
               multidimensional choice",
  author    = "{Bogacz Rafal} and {Usher Marius} and {Zhang Jiaxiang} and
               {McClelland James L}",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "Royal Society",
  volume    =  362,
  number    =  1485,
  pages     = "1655--1670",
  month     =  sep,
  year      =  2007
}

@INPROCEEDINGS{Gordon2004-gu,
  title     = "Evolving sparse direction maps for maze pathfinding",
  booktitle = "Proceedings of the 2004 Congress on Evolutionary Computation
               ({IEEE} Cat. {No.04TH8753})",
  author    = "Gordon, V S and Matley, Z",
  abstract  = "A genetic algorithm is used to solve a class of maze pathfinding
               problems. In particular, we find a complete set of paths
               directing an agent from any position in the maze towards a
               single goal. To this end, we define a sparse direction map,
               wherein the maze is divided into sectors, each of which contains
               a direction indicator. Maps are evolved using a simple genetic
               algorithm. The fitness function samples the efficacy of the map
               from random starting points, this estimating the likelihood that
               agents find the goal. The framework was effective in evolving
               successful maps for three different mazes of varying size and
               complexity, resulting in interesting and lifelike agent behavior
               suitable for games, but not always the shortest paths.",
  volume    =  1,
  pages     = "835--838 Vol.1",
  month     =  jun,
  year      =  2004,
  keywords  = "genetic algorithms;path planning;game theory;graph theory;sparse
               direction maps;maze pathfinding;genetic algorithm;fitness
               function;shortest paths;direction indicator;agent
               behavior;Genetic algorithms;Filling;Counting circuits;Computer
               science;Delay"
}

@ARTICLE{Jaafar2008-us,
  title   = "A Fuzzy Action Selection Method for Virtual Agent Navigation in
             Unknown Virtual Environments",
  author  = "Jaafar, Jafreezal and Mc Kenzie, Eric",
  journal = "Plan. Perspect.",
  volume  =  144,
  pages   = "154",
  year    =  2008
}

@ARTICLE{Caillerie_undated-bp,
  title  = "Geodesic trail formation in a two-dimensional model of foraging
            ants with directed pheromones",
  author = "Caillerie, Nils"
}

@ARTICLE{Deneubourg1989-ff,
  title     = "Collective patterns and decision-making",
  author    = "Deneubourg, J L and Goss, S",
  abstract  = "Autocatalytic interactions between the members of an animal
               group or society, and particularly chemically or visually
               mediated allelomimesis, can be an important factor in the
               organisation of their collective activity. Furthermore, the
               interactions between the individuals and the environment allow
               different collective patterns and decisions to appear under
               different conditions, with the same individual behaviour. While
               most clearly demonstrable in social insects, these principles
               are fundamental to schools of fishes, flocks of birds, groups of
               mammals, and many other social aggregates. The analysis of
               collective behaviour in these terms implies detailed observation
               of both individual and collective behaviour, combined with
               mathematical modelling to link the two.",
  journal   = "Ethol. Ecol. Evol.",
  publisher = "Taylor \& Francis",
  volume    =  1,
  number    =  4,
  pages     = "295--311",
  month     =  dec,
  year      =  1989
}

@MISC{Anil_K_Seth_Tony_J_Prescott_Joanna_J_Bryson_undated-eg,
  title    = "Modelling Natural Action Selection",
  author   = "{Anil K. Seth, Tony J. Prescott, Joanna J. Bryson}",
  keywords = "books;Books"
}

@ARTICLE{Maisto_Domenico2015-mt,
  title     = "Divide et impera: subgoaling reduces the complexity of
               probabilistic inference and problem solving",
  author    = "{Maisto Domenico} and {Donnarumma Francesco} and {Pezzulo
               Giovanni}",
  journal   = "J. R. Soc. Interface",
  publisher = "Royal Society",
  volume    =  12,
  number    =  104,
  pages     = "20141335",
  month     =  mar,
  year      =  2015
}

@ARTICLE{Russek2017-vt,
  title    = "Predictive representations can link model-based reinforcement
              learning to model-free mechanisms",
  author   = "Russek, Evan M and Momennejad, Ida and Botvinick, Matthew M and
              Gershman, Samuel J and Daw, Nathaniel D",
  abstract = "Humans and animals are capable of evaluating actions by
              considering their long-run future rewards through a process
              described using model-based reinforcement learning (RL)
              algorithms. The mechanisms by which neural circuits perform the
              computations prescribed by model-based RL remain largely unknown;
              however, multiple lines of evidence suggest that neural circuits
              supporting model-based behavior are structurally homologous to
              and overlapping with those thought to carry out model-free
              temporal difference (TD) learning. Here, we lay out a family of
              approaches by which model-based computation may be built upon a
              core of TD learning. The foundation of this framework is the
              successor representation, a predictive state representation that,
              when combined with TD learning of value predictions, can produce
              a subset of the behaviors associated with model-based learning,
              while requiring less decision-time computation than dynamic
              programming. Using simulations, we delineate the precise
              behavioral capabilities enabled by evaluating actions using this
              approach, and compare them to those demonstrated by biological
              organisms. We then introduce two new algorithms that build upon
              the successor representation while progressively mitigating its
              limitations. Because this framework can account for the full
              range of observed putatively model-based behaviors while still
              utilizing a core TD framework, we suggest that it represents a
              neurally plausible family of mechanisms for model-based
              evaluation.",
  journal  = "PLoS Comput. Biol.",
  volume   =  13,
  number   =  9,
  pages    = "e1005768",
  month    =  sep,
  year     =  2017,
  language = "en"
}

@ARTICLE{Daw2014-uh,
  title    = "The algorithmic anatomy of model-based evaluation",
  author   = "Daw, Nathaniel D and Dayan, Peter",
  abstract = "Despite many debates in the first half of the twentieth century,
              it is now largely a truism that humans and other animals build
              models of their environments and use them for prediction and
              control. However, model-based (MB) reasoning presents severe
              computational challenges. Alternative, computationally simpler,
              model-free (MF) schemes have been suggested in the reinforcement
              learning literature, and have afforded influential accounts of
              behavioural and neural data. Here, we study the realization of MB
              calculations, and the ways that this might be woven together with
              MF values and evaluation methods. There are as yet mostly only
              hints in the literature as to the resulting tapestry, so we offer
              more preview than review.",
  journal  = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  volume   =  369,
  number   =  1655,
  month    =  nov,
  year     =  2014,
  keywords = "Monte Carlo tree search; model-based reasoning; model-free
              reasoning; orbitofrontal cortex; reinforcement learning; striatum",
  language = "en"
}

@ARTICLE{Friston2017-ib,
  title    = "Active Inference: A Process Theory",
  author   = "Friston, Karl and FitzGerald, Thomas and Rigoli, Francesco and
              Schwartenbeck, Philipp and Pezzulo, Giovanni",
  abstract = "This article describes a process theory based on active inference
              and belief propagation. Starting from the premise that all
              neuronal processing (and action selection) can be explained by
              maximizing Bayesian model evidence-or minimizing variational free
              energy-we ask whether neuronal responses can be described as a
              gradient descent on variational free energy. Using a standard
              (Markov decision process) generative model, we derive the
              neuronal dynamics implicit in this description and reproduce a
              remarkable range of well-characterized neuronal phenomena. These
              include repetition suppression, mismatch negativity, violation
              responses, place-cell activity, phase precession, theta
              sequences, theta-gamma coupling, evidence accumulation,
              race-to-bound dynamics, and transfer of dopamine responses.
              Furthermore, the (approximately Bayes' optimal) behavior
              prescribed by these dynamics has a degree of face validity,
              providing a formal explanation for reward seeking, context
              learning, and epistemic foraging. Technically, the fact that a
              gradient descent appears to be a valid description of neuronal
              activity means that variational free energy is a Lyapunov
              function for neuronal dynamics, which therefore conform to
              Hamilton's principle of least action.",
  journal  = "Neural Comput.",
  volume   =  29,
  number   =  1,
  pages    = "1--49",
  month    =  jan,
  year     =  2017,
  language = "en"
}

@UNPUBLISHED{Miller2018-ag,
  title    = "Habits without Values",
  author   = "Miller, Kevin and Shenhav, Amitai and Ludvig, Elliot",
  abstract = "Habits form a crucial component of behavior. In recent years, key
              computational models have conceptualized habits as arising from
              model-free reinforcement learning (RL) mechanisms, which
              typically select between available actions based on the future
              value expected to result from each. Traditionally, however,
              habits have been understood as behaviors that can be triggered
              directly by a stimulus, without requiring the animal to evaluate
              expected outcomes. Here, we develop a computational model
              instantiating this traditional view, in which habits develop
              through the direct strengthening of recently taken actions rather
              than through the encoding of outcomes. We demonstrate that this
              model accounts for key behavioral manifestations of habits,
              including insensitivity to outcome devaluation and contingency
              degradation, as well as the effects of reinforcement schedule on
              the rate of habit formation. The model also explains the
              prevalent observation of perseveration in repeated-choice tasks
              as an additional behavioral manifestation of the habit system. We
              suggest that mapping habitual behaviors onto value-free
              mechanisms provides a parsimonious account of existing behavioral
              and neural data. This mapping may provide a new foundation for
              building robust and comprehensive models of the interaction of
              habits with other, more goal-directed types of behaviors and help
              to better guide research into the neural mechanisms underlying
              control of instrumental behavior more generally.",
  journal  = "bioRxiv",
  pages    = "067603",
  month    =  mar,
  year     =  2018,
  language = "en"
}

@ARTICLE{Doll2012-qb,
  title    = "The ubiquity of model-based reinforcement learning",
  author   = "Doll, Bradley B and Simon, Dylan A and Daw, Nathaniel D",
  abstract = "The reward prediction error (RPE) theory of dopamine (DA)
              function has enjoyed great success in the neuroscience of
              learning and decision-making. This theory is derived from
              model-free reinforcement learning (RL), in which choices are made
              simply on the basis of previously realized rewards. Recently,
              attention has turned to correlates of more flexible, albeit
              computationally complex, model-based methods in the brain. These
              methods are distinguished from model-free learning by their
              evaluation of candidate actions using expected future outcomes
              according to a world model. Puzzlingly, signatures from these
              computations seem to be pervasive in the very same regions
              previously thought to support model-free learning. Here, we
              review recent behavioral and neural evidence about these two
              systems, in attempt to reconcile their enigmatic cohabitation in
              the brain.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "1075--1081",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Miller_undated-ho,
  title  = "Re-aligning models of habitual and goal-directed decision-making",
  author = "Miller, Kevin and Ludvig, Elliot A and Pezzulo, Giovanni and
            Shenhav, Amitai"
}

@ARTICLE{Forstmeier2011-tz,
  title     = "Cryptic multiple hypotheses testing in linear models:
               overestimated effect sizes and the winner's curse",
  author    = "Forstmeier, Wolfgang and Schielzeth, Holger",
  abstract  = "Fitting generalised linear models (GLMs) with more than one
               predictor has become the standard method of analysis in
               evolutionary and behavioural research. Often, GLMs are used for
               exploratory data analysis, where one starts with a complex full
               model including interaction terms and then simplifies by
               removing non-significant terms. While this approach can be
               useful, it is problematic if significant effects are interpreted
               as if they arose from a single a priori hypothesis test. This is
               because model selection involves cryptic multiple hypothesis
               testing, a fact that has only rarely been acknowledged or
               quantified. We show that the probability of finding at least one
               'significant' effect is high, even if all null hypotheses are
               true (e.g. 40\% when starting with four predictors and their
               two-way interactions). This probability is close to theoretical
               expectations when the sample size (N) is large relative to the
               number of predictors including interactions (k). In contrast,
               type I error rates strongly exceed even those expectations when
               model simplification is applied to models that are over-fitted
               before simplification (low N/k ratio). The increase in
               false-positive results arises primarily from an overestimation
               of effect sizes among significant predictors, leading to
               upward-biased effect sizes that often cannot be reproduced in
               follow-up studies ('the winner's curse'). Despite having their
               own problems, full model tests and P value adjustments can be
               used as a guide to how frequently type I errors arise by
               sampling variation alone. We favour the presentation of full
               models, since they best reflect the range of predictors
               investigated and ensure a balanced representation also of
               non-significant results.",
  journal   = "Behav. Ecol. Sociobiol.",
  publisher = "Springer",
  volume    =  65,
  number    =  1,
  pages     = "47--55",
  month     =  jan,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Bolker2009-az,
  title    = "Generalized linear mixed models: a practical guide for ecology
              and evolution",
  author   = "Bolker, Benjamin M and Brooks, Mollie E and Clark, Connie J and
              Geange, Shane W and Poulsen, John R and Stevens, M Henry H and
              White, Jada-Simone S",
  abstract = "How should ecologists and evolutionary biologists analyze
              nonnormal data that involve random effects? Nonnormal data such
              as counts or proportions often defy classical statistical
              procedures. Generalized linear mixed models (GLMMs) provide a
              more flexible approach for analyzing nonnormal data when random
              effects are present. The explosion of research on GLMMs in the
              last decade has generated considerable uncertainty for
              practitioners in ecology and evolution. Despite the availability
              of accurate techniques for estimating GLMM parameters in simple
              cases, complex GLMMs are challenging to fit and statistical
              inference such as hypothesis testing remains difficult. We review
              the use (and misuse) of GLMMs in ecology and evolution, discuss
              estimation and inference and summarize 'best-practice' data
              analysis procedures for scientists facing this challenge.",
  journal  = "Trends Ecol. Evol.",
  volume   =  24,
  number   =  3,
  pages    = "127--135",
  month    =  mar,
  year     =  2009,
  language = "en"
}

@ARTICLE{Czaczkes2015-tx,
  title    = "Trail pheromones: an integrative view of their role in social
              insect colony organization",
  author   = "Czaczkes, Tomer J and Gr{\"u}ter, Christoph and Ratnieks, Francis
              L W",
  abstract = "Trail pheromones do more than simply guide social insect workers
              from point A to point B. Recent research has revealed additional
              ways in which they help to regulate colony foraging, often via
              positive and negative feedback processes that influence the
              exploitation of the different resources that a colony has
              knowledge of. Trail pheromones are often complementary or
              synergistic with other information sources, such as individual
              memory. Pheromone trails can be composed of two or more
              pheromones with different functions, and information may be
              embedded in the trail network geometry. These findings indicate
              remarkable sophistication in how trail pheromones are used to
              regulate colony-level behavior, and how trail pheromones are used
              and deployed at the individual level.",
  journal  = "Annu. Rev. Entomol.",
  volume   =  60,
  pages    = "581--599",
  month    =  jan,
  year     =  2015,
  keywords = "ants; complex adaptive systems; complexity; organization;
              recruitment; review",
  language = "en"
}

@ARTICLE{Ramsch2012-so,
  title    = "A mathematical model of foraging in a dynamic environment by
              trail-laying Argentine ants",
  author   = "Ramsch, Kai and Reid, Chris R and Beekman, Madeleine and
              Middendorf, Martin",
  abstract = "Ants live in dynamically changing environments, where food
              sources become depleted and alternative sources appear. Yet most
              mathematical models of ant foraging assume that the ants'
              foraging environment is static. Here we describe a mathematical
              model of ant foraging in a dynamic environment. Our model
              attempts to explain recent empirical data on dynamic foraging in
              the Argentine ant Linepithema humile (Mayr). The ants are able to
              find the shortest path in a Towers of Hanoi maze, a complex
              network containing 32,768 alternative paths, even when the maze
              is altered dynamically. We modify existing models developed to
              explain ant foraging in static environments, to elucidate what
              possible mechanisms allow the ants to quickly adapt to changes in
              their foraging environment. Our results suggest that navigation
              of individual ants based on a combination of one pheromone
              deposited during foraging and directional information enables the
              ants to adapt their foraging trails and recreates the
              experimental results.",
  journal  = "J. Theor. Biol.",
  volume   =  306,
  pages    = "32--45",
  month    =  aug,
  year     =  2012,
  language = "en"
}

@ARTICLE{Holcombe2012-qk,
  title    = "Modelling complex biological systems using an agent-based
              approach",
  author   = "Holcombe, Mike and Adra, Salem and Bicak, Mesude and Chin, Shawn
              and Coakley, Simon and Graham, Alison I and Green, Jeffrey and
              Greenough, Chris and Jackson, Duncan and Kiran, Mariam and
              MacNeil, Sheila and Maleki-Dizaji, Afsaneh and McMinn, Phil and
              Pogson, Mark and Poole, Robert and Qwarnstrom, Eva and Ratnieks,
              Francis and Rolfe, Matthew D and Smallwood, Rod and Sun, Tao and
              Worth, David",
  abstract = "Many of the complex systems found in biology are comprised of
              numerous components, where interactions between individual agents
              result in the emergence of structures and function, typically in
              a highly dynamic manner. Often these entities have limited
              lifetimes but their interactions both with each other and their
              environment can have profound biological consequences. We will
              demonstrate how modelling these entities, and their interactions,
              can lead to a new approach to experimental biology bringing new
              insights and a deeper understanding of biological systems.",
  journal  = "Integr. Biol.",
  volume   =  4,
  number   =  1,
  pages    = "53--64",
  month    =  jan,
  year     =  2012,
  language = "en"
}

@ARTICLE{Czaczkes2013-tr,
  title    = "Ant foraging on complex trails: route learning and the role of
              trail pheromones in Lasius niger",
  author   = "Czaczkes, Tomer J and Gr{\"u}ter, Christoph and Ellis, Laura and
              Wood, Elizabeth and Ratnieks, Francis L W",
  abstract = "Ants are central place foragers and use multiple information
              sources to navigate between the nest and feeding sites.
              Individual ants rapidly learn a route, and often prioritize
              memory over pheromone trails when tested on a simple trail with a
              single bifurcation. However, in nature, ants often forage at
              locations that are reached via more complex routes with multiple
              trail bifurcations. Such routes may be more difficult to learn,
              and thus ants would benefit from additional information. We
              hypothesized that trail pheromones play a more significant role
              in ant foraging on complex routes, either by assisting in
              navigation or route learning or both. We studied Lasius niger
              workers foraging on a doubly bifurcating trail with four end
              points. Route learning was slower and errors greater on
              alternating (e.g. left-right) versus repeating routes (e.g.
              left-left), with error rates of 32 and 3\%, respectively.
              However, errors on alternating routes decreased by 30\% when
              trail pheromone was present. Trail pheromones also aid route
              learning, leading to reduced errors in subsequent journeys
              without pheromone. If an experienced forager makes an error when
              returning to a food source, it reacts by increasing pheromone
              deposition on the return journey. In addition, high levels of
              trail pheromone suppress further pheromone deposition. This
              negative feedback mechanism may act to conserve pheromone or to
              regulate recruitment. Taken together, these results demonstrate
              further complexity and sophistication in the foraging system of
              ant colonies, especially in the role of trail pheromones and
              their relationship with learning and the use of private
              information (memory) in a complex environment.",
  journal  = "J. Exp. Biol.",
  volume   =  216,
  number   = "Pt 2",
  pages    = "188--197",
  month    =  jan,
  year     =  2013,
  language = "en"
}

@ARTICLE{Vittori2006-qd,
  title    = "Path efficiency of ant foraging trails in an artificial network",
  author   = "Vittori, Karla and Talbot, Gr{\'e}goire and Gautrais, Jacques and
              Fourcassi{\'e}, Vincent and Ara{\'u}jo, Aluizio F R and
              Theraulaz, Guy",
  abstract = "In this paper we present an individual-based model describing the
              foraging behavior of ants moving in an artificial network of
              tunnels in which several interconnected paths can be used to
              reach a single food source. Ants lay a trail pheromone while
              moving in the network and this pheromone acts as a system of mass
              recruitment that attracts other ants in the network. The rules
              implemented in the model are based on measures of the decisions
              taken by ants at tunnel bifurcations during real experiments. The
              collective choice of the ants is estimated by measuring their
              probability to take a given path in the network. Overall, we
              found a good agreement between the results of the simulations and
              those of the experiments, showing that simple behavioral rules
              can lead ants to find the shortest paths in the network. The
              match between the experiments and the model, however, was better
              for nestbound than for outbound ants. A sensitivity study of the
              model suggests that the bias observed in the choice of the ants
              at asymmetrical bifurcations is a key behavior to reproduce the
              collective choice observed in the experiments.",
  journal  = "J. Theor. Biol.",
  volume   =  239,
  number   =  4,
  pages    = "507--515",
  month    =  apr,
  year     =  2006,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Forster2014-ms,
  title    = "Effect of Trail Bifurcation Asymmetry and Pheromone Presence or
              Absence on Trail Choice by Lasius niger Ants",
  author   = "Forster, Antonia and Czaczkes, Tomer J and Warner, Emma and
              Woodall, Tom and Martin, Emily and Ratnieks, Francis L W and
              Herberstein, M",
  abstract = "During foraging, ant workers are known to make use of multiple
              information sources, such as private information (personal
              memory) and social information (trail pheromones). Environmental
              effects on foraging, and how these interact with other
              information sources, have, however, been little studied. One
              environmental effect is trail bifurcation asymmetry. Ants forage
              on branching trail networks and must often decide which branch to
              take at a junction (bifurcation). This is an important decision,
              as finding food sources relies on making the correct choices at
              bifurcations. Bifurcation angle may provide important information
              when making this choice. We used a Y-maze with a pivoting 90°
              bifurcation to study trail choice of Lasius niger foragers at
              varying branch asymmetries (0°, [both branches 45° from straight
              ahead], 30° [branches at 30° and 60° from straight ahead], 45°,
              60° and 90° [one branch straight ahead, the other at 90°]). The
              experiment was carried out either with equal amounts of trail
              pheromone on both branches of the bifurcation or with pheromone
              present on only one branch. Our results show that with equal
              pheromone, trail asymmetry has a significant effect on trail
              choice. Ants preferentially follow the branch deviating least
              from straight, and this effect increases as asymmetry increases
              (47\% at 0°, 54\% at 30°, 57\% at 45°, 66\% at 60° and 73\% at
              90°). However, when pheromone is only present on one branch, the
              graded effect of asymmetry disappears. Overall, however, there is
              an effect of asymmetry as the preference of ants for the
              pheromone-marked branch over the unmarked branch is reduced from
              65\%, when it is the less deviating branch, to 53\%, when it is
              the more deviating branch. These results demonstrate that trail
              asymmetry influences ant decision-making at bifurcations and that
              this information interacts with trail pheromone presence in a
              non-hierarchical manner.",
  journal  = "Ethology",
  volume   =  120,
  number   =  8,
  pages    = "768--775",
  month    =  aug,
  year     =  2014,
  keywords = "Lasius niger; asymmetry; environmental effects; foraging;
              pheromone; trail choice",
  language = "en"
}

@ARTICLE{Garnier2013-cv,
  title    = "Do ants need to estimate the geometrical properties of trail
              bifurcations to find an efficient route? A swarm robotics test
              bed",
  author   = "Garnier, Simon and Combe, Maud and Jost, Christian and Theraulaz,
              Guy",
  abstract = "Interactions between individuals and the structure of their
              environment play a crucial role in shaping self-organized
              collective behaviors. Recent studies have shown that ants
              crossing asymmetrical bifurcations in a network of galleries tend
              to follow the branch that deviates the least from their incoming
              direction. At the collective level, the combination of this
              tendency and the pheromone-based recruitment results in a greater
              likelihood of selecting the shortest path between the colony's
              nest and a food source in a network containing asymmetrical
              bifurcations. It was not clear however what the origin of this
              behavioral bias is. Here we propose that it results from a simple
              interaction between the behavior of the ants and the geometry of
              the network, and that it does not require the ability to measure
              the angle of the bifurcation. We tested this hypothesis using
              groups of ant-like robots whose perceptual and cognitive
              abilities can be fully specified. We programmed them only to lay
              down and follow light trails, avoid obstacles and move according
              to a correlated random walk, but not to use more sophisticated
              orientation methods. We recorded the behavior of the robots in
              networks of galleries presenting either only symmetrical
              bifurcations or a combination of symmetrical and asymmetrical
              bifurcations. Individual robots displayed the same pattern of
              branch choice as individual ants when crossing a bifurcation,
              suggesting that ants do not actually measure the geometry of the
              bifurcations when travelling along a pheromone trail. Finally at
              the collective level, the group of robots was more likely to
              select one of the possible shorter paths between two designated
              areas when moving in an asymmetrical network, as observed in
              ants. This study reveals the importance of the shape of trail
              networks for foraging in ants and emphasizes the underestimated
              role of the geometrical properties of transportation networks in
              general.",
  journal  = "PLoS Comput. Biol.",
  volume   =  9,
  number   =  3,
  pages    = "e1002903",
  month    =  mar,
  year     =  2013,
  language = "en"
}

@ARTICLE{Sych2019-ds,
  title    = "High-density multi-fiber photometry for studying large-scale
              brain circuit dynamics",
  author   = "Sych, Yaroslav and Chernysheva, Maria and Sumanovski, Lazar T and
              Helmchen, Fritjof",
  abstract = "Animal behavior originates from neuronal activity distributed
              across brain-wide networks. However, techniques available to
              assess large-scale neural dynamics in behaving animals remain
              limited. Here we present compact, chronically implantable,
              high-density arrays of optical fibers that enable multi-fiber
              photometry and optogenetic perturbations across many regions in
              the mammalian brain. In mice engaged in a texture discrimination
              task, we achieved simultaneous photometric calcium recordings
              from networks of 12-48 brain regions, including striatal,
              thalamic, hippocampal and cortical areas. Furthermore, we
              optically perturbed subsets of regions in VGAT-ChR2 mice by
              targeting specific fiber channels with a spatial light modulator.
              Perturbation of ventral thalamic nuclei caused distributed
              network modulation and behavioral deficits. Finally, we
              demonstrate multi-fiber photometry in freely moving animals,
              including simultaneous recordings from two mice during social
              interaction. High-density multi-fiber arrays are versatile tools
              for the investigation of large-scale brain dynamics during
              behavior.",
  journal  = "Nat. Methods",
  month    =  may,
  year     =  2019,
  language = "en"
}

@ARTICLE{Pezzulo2019-dg,
  title    = "Planning at decision time and in the background during spatial
              navigation",
  author   = "Pezzulo, Giovanni and Donnarumma, Francesco and Maisto, Domenico
              and Stoianov, Ivilin",
  abstract = "Planning is the model-based approach to solving control problems.
              The hallmark of planning is the endogenous generation of
              dynamical representations of future states, like goal locations,
              or state sequences, like trajectories to the goal location, using
              an internal model of the task. We review recent evidence of
              model-based planning processes and the representation of future
              goal states in the brain of rodents and humans engaged in spatial
              navigation tasks. We highlight two distinct but complementary
              usages of planning as identified in artificial intelligence: `at
              decision time', to support goal-directed choices and sequential
              memory encoding, and `in the background', to learn behavioral
              policies and to optimize internal models. We discuss how two
              kinds of internally generated sequences in the hippocampus --
              theta and SWR sequences -- might participate in the neuronal
              implementation of these two planning modes, thus supporting a
              flexible model-based system for adaptive cognition and action.",
  journal  = "Current Opinion in Behavioral Sciences",
  volume   =  29,
  pages    = "69--76",
  month    =  oct,
  year     =  2019
}

@ARTICLE{Blum2005-ut,
  title    = "Ant colony optimization: Introduction and recent trends",
  author   = "Blum, Christian",
  abstract = "Ant colony optimization is a technique for optimization that was
              introduced in the early 1990's. The inspiring source of ant
              colony optimization is the foraging behavior of real ant
              colonies. This behavior is exploited in artificial ant colonies
              for the search of approximate solutions to discrete optimization
              problems, to continuous optimization problems, and to important
              problems in telecommunications, such as routing and load
              balancing. First, we deal with the biological inspiration of ant
              colony optimization algorithms. We show how this biological
              inspiration can be transfered into an algorithm for discrete
              optimization. Then, we outline ant colony optimization in more
              general terms in the context of discrete optimization, and
              present some of the nowadays best-performing ant colony
              optimization variants. After summarizing some important
              theoretical results, we demonstrate how ant colony optimization
              can be applied to continuous optimization problems. Finally, we
              provide examples of an interesting recent research direction: The
              hybridization with more classical techniques from artificial
              intelligence and operations research.",
  journal  = "Phys. Life Rev.",
  volume   =  2,
  number   =  4,
  pages    = "353--373",
  month    =  dec,
  year     =  2005,
  keywords = "Ant colony optimization; Discrete optimization; Hybridization"
}

@ARTICLE{Gronenberg2008-rj,
  title   = "Structure and function of ant (Hymenoptera: Formicidae) brains:
             strength in numbers",
  author  = "Gronenberg, Wulfila",
  journal = "Myrmecol. News",
  volume  =  11,
  pages   = "25--36",
  year    =  2008
}

@ARTICLE{Daw2011-jx,
  title     = "Model-based influences on humans' choices and striatal
               prediction errors",
  author    = "Daw, Nathaniel D and Gershman, Samuel J and Seymour, Ben and
               Dayan, Peter and Dolan, Raymond J",
  abstract  = "The mesostriatal dopamine system is prominently implicated in
               model-free reinforcement learning, with fMRI BOLD signals in
               ventral striatum notably covarying with model-free prediction
               errors. However, latent learning and devaluation studies show
               that behavior also shows hallmarks of model-based planning, and
               the interaction between model-based and model-free values,
               prediction errors, and preferences is underexplored. We designed
               a multistep decision task in which model-based and model-free
               influences on human choice behavior could be distinguished. By
               showing that choices reflected both influences we could then
               test the purity of the ventral striatal BOLD signal as a
               model-free report. Contrary to expectations, the signal
               reflected both model-free and model-based predictions in
               proportions matching those that best explained choice behavior.
               These results challenge the notion of a separate model-free
               learner and suggest a more integrated computational architecture
               for high-level human decision-making.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  69,
  number    =  6,
  pages     = "1204--1215",
  month     =  mar,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Gao2015-ik,
  title    = "On simplicity and complexity in the brave new world of
              large-scale neuroscience",
  author   = "Gao, Peiran and Ganguli, Surya",
  abstract = "Technological advances have dramatically expanded our ability to
              probe multi-neuronal dynamics and connectivity in the brain.
              However, our ability to extract a simple conceptual understanding
              from complex data is increasingly hampered by the lack of
              theoretically principled data analytic procedures, as well as
              theoretical frameworks for how circuit connectivity and dynamics
              can conspire to generate emergent behavioral and cognitive
              functions. We review and outline potential avenues for progress,
              including new theories of high dimensional data analysis, the
              need to analyze complex artificial networks, and methods for
              analyzing entire spaces of circuit models, rather than one model
              at a time. Such interplay between experiments, data analysis and
              theory will be indispensable in catalyzing conceptual advances in
              the age of large-scale neuroscience.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  32,
  pages    = "148--155",
  month    =  jun,
  year     =  2015,
  language = "en"
}

@INPROCEEDINGS{Lobo1997-qb,
  title     = "Decision making in a hybrid genetic algorithm",
  booktitle = "Proceedings of 1997 {IEEE} International Conference on
               Evolutionary Computation ({ICEC} '97)",
  author    = "Lobo, F G and Goldberg, D E",
  abstract  = "There are several issues that need to be taken into
               consideration when designing a hybrid problem solver. The paper
               focuses on one of them-decision making. More specifically, we
               address the following questions: given two different methods,
               how to get the most out of both of them? When should we use one
               and when should we use the other in order to get maximum
               efficiency? We present a model for hybridizing genetic
               algorithms (GAs) based on a concept that decision theorists call
               probability matching and we use it to combine an elitist
               selecto-recombinative GA with a simple hill climber (HC). Tests
               on an easy problem with a small population size match our
               intuition that both GA and HC are needed to solve the problem
               efficiently.",
  pages     = "121--125",
  month     =  apr,
  year      =  1997,
  keywords  = "decision theory;genetic algorithms;probability;decision
               making;hybrid genetic algorithm;hybrid problem solver;maximum
               efficiency;decision theorists;probability matching;elitist
               selecto-recombinative GA;simple hill climber;population
               size;Decision making;Genetic algorithms;Algorithm design and
               analysis;Testing;Expert systems;Turbines;Jet engines;Diversity
               reception;Maintenance engineering;Mathematical analysis"
}

@ARTICLE{Balaguer2016-ho,
  title    = "Neural Mechanisms of Hierarchical Planning in a Virtual Subway
              Network",
  author   = "Balaguer, Jan and Spiers, Hugo and Hassabis, Demis and
              Summerfield, Christopher",
  abstract = "Planning allows actions to be structured in pursuit of a future
              goal. However, in natural environments, planning over multiple
              possible future states incurs prohibitive computational costs. To
              represent plans efficiently, states can be clustered
              hierarchically into ``contexts''. For example, representing a
              journey through a subway network as a succession of individual
              states (stations) is more costly than encoding a sequence of
              contexts (lines) and context switches (line changes). Here, using
              functional brain imaging, we asked humans to perform a planning
              task in a virtual subway network. Behavioral analyses revealed
              that humans executed a hierarchically organized plan. Brain
              activity in the dorsomedial prefrontal cortex and premotor cortex
              scaled with the cost of hierarchical plan representation and
              unique neural signals in these regions signaled contexts and
              context switches. These results suggest that humans represent
              hierarchical plans using a network of caudal prefrontal
              structures. VIDEO ABSTRACT.",
  journal  = "Neuron",
  volume   =  90,
  number   =  4,
  pages    = "893--903",
  month    =  may,
  year     =  2016,
  language = "en"
}

@ARTICLE{Spiers2015-fq,
  title    = "Neural systems supporting navigation",
  author   = "Spiers, Hugo J and Barry, Caswell",
  abstract = "Much is known about how neural systems determine current spatial
              position and orientation in the environment. By contrast little
              is understood about how the brain represents future goal
              locations or computes the distance and direction to such goals.
              Recent electrophysiology, computational modelling and
              neuroimaging research have shed new light on how the spatial
              relationship to a goal may be determined and represented during
              navigation. This research suggests that the hippocampus may code
              the path to the goal while the entorhinal cortex represents the
              vector to the goal. It also reveals that the engagement of the
              hippocampus and entorhinal cortex varies across the different
              operational stages of navigation, such as during travel, route
              planning, and decision-making at waypoints.",
  journal  = "Current Opinion in Behavioral Sciences",
  volume   =  1,
  pages    = "47--55",
  month    =  feb,
  year     =  2015
}

@ARTICLE{Spiers2008-aw,
  title    = "Keeping the goal in mind: prefrontal contributions to spatial
              navigation",
  author   = "Spiers, Hugo J",
  journal  = "Neuropsychologia",
  volume   =  46,
  number   =  7,
  pages    = "2106--2108",
  month    =  feb,
  year     =  2008,
  language = "en"
}

@ARTICLE{Beekman2001-xe,
  title    = "Phase transition between disordered and ordered foraging in
              Pharaoh's ants",
  author   = "Beekman, M and Sumpter, D J and Ratnieks, F L",
  abstract = "The complex collective behavior seen in many insect societies
              strongly suggests that a minimum number of workers are required
              for these societies to function effectively. Here we investigated
              the transition between disordered and ordered foraging in the
              Pharaoh's ant. We show that small colonies forage in a
              disorganized manner, with a transition to organized
              pheromone-based foraging in larger colonies. We also show that
              when food sources are difficult to locate through independent
              searching, this transition is first-order and exhibits
              hysteresis, comparable to a first-order phase transition found in
              many physical systems. To our knowledge, this is the first
              experimental evidence of a behavioral phase transition between a
              maladaptive (disorganized) and an adaptive (organized) state.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  98,
  number   =  17,
  pages    = "9703--9706",
  month    =  aug,
  year     =  2001,
  language = "en"
}

@ARTICLE{Trimmer_Pete_C2008-ub,
  title     = "Mammalian choices: combining fast-but-inaccurate and
               slow-but-accurate decision-making systems",
  author    = "{Trimmer Pete C} and {Houston Alasdair I} and {Marshall James
               A.R} and {Bogacz Rafal} and {Paul Elizabeth S} and {Mendl Mike
               T} and {McNamara John M}",
  journal   = "Proceedings of the Royal Society B: Biological Sciences",
  publisher = "Royal Society",
  volume    =  275,
  number    =  1649,
  pages     = "2353--2361",
  month     =  oct,
  year      =  2008
}

@ARTICLE{Gremel2013-yb,
  title     = "Orbitofrontal and striatal circuits dynamically encode the shift
               between goal-directed and habitual actions",
  author    = "Gremel, Christina M and Costa, Rui M",
  abstract  = "Shifting between goal-directed and habitual actions allows for
               efficient and flexible decision making. Here we demonstrate a
               novel, within-subject instrumental lever-pressing paradigm, in
               which mice shift between goal-directed and habitual actions. We
               identify a role for orbitofrontal cortex (OFC) in actions
               following outcome revaluation, and confirm that dorsal medial
               (DMS) and lateral striatum (DLS) mediate different action
               strategies. Simultaneous in vivo recordings of OFC, DMS and DLS
               neuronal ensembles during shifting reveal that the same neurons
               display different activities depending on whether presses are
               goal-directed or habitual, with DMS and OFC becoming more and
               DLS less engaged during goal-directed actions. Importantly, the
               magnitude of neural activity changes in OFC following changes in
               outcome value positively correlates with the level of
               goal-directed behavior. Chemogenetic inhibition of OFC disrupts
               goal-directed actions, whereas optogenetic activation of OFC
               specifically increases goal-directed pressing. These results
               also reveal a role for OFC in action revaluation, which has
               implications for understanding compulsive behavior.",
  journal   = "Nat. Commun.",
  publisher = "nature.com",
  volume    =  4,
  pages     = "2264",
  year      =  2013,
  language  = "en"
}

@ARTICLE{McDannald2011-df,
  title     = "Ventral striatum and orbitofrontal cortex are both required for
               model-based, but not model-free, reinforcement learning",
  author    = "McDannald, Michael A and Lucantonio, Federica and Burke, Kathryn
               A and Niv, Yael and Schoenbaum, Geoffrey",
  abstract  = "In many cases, learning is thought to be driven by differences
               between the value of rewards we expect and rewards we actually
               receive. Yet learning can also occur when the identity of the
               reward we receive is not as expected, even if its value remains
               unchanged. Learning from changes in reward identity implies
               access to an internal model of the environment, from which
               information about the identity of the expected reward can be
               derived. As a result, such learning is not easily accounted for
               by model-free reinforcement learning theories such as temporal
               difference reinforcement learning (TDRL), which predicate
               learning on changes in reward value, but not identity. Here, we
               used unblocking procedures to assess learning driven by value-
               versus identity-based prediction errors. Rats were trained to
               associate distinct visual cues with different food quantities
               and identities. These cues were subsequently presented in
               compound with novel auditory cues and the reward quantity or
               identity was selectively changed. Unblocking was assessed by
               presenting the auditory cues alone in a probe test. Consistent
               with neural implementations of TDRL models, we found that the
               ventral striatum was necessary for learning in response to
               changes in reward value. However, this area, along with
               orbitofrontal cortex, was also required for learning driven by
               changes in reward identity. This observation requires that
               existing models of TDRL in the ventral striatum be modified to
               include information about the specific features of expected
               outcomes derived from model-based representations, and that the
               role of orbitofrontal cortex in these models be clearly
               delineated.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  31,
  number    =  7,
  pages     = "2700--2705",
  month     =  feb,
  year      =  2011,
  language  = "en"
}

@UNPUBLISHED{Kay2019-yl,
  title    = "Regular cycling between representations of alternatives in the
              hippocampus",
  author   = "Kay, Kenneth and Chung, Jason E and Sosa, Marielena and Schor,
              Jonathan S and Karlsson, Mattias P and Larkin, Margaret C and
              Liu, Daniel F and Frank, Loren M",
  abstract = "Cognitive faculties such as imagination, planning, and
              decision-making require the ability to represent alternative
              scenarios. In animals, split-second decision-making implies that
              the brain can represent alternatives at a commensurate speed. Yet
              despite this insight, it has remained unknown whether there
              exists neural activity that can consistently represent
              alternatives in",
  journal  = "bioRxiv",
  pages    = "528976",
  month    =  jan,
  year     =  2019,
  language = "en"
}

@ARTICLE{Karlsson2009-wx,
  title    = "Awake replay of remote experiences in the hippocampus",
  author   = "Karlsson, Mattias P and Frank, Loren M",
  abstract = "Hippocampal replay is thought to be essential for the
              consolidation of event memories in hippocampal-neocortical
              networks. Replay is present during both sleep and waking
              behavior, but although sleep replay involves the reactivation of
              stored representations in the absence of specific sensory inputs,
              awake replay is thought to depend on sensory input from the
              current environment. Here, we show that stored representations
              are reactivated during both waking and sleep replay. We found
              frequent awake replay of sequences of rat hippocampal place cells
              from a previous experience. This spatially remote replay was as
              common as local replay of the current environment and was more
              robust when the rat had recently been in motion than during
              extended periods of quiescence. Our results indicate that the
              hippocampus consistently replays past experiences during brief
              pauses in waking behavior, suggesting a role for waking replay in
              memory consolidation and retrieval.",
  journal  = "Nat. Neurosci.",
  volume   =  12,
  number   =  7,
  pages    = "913--918",
  month    =  jul,
  year     =  2009,
  language = "en"
}

@ARTICLE{Miller2017-em,
  title    = "Dorsal hippocampus contributes to model-based planning",
  author   = "Miller, Kevin J and Botvinick, Matthew M and Brody, Carlos D",
  abstract = "Planning can be defined as action selection that leverages an
              internal model of the outcomes likely to follow each possible
              action. Its neural mechanisms remain poorly understood. Here we
              adapt recent advances from human research for rats, presenting
              for the first time an animal task that produces many trials of
              planned behavior per session, making multitrial rodent
              experimental tools available to study planning. We use part of
              this toolkit to address a perennially controversial issue in
              planning: the role of the dorsal hippocampus. Although
              prospective hippocampal representations have been proposed to
              support planning, intact planning in animals with damaged
              hippocampi has been repeatedly observed. Combining formal
              algorithmic behavioral analysis with muscimol inactivation, we
              provide causal evidence directly linking dorsal hippocampus with
              planning behavior. Our results and methods open the door to new
              and more detailed investigations of the neural mechanisms of
              planning in the hippocampus and throughout the brain.",
  journal  = "Nat. Neurosci.",
  volume   =  20,
  number   =  9,
  pages    = "1269--1276",
  month    =  sep,
  year     =  2017,
  language = "en"
}

@ARTICLE{Botvinick2019-ac,
  title    = "Reinforcement Learning, Fast and Slow",
  author   = "Botvinick, Matthew and Ritter, Sam and Wang, Jane X and
              Kurth-Nelson, Zeb and Blundell, Charles and Hassabis, Demis",
  abstract = "Deep reinforcement learning (RL) methods have driven impressive
              advances in artificial intelligence in recent years, exceeding
              human performance in domains ranging from Atari to Go to no-limit
              poker. This progress has drawn the attention of cognitive
              scientists interested in understanding human learning. However,
              the concern has been raised that deep RL may be too
              sample-inefficient - that is, it may simply be too slow - to
              provide a plausible model of how humans learn. In the present
              review, we counter this critique by describing recently developed
              techniques that allow deep RL to operate more nimbly, solving
              problems much more quickly than previous methods. Although these
              techniques were developed in an AI context, we propose that they
              may have rich implications for psychology and neuroscience. A key
              insight, arising from these AI methods, concerns the fundamental
              connection between fast RL and slower, more incremental forms of
              learning.",
  journal  = "Trends Cogn. Sci.",
  month    =  apr,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Huda2018-bn,
  title    = "Bidirectional control of goal-oriented action selection by
              distinct prefrontal cortex circuits",
  author   = "Huda, Rafiq and Sipe, Grayson O and Adam, Elie and
              Breton-Provencher, Vincent and Pho, Gerald N and Gunter, Liadan M
              and Wickersham, Ian R and Sur, Mriganka",
  abstract = "Summary The immense behavioral repertoire of animals necessitates
              mechanisms that select and suppress specific actions depending on
              current goals. The prefrontal cortex (PFC) has been suggested to
              orchestrate these processes by biasing activity in its target
              structures, but how its vastly converging inputs and diverging
              outputs are coordinated to control goal-oriented actions remains
              unclear. Here we use a bilateral task in which mice select
              between symmetric but opposing actions to show that distinct
              outputs from a subdivision of the PFC, the anterior cingulate
              cortex (ACC), promote correct and suppress incorrect actions.
              Surprisingly, ACC outputs to the superior colliculus principally
              inhibit incorrect actions. Optogenetic analyses and a
              projection-based activity model make the unexpected prediction
              that feedback from the ACC to the visual cortex promotes correct
              actions, which we confirm. Our results show that anatomically
              non-overlapping but functionally complementary PFC outputs
              bidirectionally control actions, and suggest a candidate
              organizing principle for PFC circuits.",
  journal  = "bioRxiv",
  pages    = "307009",
  month    =  jul,
  year     =  2018,
  language = "en"
}

@ARTICLE{Coutureau2003-sj,
  title     = "Inactivation of the infralimbic prefrontal cortex reinstates
               goal-directed responding in overtrained rats",
  author    = "Coutureau, Etienne and Killcross, Simon",
  abstract  = "Over the course of extended training, instrumental responding in
               rats shows a transition from goal-dependent performance to
               goal-independent performance, as assessed by sensitivity to
               reward-devaluation induced by taste aversions or specific
               satiety. It has been suggested that this reflects the gradual
               dominance of reflexive, habit-based responding over voluntary,
               goal-directed actions. Previous research suggests that lesions
               of the medial prefrontal cortex disrupt this interaction between
               goal-directed and habitual responding. More specifically,
               whereas lesions of the prelimbic prefrontal cortex appear to
               disrupt normal goal-directed responding, lesions of the
               infralimbic prefrontal cortex cause animals to remain
               goal-directed even after substantial overtraining. The current
               experiment explored further the nature of this interaction
               between actions and habits. Rats were given extended training of
               an instrumental lever press response before bilateral
               intracerebral cannulae giving access to the infralimbic cortex
               were implanted. Following further reminder training all animals
               were given a test of goal sensitivity by specific-satiety
               devaluation of the instrumental outcome, or a matched reward,
               prior to extinction tests. Before these tests, half of the
               animals received bilateral infusions of muscimol into the
               infralimbic cortex, and the remainder, control vehicle
               infusions. As expected after extended instrumental training,
               control-infused animals showed habitual performance that was not
               selectively influenced by devaluation of the instrumental
               outcome. In contrast, animals receiving temporary inactivation
               of the infralimbic cortex by muscimol showed selective
               sensitivity to devaluation of the instrumental outcome,
               indicating a reinstatement of goal-directed responding in these
               animals. This suggests that the development of habitual
               responding reflects the active inhibition of goal-directed
               responses that are mediated by action-outcome associations.",
  journal   = "Behav. Brain Res.",
  publisher = "Elsevier",
  volume    =  146,
  number    = "1-2",
  pages     = "167--174",
  month     =  nov,
  year      =  2003,
  language  = "en"
}

@ARTICLE{Rao2010-cq,
  title    = "Decision making under uncertainty: a neural model based on
              partially observable markov decision processes",
  author   = "Rao, Rajesh P N",
  abstract = "A fundamental problem faced by animals is learning to select
              actions based on noisy sensory information and incomplete
              knowledge of the world. It has been suggested that the brain
              engages in Bayesian inference during perception but how such
              probabilistic representations are used to select actions has
              remained unclear. Here we propose a neural model of action
              selection and decision making based on the theory of partially
              observable Markov decision processes (POMDPs). Actions are
              selected based not on a single ``optimal'' estimate of state but
              on the posterior distribution over states (the ``belief'' state).
              We show how such a model provides a unified framework for
              explaining experimental results in decision making that involve
              both information gathering and overt actions. The model utilizes
              temporal difference (TD) learning for maximizing expected reward.
              The resulting neural architecture posits an active role for the
              neocortex in belief computation while ascribing a role to the
              basal ganglia in belief representation, value computation, and
              action selection. When applied to the random dots motion
              discrimination task, model neurons representing belief exhibit
              responses similar to those of LIP neurons in primate neocortex.
              The appropriate threshold for switching from information
              gathering to overt actions emerges naturally during reward
              maximization. Additionally, the time course of reward prediction
              error in the model shares similarities with dopaminergic
              responses in the basal ganglia during the random dots task. For
              tasks with a deadline, the model learns a decision making
              strategy that changes with elapsed time, predicting a collapsing
              decision threshold consistent with some experimental studies. The
              model provides a new framework for understanding neural decision
              making and suggests an important role for interactions between
              the neocortex and the basal ganglia in learning the mapping
              between probabilistic sensory representations and actions that
              maximize rewards.",
  journal  = "Front. Comput. Neurosci.",
  volume   =  4,
  pages    = "146",
  month    =  nov,
  year     =  2010,
  keywords = "Bayesian inference; basal ganglia; decision theory; dopamine;
              parietal cortex; probabilistic models; reinforcement learning;
              temporal difference learning",
  language = "en"
}

@ARTICLE{Van_der_Meer2010-ka,
  title    = "Triple dissociation of information processing in dorsal striatum,
              ventral striatum, and hippocampus on a learned spatial decision
              task",
  author   = "van der Meer, Matthijs A A and Johnson, Adam and
              Schmitzer-Torbert, Neil C and Redish, A David",
  abstract = "Decision-making studies across different domains suggest that
              decisions can arise from multiple, parallel systems in the brain:
              a flexible system utilizing action-outcome expectancies and a
              more rigid system based on situation-action associations. The
              hippocampus, ventral striatum, and dorsal striatum make unique
              contributions to each system, but how information processing in
              each of these structures supports these systems is unknown.
              Recent work has shown covert representations of future paths in
              hippocampus and of future rewards in ventral striatum. We
              developed analyses in order to use a comparative methodology and
              apply the same analyses to all three structures. Covert
              representations of future paths and reward were both absent from
              the dorsal striatum. In contrast, dorsal striatum slowly
              developed situation representations that selectively represented
              action-rich parts of the task. This triple dissociation suggests
              that the different roles these structures play are due to
              differences in information-processing mechanisms.",
  journal  = "Neuron",
  volume   =  67,
  number   =  1,
  pages    = "25--32",
  month    =  jul,
  year     =  2010,
  language = "en"
}

@ARTICLE{Yin2006-jc,
  title     = "The role of the basal ganglia in habit formation",
  author    = "Yin, Henry H and Knowlton, Barbara J",
  abstract  = "Many organisms, especially humans, are characterized by their
               capacity for intentional, goal-directed actions. However,
               similar behaviours often proceed automatically, as habitual
               responses to antecedent stimuli. How are goal-directed actions
               transformed into habitual responses? Recent work combining
               modern behavioural assays and neurobiological analysis of the
               basal ganglia has begun to yield insights into the neural basis
               of habit formation.",
  journal   = "Nat. Rev. Neurosci.",
  publisher = "nature.com",
  volume    =  7,
  number    =  6,
  pages     = "464--476",
  month     =  jun,
  year      =  2006,
  language  = "en"
}

@ARTICLE{Fiore2015-om,
  title    = "Evolutionarily conserved mechanisms for the selection and
              maintenance of behavioural activity",
  author   = "Fiore, Vincenzo G and Dolan, Raymond J and Strausfeld, Nicholas J
              and Hirth, Frank",
  abstract = "Survival and reproduction entail the selection of adaptive
              behavioural repertoires. This selection manifests as
              phylogenetically acquired activities that depend on evolved
              nervous system circuitries. Lorenz and Tinbergen already
              postulated that heritable behaviours and their reliable
              performance are specified by genetically determined programs.
              Here we compare the functional anatomy of the insect central
              complex and vertebrate basal ganglia to illustrate their role in
              mediating selection and maintenance of adaptive behaviours.
              Comparative analyses reveal that central complex and basal
              ganglia circuitries share comparable lineage relationships within
              clusters of functionally integrated neurons. These clusters are
              specified by genetic mechanisms that link birth time and order to
              their neuronal identities and functions. Their subsequent
              connections and associated functions are characterized by similar
              mechanisms that implement dimensionality reduction and transition
              through attractor states, whereby spatially organized
              parallel-projecting loops integrate and convey sensorimotor
              representations that select and maintain behavioural activity. In
              both taxa, these neural systems are modulated by dopamine
              signalling that also mediates memory-like processes. The
              multiplicity of similarities between central complex and basal
              ganglia suggests evolutionarily conserved computational
              mechanisms for action selection. We speculate that these may have
              originated from ancestral ground pattern circuitries present in
              the brain of the last common ancestor of insects and vertebrates.",
  journal  = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  volume   =  370,
  number   =  1684,
  month    =  dec,
  year     =  2015,
  keywords = "action selection; attractor state; basal ganglia; brain
              evolution; central complex; sensorimotor representation",
  language = "en"
}

@ARTICLE{Patrick_undated-xh,
  title  = "Computational model of habit learning and reversal",
  author = "Patrick, Sean and Bullock, Daniel"
}

@ARTICLE{Harvey2009-ql,
  title     = "Intracellular dynamics of hippocampal place cells during virtual
               navigation",
  author    = "Harvey, Christopher D and Collman, Forrest and Dombeck, Daniel A
               and Tank, David W",
  abstract  = "Hippocampal place cells encode spatial information in rate and
               temporal codes. To examine the mechanisms underlying hippocampal
               coding, here we measured the intracellular dynamics of place
               cells by combining in vivo whole-cell recordings with a
               virtual-reality system. Head-restrained mice, running on a
               spherical treadmill, interacted with a computer-generated visual
               environment to perform spatial behaviours. Robust place-cell
               activity was present during movement along a virtual linear
               track. From whole-cell recordings, we identified three
               subthreshold signatures of place fields: an asymmetric ramp-like
               depolarization of the baseline membrane potential, an increase
               in the amplitude of intracellular theta oscillations, and a
               phase precession of the intracellular theta oscillation relative
               to the extracellularly recorded theta rhythm. These
               intracellular dynamics underlie the primary features of
               place-cell rate and temporal codes. The virtual-reality system
               developed here will enable new experimental approaches to study
               the neural circuits underlying navigation.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  461,
  number    =  7266,
  pages     = "941--946",
  month     =  oct,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Buschman2014-yb,
  title     = "Goal-direction and top-down control",
  author    = "Buschman, Timothy J and Miller, Earl K",
  abstract  = "We review the neural mechanisms that support top-down control of
               behaviour and suggest that goal-directed behaviour uses two
               systems that work in concert. A basal ganglia-centred system
               quickly learns simple, fixed goal-directed behaviours while a
               prefrontal cortex-centred system gradually learns more complex
               (abstract or long-term) goal-directed behaviours. Interactions
               between these two systems allow top-down control mechanisms to
               learn how to direct behaviour towards a goal but also how to
               guide behaviour when faced with a novel situation.",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "royalsocietypublishing.org",
  volume    =  369,
  number    =  1655,
  month     =  nov,
  year      =  2014,
  keywords  = "basal ganglia; cognition; frontal lobe; goal direction; learning",
  language  = "en"
}

@ARTICLE{Kawato2007-vk,
  title     = "Efficient reinforcement learning: computational theories,
               neuroscience and robotics",
  author    = "Kawato, Mitsuo and Samejima, Kazuyuki",
  abstract  = "Reinforcement learning algorithms have provided some of the most
               influential computational theories for behavioral learning that
               depends on reward and penalty. After briefly reviewing
               supporting experimental data, this paper tackles three difficult
               theoretical issues that remain to be explored. First, plain
               reinforcement learning is much too slow to be considered a
               plausible brain model. Second, although the temporal-difference
               error has an important role both in theory and in experiments,
               how to compute it remains an enigma. Third, function of all
               brain areas, including the cerebral cortex, cerebellum,
               brainstem and basal ganglia, seems to necessitate a new
               computational framework. Computational studies that emphasize
               meta-parameters, hierarchy, modularity and supervised learning
               to resolve these issues are reviewed here, together with the
               related experimental data.",
  journal   = "Curr. Opin. Neurobiol.",
  publisher = "Elsevier",
  volume    =  17,
  number    =  2,
  pages     = "205--212",
  month     =  apr,
  year      =  2007,
  language  = "en"
}

@ARTICLE{Ghahramani2015-gx,
  title     = "Probabilistic machine learning and artificial intelligence",
  author    = "Ghahramani, Zoubin",
  abstract  = "How can a machine learn from experience? Probabilistic modelling
               provides a framework for understanding what learning is, and has
               therefore emerged as one of the principal theoretical and
               practical approaches for designing machines that learn from data
               acquired through experience. The probabilistic framework, which
               describes how to represent and manipulate uncertainty about
               models and predictions, has a central role in scientific data
               analysis, machine learning, robotics, cognitive science and
               artificial intelligence. This Review provides an introduction to
               this framework, and discusses some of the state-of-the-art
               advances in the field, namely, probabilistic programming,
               Bayesian optimization, data compression and automatic model
               discovery.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  521,
  number    =  7553,
  pages     = "452--459",
  month     =  may,
  year      =  2015,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Becker1964-sy,
  title     = "Measuring utility by a single-response sequential method",
  author    = "Becker, Gordon M and DeGroot, Morris H and Marschak, Jacob",
  abstract  = "A person deciding on a career, a wife, or a place to live bases
               his choice on two factors:(1) How much do I like each of the
               available alternatives? and (2) What are the chances for a
               successful outcome of each alternative? These two factors
               comprise the utility of each outcome for the person making the
               choice. This notion of utility is fundamental to most current
               theories of decision behavior. According to the expected utility
               hypothesis, if we could know the utility function of a person,
               we could predict his choice from among any set of …",
  journal   = "Behav. Sci.",
  publisher = "Wiley Online Library",
  volume    =  9,
  number    =  3,
  pages     = "226--232",
  year      =  1964
}

@ARTICLE{Rangel2010-ch,
  title     = "Neural computations associated with goal-directed choice",
  author    = "Rangel, Antonio and Hare, Todd",
  abstract  = "In goal-directed decision-making, animals choose between actions
               that are associated with different reward outcomes (e.g., foods)
               and with different costs (e.g., effort). Rapid advances have
               been made over the past few years in our understanding of the
               computations associated with goal-directed choices, and of how
               those computations are implemented in the brain. We review some
               important findings, with an emphasis on computational models,
               human fMRI, and monkey neurophysiology studies.",
  journal   = "Curr. Opin. Neurobiol.",
  publisher = "rnl.caltech.edu",
  volume    =  20,
  number    =  2,
  pages     = "262--270",
  month     =  apr,
  year      =  2010,
  language  = "en"
}

@MISC{noauthor_undated-xv,
  title    = "elegantscipy.pdf",
  keywords = "Python books;Books/Python"
}

@ARTICLE{Ramalho_undated-wv,
  title    = "{CLEAR}, {CONCISE}, {AND} {EFFECTIVE} {PROGRAMMING}",
  author   = "Ramalho, Luciano",
  keywords = "Python books;Books/Python"
}

@MISC{noauthor_undated-qc,
  title    = "introducingpython.pdf",
  keywords = "Python books;Books/Python"
}

@MISC{noauthor_undated-jh,
  title    = "naturallanguageprocessingwithpython.pdf",
  keywords = "Python books;Books/Python"
}

@ARTICLE{By_undated-ov,
  title    = "{ESSENTIAL} {TOOLS} {FOR} {WORKING} {WITH} {DATA}",
  author   = "By, Powered",
  keywords = "Python books;Books/Python"
}

@MISC{noauthor_undated-rx,
  title    = "thinkbayes.pdf",
  keywords = "Python books;Books/Python"
}

@ARTICLE{Kirk_undated-qt,
  title    = "A {TEST-DRIVEN} {APPROACHPython}",
  author   = "Kirk, Matthew",
  keywords = "Python books;Books/Python"
}

@MISC{noauthor_undated-pt,
  title    = "twistednetworkprogrammingessentials.pdf",
  keywords = "Python books;Books/Python"
}

@MISC{noauthor_undated-wa,
  title    = "webscrapingwithpython.pdf",
  keywords = "Python books;Books/Python"
}

@ARTICLE{Altshuler2005-ci,
  title     = "Symmetry breaking in escaping ants",
  author    = "Altshuler, E and Ramos, O and N{\'u}{\~n}ez, Y and
               Fern{\'a}ndez, J and Batista-Leyva, A J and Noda, C",
  abstract  = "The phenomenon of herding is a very general feature of the
               collective behavior of many species in panic conditions,
               including humans. It has been predicted theoretically that
               panic-induced herding in individuals confined to a room can
               produce a nonsymmetrical use of two identical exit doors. Here
               we demonstrate the existence of that phenomenon in experiments,
               using ants as a model of pedestrians. We show that ants confined
               to a cell with two symmetrically located exits use both exits in
               approximately equal proportions to abandon it in normal
               conditions but prefer one of the exits if panic is created by
               adding a repellent fluid. In addition, we are able to reproduce
               the observed escape dynamics in detail using a modification of a
               previous theoretical model that includes herding associated with
               a panic parameter as a central ingredient. Our experimental
               results, combined with theoretical models, suggest that some
               features of the collective behavior of humans and ants can be
               quite similar when escaping under panic.",
  journal   = "Am. Nat.",
  publisher = "journals.uchicago.edu",
  volume    =  166,
  number    =  6,
  pages     = "643--649",
  month     =  dec,
  year      =  2005,
  language  = "en"
}

@ARTICLE{Nicolis1999-xi,
  title     = "Emerging patterns and food recruitment in ants: an analytical
               study",
  author    = "Nicolis, S C and Deneubourg, J L",
  abstract  = "A model of food recruitment by social insects accounting for the
               competition between trails in the presence of an arbitrary
               number of sources is developed and analysed in detail. Both the
               case of identical environmental characteristics and the case
               where one source and the corresponding trail are different from
               the others are considered. Different collective responses
               depending on the environmental conditions, and without change of
               individual behaviour, are shown to exist, associated with the
               possibility that the colony may be led to exploit one source or
               a group of sources preferentially. The full bifurcation diagram
               of steady-state solutions is constructed from which the dominant
               exploitation patterns are identified. The biological relevance
               of the results is discussed and suggestions are made for their
               experimental testing in connection with the recruitment behavior
               of species using trail recruitment. The same phenomenological
               model can be used for different trail-laying species since the
               predictions are generic and not restricted to a given species,
               except for the parameter values used. Copyright 1999 Academic
               Press.",
  journal   = "J. Theor. Biol.",
  publisher = "Elsevier",
  volume    =  198,
  number    =  4,
  pages     = "575--592",
  month     =  jun,
  year      =  1999,
  language  = "en"
}

@TECHREPORT{Millonas1993-ss,
  title     = "Swarms, Phase Transitions, and Collective Intelligence (Paper
               1); and A Nonequilibrium Statistical Field Theory of Swarms and
               Other Spatially Extended Complex Systems (Paper 2)",
  author    = "Millonas, Mark M",
  abstract  = "(Paper 1) A spacially extended model of the collective behavior
               of a large number of locally acting organisms is proposed in
               which organisms move probabilistically between local cells in
               space, but with weights dependent on local morphogenetic
               substances, or morphogens. The morphogens are in turn effected
               by the passage of an organism. The evolution of the morphogens,
               and the corresponding flow of the organisms constitutes the
               collective behavior of the group. Such models have various types
               of phase transitions and self-organizing properties controlled
               both by the level of the noise, and other parameters. The model
               is then applied to the specific case of ants moving on a
               lattice. The local behavior of the ants is inspired by the
               actual behavior observed in the laboratory, and analytic results
               for the collective behavior are compared to the corresponding
               laboratory results. It is hoped that the present model might
               serve as a paradigmatic example of a complex cooperative system
               in nature. In particular swarm models can be used to explore the
               relation of nonequilibrium phase transitions to at least three
               important issues encountered in artificial life. Firstly, that
               of emergence as complex adaptive behavior. Secondly, as an
               exporation of continuous phase transitions in biological
               systems. Lastly, to derive behavioral criteria for the evolution
               of collective behavior in social organisms. (Paper 2) A class of
               models with applications to swarm behavior as well as many other
               types of spatially extended complex biological and physical
               systems is studied. Internal fluctuations can play an active
               role in the organization of the phase structure of such systems.
               Consequently, it is not possible to fully understand the
               behavior of these systems without explicitly incorporating the
               fluctuations. In particular, for the class of models studied
               here the effect of internal fluctuations due to finite size is a
               renormalized \{\textbackslashit decrease\} in the temperature
               near the point of spontaneous symmetry breaking. We briefly
               outline how these models can be applied to the behavior of an
               ant swarm.",
  publisher = "Santa Fe Institute",
  number    = "93-06-039",
  month     =  jun,
  year      =  1993
}

@ARTICLE{Marshall2009-pa,
  title     = "On optimal decision-making in brains and social insect colonies",
  author    = "Marshall, James A R and Bogacz, Rafal and Dornhaus, Anna and
               Planqu{\'e}, Robert and Kovacs, Tim and Franks, Nigel R",
  abstract  = "The problem of how to compromise between speed and accuracy in
               decision-making faces organisms at many levels of biological
               complexity. Striking parallels are evident between
               decision-making in primate brains and collective decision-making
               in social insect colonies: in both systems, separate populations
               accumulate evidence for alternative choices; when one population
               reaches a threshold, a decision is made for the corresponding
               alternative, and this threshold may be varied to compromise
               between the speed and the accuracy of decision-making. In
               primate decision-making, simple models of these processes have
               been shown, under certain parametrizations, to implement the
               statistically optimal procedure that minimizes decision time for
               any given error rate. In this paper, we adapt these same
               analysis techniques and apply them to new models of collective
               decision-making in social insect colonies. We show that social
               insect colonies may also be able to achieve statistically
               optimal collective decision-making in a very similar way to
               primate brains, via direct competition between
               evidence-accumulating populations. This optimality result makes
               testable predictions for how collective decision-making in
               social insects should be organized. Our approach also represents
               the first attempt to identify a common theoretical framework for
               the study of decision-making in diverse biological systems.",
  journal   = "J. R. Soc. Interface",
  publisher = "royalsocietypublishing.org",
  volume    =  6,
  number    =  40,
  pages     = "1065--1074",
  month     =  nov,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Detrain2006-vd,
  title     = "Self-organized structures in a superorganism: do ants ``behave''
               like molecules?",
  author    = "Detrain, Claire and Deneubourg, Jean-Louis",
  abstract  = "While the striking structures (e.g. nest architecture, trail
               networks) of insect societies may seem familiar to many of us,
               the understanding of pattern formation still constitutes a
               challenging problem. Over the last two decades,
               self-organization has dramatically changed our view on how
               collective decision-making and structures may emerge out of a
               population of ant workers having each their own individuality as
               well as a limited access to information. A variety of collective
               behaviour spontaneously outcome from multiple interactions
               between nestmates, even when there is no directing influence
               imposed by an external template, a pacemaker or a leader. By
               focussing this review on foraging structures, we show that ant
               societies display some properties which are usually considered
               in physico-chemical systems, as typical signatures of
               self-organization. We detail the key role played by feed-back
               loops, fluctuations, number of interacting units and sensitivity
               to environmental factors in the emergence of a structured
               collective behaviour. Nonetheless, going beyond simple analogies
               with non-living self-organized patterns, we stress on the
               specificities of social structures made of complex living units
               of which the biological features have been selected throughout
               the evolution depending on their adaptive value. In particular,
               we consider the ability of each ant individual to process
               information about environmental and social parameters, to
               accordingly tune its interactions with nestmates and ultimately
               to determine the final pattern emerging at the collective level.
               We emphasize on the parsimony and simplicity of behavioural
               rules at the individual level which allow an efficient
               processing of information, energy and matter within the whole
               colony.",
  journal   = "Phys. Life Rev.",
  publisher = "Elsevier",
  volume    =  3,
  number    =  3,
  pages     = "162--187",
  month     =  sep,
  year      =  2006,
  keywords  = "Self-organization; Decision-making; Pattern formation; Social
               insects; Foraging; Trail"
}

@ARTICLE{Mora2011-th,
  title     = "Are Biological Systems Poised at Criticality?",
  author    = "Mora, Thierry and Bialek, William",
  abstract  = "Many of life's most fascinating phenomena emerge from
               interactions among many elements---many amino acids determine
               the structure of a single protein, many genes determine the fate
               of a cell, many neurons are involved in shaping our thoughts and
               memories. Physicists have long hoped that these collective
               behaviors could be described using the ideas and methods of
               statistical mechanics. In the past few years, new, larger scale
               experiments have made it possible to construct statistical
               mechanics models of biological systems directly from real data.
               We review the surprising successes of this ``inverse'' approach,
               using examples from families of proteins, networks of neurons,
               and flocks of birds. Remarkably, in all these cases the models
               that emerge from the data are poised near a very special point
               in their parameter space---a critical point. This suggests there
               may be some deeper theoretical principle behind the behavior of
               these diverse systems.",
  journal   = "J. Stat. Phys.",
  publisher = "Springer",
  volume    =  144,
  number    =  2,
  pages     = "268--302",
  month     =  jul,
  year      =  2011
}

@ARTICLE{Sole1995-op,
  title     = "Information at the edge of chaos in fluid neural networks",
  author    = "Sol{\'e}, Ricard V and Miramontes, Octavio",
  abstract  = "Fluid neural networks, defined as neural nets of mobile elements
               with random activation, are studied by means of several
               approaches. They are proposed as a theoretical framework for a
               wide class of systems as insect societies, collectives of robots
               or the immune system. The critical properties of this model are
               also analysed, showing the existence of a critical boundary in
               parameter space where maximum information transfer occurs. In
               this sense, this boundary is in fact an example of the ``edge of
               chaos'' in systems like those described in our approach. Recent
               experiments with ant colonies seem to confirm our result.",
  journal   = "Physica D",
  publisher = "Elsevier",
  volume    =  80,
  number    =  1,
  pages     = "171--180",
  month     =  jan,
  year      =  1995
}

@ARTICLE{Baluska2016-po,
  title     = "On Having No Head: Cognition throughout Biological Systems",
  author    = "Balu{\v s}ka, Franti{\v s}ek and Levin, Michael",
  abstract  = "The central nervous system (CNS) underlies memory, perception,
               decision-making, and behavior in numerous organisms. However,
               neural networks have no monopoly on the signaling functions that
               implement these remarkable algorithms. It is often forgotten
               that neurons optimized cellular signaling modes that existed
               long before the CNS appeared during evolution, and were used by
               somatic cellular networks to orchestrate physiology, embryonic
               development, and behavior. Many of the key dynamics that enable
               information processing can, in fact, be implemented by different
               biological hardware. This is widely exploited by organisms
               throughout the tree of life. Here, we review data on memory,
               learning, and other aspects of cognition in a range of models,
               including single celled organisms, plants, and tissues in animal
               bodies. We discuss current knowledge of the molecular mechanisms
               at work in these systems, and suggest several hypotheses for
               future investigation. The study of cognitive processes
               implemented in aneural contexts is a fascinating, highly
               interdisciplinary topic that has many implications for
               evolution, cell biology, regenerative medicine, computer
               science, and synthetic bioengineering.",
  journal   = "Front. Psychol.",
  publisher = "frontiersin.org",
  volume    =  7,
  pages     = "902",
  month     =  jun,
  year      =  2016,
  keywords  = "aneural; bioelectric signaling; cognition; computation;
               information; learning; memory; plants",
  language  = "en"
}

@ARTICLE{Pinero_Jordi2019-zs,
  title     = "Statistical physics of liquid brains",
  author    = "{Pi{\~n}ero Jordi} and {Sol{\'e} Ricard}",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "Royal Society",
  volume    =  374,
  number    =  1774,
  pages     = "20180376",
  month     =  jun,
  year      =  2019
}

@ARTICLE{Niv2009-gn,
  title     = "Reinforcement learning in the brain",
  author    = "Niv, Yael",
  abstract  = "A wealth of research focuses on the decision-making processes
               that animals and humans employ when selecting actions in the
               face of reward and punishment. Initially such work stemmed from
               psychological investigations of conditioned behavior, and
               explanations of these in terms of computational models.
               Increasingly, analysis at the computational level has drawn on
               ideas from reinforcement learning, which provide a normative
               framework within which decision-making can be analyzed. More
               recently, the fruits of these extensive lines of research have
               made contact with investigations into the neural basis of
               decision making. Converging evidence now links reinforcement
               learning to specific neural substrates, assigning them precise
               computational roles. Specifically, electrophysiological
               recordings in behaving animals and functional imaging of human
               decision-making have revealed in the brain the existence of a
               key reinforcement learning signal, the temporal difference
               reward prediction error. Here, we first introduce the formal
               reinforcement learning framework. We then review the multiple
               lines of evidence linking reinforcement learning to the function
               of dopaminergic neurons in the mammalian midbrain and to more
               recent data from human imaging experiments. We further extend
               the discussion to aspects of learning not associated with phasic
               dopamine signals, such as learning of goal-directed responding
               that may not be dopamine-dependent, and learning about the vigor
               (or rate) with which actions should be performed that has been
               linked to tonic aspects of dopaminergic signaling. We end with a
               brief discussion of some of the limitations of the reinforcement
               learning framework, highlighting questions for future research.",
  journal   = "J. Math. Psychol.",
  publisher = "Elsevier",
  volume    =  53,
  number    =  3,
  pages     = "139--154",
  month     =  jun,
  year      =  2009
}

@ARTICLE{Friston2010-yo,
  title    = "The free-energy principle: a unified brain theory?",
  author   = "Friston, Karl",
  abstract = "A free-energy principle has been proposed recently that accounts
              for action, perception and learning. This Review looks at some
              key brain theories in the biological (for example, neural
              Darwinism) and physical (for example, information theory and
              optimal control theory) sciences from the free-energy
              perspective. Crucially, one key theme runs through each of these
              theories - optimization. Furthermore, if we look closely at what
              is optimized, the same quantity keeps emerging, namely value
              (expected reward, expected utility) or its complement, surprise
              (prediction error, expected cost). This is the quantity that is
              optimized under the free-energy principle, which suggests that
              several global brain theories might be unified within a
              free-energy framework.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  11,
  number   =  2,
  pages    = "127--138",
  month    =  feb,
  year     =  2010,
  language = "en"
}

@MISC{Murphy_undated-zd,
  title    = "Machine Learning - A Probabilistic Perspective",
  author   = "{Murphy}",
  keywords = "books;Books"
}

@ARTICLE{Botvinick2012-ho,
  title    = "Planning as inference",
  author   = "Botvinick, Matthew and Toussaint, Marc",
  abstract = "Recent developments in decision-making research are bringing the
              topic of planning back to center stage in cognitive science. This
              renewed interest reopens an old, but still unanswered question:
              how exactly does planning happen? What are the underlying
              information processing operations and how are they implemented in
              the brain? Although a range of interesting possibilities exists,
              recent work has introduced a potentially transformative new idea,
              according to which planning is accomplished through probabilistic
              inference.",
  journal  = "Trends Cogn. Sci.",
  volume   =  16,
  number   =  10,
  pages    = "485--488",
  month    =  oct,
  year     =  2012,
  language = "en"
}

@ARTICLE{Kraus2013-yt,
  title    = "Hippocampal ``time cells'': time versus path integration",
  author   = "Kraus, Benjamin J and Robinson, 2nd, Robert J and White, John A
              and Eichenbaum, Howard and Hasselmo, Michael E",
  abstract = "Recent studies have reported the existence of hippocampal ``time
              cells,'' neurons that fire at particular moments during periods
              when behavior and location are relatively constant. However, an
              alternative explanation of apparent time coding is that
              hippocampal neurons ``path integrate'' to encode the distance an
              animal has traveled. Here, we examined hippocampal neuronal
              firing patterns as rats ran in place on a treadmill, thus
              ``clamping'' behavior and location, while we varied the treadmill
              speed to distinguish time elapsed from distance traveled.
              Hippocampal neurons were strongly influenced by time and
              distance, and less so by minor variations in location.
              Furthermore, the activity of different neurons reflected
              integration over time and distance to varying extents, with most
              neurons strongly influenced by both factors and some
              significantly influenced by only time or distance. Thus,
              hippocampal neuronal networks captured both the organization of
              time and distance in a situation where these dimensions dominated
              an ongoing experience.",
  journal  = "Neuron",
  volume   =  78,
  number   =  6,
  pages    = "1090--1101",
  month    =  jun,
  year     =  2013,
  language = "en"
}

@ARTICLE{Smith2012-nb,
  title    = "Reversible online control of habitual behavior by optogenetic
              perturbation of medial prefrontal cortex",
  author   = "Smith, Kyle S and Virkud, Arti and Deisseroth, Karl and Graybiel,
              Ann M",
  abstract = "Habits tend to form slowly but, once formed, can have great
              stability. We probed these temporal characteristics of habitual
              behaviors by intervening optogenetically in forebrain habit
              circuits as rats performed well-ingrained habitual runs in a
              T-maze. We trained rats to perform a maze habit, confirmed the
              habitual behavior by devaluation tests, and then, during the maze
              runs (ca. 3 s), we disrupted population activity in a small
              region in the medial prefrontal cortex, the infralimbic cortex.
              In accordance with evidence that this region is necessary for the
              expression of habits, we found that this cortical disruption
              blocked habitual behavior. Notably, however, this blockade of
              habitual performance occurred on line, within an average of three
              trials (ca. 9 s of inhibition), and as soon as during the first
              trial (<3 s). During subsequent weeks of training, the rats
              acquired a new behavioral pattern. When we again imposed the same
              cortical perturbation, the rats regained the suppressed
              maze-running that typified the original habit, and,
              simultaneously, the more recently acquired habit was blocked.
              These online changes occurred within an average of two trials
              (ca. 6 s of infralimbic inhibition). Measured changes in
              generalized performance ability and motivation to consume reward
              were unaffected. This immediate toggling between breaking old
              habits and returning to them demonstrates that even semiautomatic
              behaviors are under cortical control and that this control occurs
              online, second by second. These temporal characteristics define a
              framework for uncovering cellular transitions between fixed and
              flexible behaviors, and corresponding disturbances in
              pathologies.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  109,
  number   =  46,
  pages    = "18932--18937",
  month    =  nov,
  year     =  2012,
  language = "en"
}

@ARTICLE{Gruber2012-nm,
  title    = "Context, emotion, and the strategic pursuit of goals:
              interactions among multiple brain systems controlling motivated
              behavior",
  author   = "Gruber, Aaron J and McDonald, Robert J",
  abstract = "Motivated behavior exhibits properties that change with
              experience and partially dissociate among a number of brain
              structures. Here, we review evidence from rodent experiments
              demonstrating that multiple brain systems acquire information in
              parallel and either cooperate or compete for behavioral control.
              We propose a conceptual model of systems interaction wherein a
              ventral emotional memory network involving ventral striatum (VS),
              amygdala, ventral hippocampus, and ventromedial prefrontal cortex
              triages behavioral responding to stimuli according to their
              associated affective outcomes. This system engages autonomic and
              postural responding (avoiding, ignoring, approaching) in
              accordance with associated stimulus valence (negative, neutral,
              positive), but does not engage particular operant responses.
              Rather, this emotional system suppresses or invigorates actions
              that are selected through competition between goal-directed
              control involving dorsomedial striatum (DMS) and habitual control
              involving dorsolateral striatum (DLS). The hippocampus provides
              contextual specificity to the emotional system, and provides an
              information rich input to the goal-directed system for navigation
              and discriminations involving ambiguous contexts, complex sensory
              configurations, or temporal ordering. The rapid acquisition and
              high capacity for episodic associations in the emotional system
              may unburden the more complex goal-directed system and reduce
              interference in the habit system from processing contingencies of
              neutral stimuli. Interactions among these systems likely involve
              inhibitory mechanisms and neuromodulation in the striatum to form
              a dominant response strategy. Innate traits, training methods,
              and task demands contribute to the nature of these interactions,
              which can include incidental learning in non-dominant systems.
              Addition of these features to reinforcement learning models of
              decision-making may better align theoretical predictions with
              behavioral and neural correlates in animals.",
  journal  = "Front. Behav. Neurosci.",
  volume   =  6,
  pages    = "50",
  month    =  aug,
  year     =  2012,
  keywords = "Pavlovian-instrumental transfer; amygdala; dopamine; emotion;
              hippocampus; inhibition; reinforcement learning; striatum",
  language = "en"
}

@ARTICLE{Bornstein2011-xi,
  title    = "Multiplicity of control in the basal ganglia: computational roles
              of striatal subregions",
  author   = "Bornstein, Aaron M and Daw, Nathaniel D",
  abstract = "The basal ganglia, in particular the striatum, are central to
              theories of behavioral control, and often identified as a seat of
              action selection. Reinforcement learning (RL) models--which have
              driven much recent experimental work on this region--cast
              striatum as a dynamic controller, integrating sensory and
              motivational information to construct efficient and enriching
              behavioral policies. Befitting this informationally central role,
              the BG sit at the nexus of multiple anatomical 'loops' of
              synaptic projections, connecting a wide range of cortical and
              subcortical structures. Numerous pioneering anatomical studies
              conducted over the past several decades have meticulously
              catalogued these loops, and labeled them according to the
              inferred functions of the connected regions. The specific
              cotermina of the projections are highly localized to several
              different subregions of the striatum, leading to the suggestion
              that these subregions perform complementary but distinct
              functions. However, until recently, the dominant computational
              framework outlined only a bipartite, dorsal/ventral, division of
              striatum. We review recent computational and experimental
              advances that argue for a more finely fractionated delineation.
              In particular, experimental data provide extensive insight into
              unique functions subserved by the dorsomedial striatum (DMS).
              These functions appear to correspond well with theories of a
              'model-based' RL subunit, and may also shed light on the
              suborganization of ventral striatum. Finally, we discuss the
              limitations of these ideas and how they point the way toward
              future refinements of neurocomputational theories of striatal
              function, bringing them into contact with other areas of
              computational theory and other regions of the brain.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  21,
  number   =  3,
  pages    = "374--380",
  month    =  jun,
  year     =  2011,
  language = "en"
}

@ARTICLE{Cooper2006-gu,
  title     = "Hierarchical schemas and goals in the control of sequential
               behavior",
  author    = "Cooper, Richard P and Shallice, Tim",
  abstract  = "Traditional accounts of sequential behavior assume that schemas
               and goals play a causal role in the control of behavior. In
               contrast, M. Botvinick and D. C. Plaut argued that, at least in
               routine behavior, schemas and goals are epiphenomenal. The
               authors evaluate the Botvinick and Plaut account by contrasting
               the simple recurrent network model of Botvinick and Plaut with
               their own more traditional hierarchically structured interactive
               activation model (R. P. Cooper \& T. Shallice, 2000). The
               authors present a range of arguments and additional simulations
               that demonstrate theoretical and empirical difficulties for both
               Botvinick and Plaut's model and their theoretical position. The
               authors conclude that explicit hierarchically organized and
               causally efficacious schema and goal representations are
               required to provide an adequate account of the flexibility of
               sequential behavior.",
  journal   = "Psychol. Rev.",
  publisher = "psycnet.apa.org",
  volume    =  113,
  number    =  4,
  pages     = "887--916; discussion 917--31",
  month     =  oct,
  year      =  2006,
  language  = "en"
}

@ARTICLE{Botvinick2006-ux,
  title     = "Such stuff as habits are made on: A reply to Cooper and Shallice
               (2006)",
  author    = "Botvinick, Matthew M and Plaut, David C",
  abstract  = "The representations and mechanisms guiding everyday routine
               sequential action remain incompletely understood. In recent
               work, the authors proposed a computational model of routine
               sequential behavior that took the form of a recurrent neural
               network (M. Botvinick \& D. C. Plaut, 2004; see record
               2004-12248-005). Subsequently, R. P. Cooper and T. Shallice
               (2006; see record 2006-12689-008) put forth a detailed critique
               of that work, contrasting it with their own account, which
               assumes a strict hierarchical processing system (R. P. Cooper \&
               T. Shallice, 2000; see record 2000-03986-001). The authors
               respond here to the main points of R. P. Cooper and T.
               Shallice's (2006) critique. Although careful and constructive,
               the arguments offered by R. P. Cooper and T. Shallice (2006)
               mistook several superficial implementational issues for
               fundamental theoretical ones, underestimated the computational
               power of recurrent networks as a class, and in some ways
               mischaracterized the relationship between the accounts they
               compare. In responding to these points, the authors articulate
               several key theoretical choices facing models of routine
               sequential behavior. (PsycINFO Database Record (c) 2016 APA, all
               rights reserved)",
  journal   = "Psychol. Rev.",
  publisher = "psycnet.apa.org",
  volume    =  113,
  number    =  4,
  pages     = "917--927",
  month     =  oct,
  year      =  2006
}

@ARTICLE{Botvinick2008-sh,
  title     = "Hierarchical models of behavior and prefrontal function",
  author    = "Botvinick, Matthew M",
  abstract  = "The recognition of hierarchical structure in human behavior was
               one of the founding insights of the cognitive revolution.
               Despite decades of research, however, the computational
               mechanisms underlying hierarchically organized behavior are
               still not fully understood. Recent findings from behavioral and
               neuroscientific research have fueled a resurgence of interest in
               the problem, inspiring a new generation of computational models.
               In addition to developing some classic proposals, these models
               also break fresh ground, teasing apart different forms of
               hierarchical structure, placing a new focus on the issue of
               learning and addressing recent findings concerning the
               representation of behavioral hierarchies within the prefrontal
               cortex. In addition to offering explanations for some key
               aspects of behavior and functional neuroanatomy, the latest
               models also pose new questions for empirical research.",
  journal   = "Trends Cogn. Sci.",
  publisher = "Elsevier",
  volume    =  12,
  number    =  5,
  pages     = "201--208",
  month     =  may,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Dayan1995-ai,
  title     = "The Helmholtz machine",
  author    = "Dayan, P and Hinton, G E and Neal, R M and Zemel, R S",
  abstract  = "Discovering the structure inherent in a set of patterns is a
               fundamental aim of statistical inference or learning. One
               fruitful approach is to build a parameterized stochastic
               generative model, independent draws from which are likely to
               produce the patterns. For all but the simplest generative
               models, each pattern can be generated in exponentially many
               ways. It is thus intractable to adjust the parameters to
               maximize the probability of the observed patterns. We describe a
               way of finessing this combinatorial explosion by maximizing an
               easily computed lower bound on the probability of the
               observations. Our method can be viewed as a form of hierarchical
               self-supervised learning that may relate to the function of
               bottom-up and top-down cortical processing pathways.",
  journal   = "Neural Comput.",
  publisher = "MIT Press",
  volume    =  7,
  number    =  5,
  pages     = "889--904",
  month     =  sep,
  year      =  1995,
  language  = "en"
}

@ARTICLE{Gatto2018-oi,
  title    = "Locomotion Control: Brainstem Circuits Satisfy the Need for Speed",
  author   = "Gatto, Graziana and Goulding, Martyn",
  abstract = "Three new and closely complementary studies have defined the
              architecture of the circuits underlying the descending control of
              locomotion, identifying neurons that drive fast motor responses
              and those that seem to be specialised for exploratory behaviors.",
  journal  = "Curr. Biol.",
  volume   =  28,
  number   =  6,
  pages    = "R256--R259",
  month    =  mar,
  year     =  2018,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{Corrado2007-ds,
  title    = "Understanding neural coding through the model-based analysis of
              decision making",
  author   = "Corrado, Greg and Doya, Kenji",
  abstract = "The study of decision making poses new methodological challenges
              for systems neuroscience. Whereas our traditional approach linked
              neural activity to external variables that the experimenter
              directly observed and manipulated, many of the key elements that
              contribute to decisions are internal to the decider. Variables
              such as subjective value or subjective probability may be
              influenced by experimental conditions and manipulations but can
              neither be directly measured nor precisely controlled. Pioneering
              work on the neural basis of decision circumvented this difficulty
              by studying behavior in static conditions, in which knowledge of
              the average state of these quantities was sufficient. More
              recently, a new wave of studies has confronted the conundrum of
              internal decision variables more directly by leveraging
              quantitative behavioral models. When these behavioral models are
              successful in predicting a subject's choice, the model's internal
              variables may serve as proxies for the unobservable decision
              variables that actually drive behavior. This new methodology has
              allowed researchers to localize neural subsystems that encode
              hidden decision variables related to free choice and to study
              these variables under dynamic conditions.",
  journal  = "J. Neurosci.",
  volume   =  27,
  number   =  31,
  pages    = "8178--8180",
  month    =  aug,
  year     =  2007,
  language = "en"
}

@ARTICLE{Hikosaka2010-ql,
  title    = "The habenula: from stress evasion to value-based decision-making",
  author   = "Hikosaka, Okihide",
  abstract = "Surviving in a world with hidden rewards and dangers requires
              choosing the appropriate behaviours. Recent discoveries indicate
              that the habenula plays a prominent part in such behavioural
              choice through its effects on neuromodulator systems, in
              particular the dopamine and serotonin systems. By inhibiting
              dopamine-releasing neurons, habenula activation leads to the
              suppression of motor behaviour when an animal fails to obtain a
              reward or anticipates an aversive outcome. Moreover, the habenula
              is involved in behavioural responses to pain, stress, anxiety,
              sleep and reward, and its dysfunction is associated with
              depression, schizophrenia and drug-induced psychosis. As a highly
              conserved structure in the brain, the habenula provides a
              fundamental mechanism for both survival and decision-making.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  11,
  number   =  7,
  pages    = "503--513",
  month    =  jul,
  year     =  2010,
  language = "en"
}

@ARTICLE{Balleine2007-qv,
  title    = "The role of the dorsal striatum in reward and decision-making",
  author   = "Balleine, Bernard W and Delgado, Mauricio R and Hikosaka, Okihide",
  abstract = "Although the involvement in the striatum in the refinement and
              control of motor movement has long been recognized, recent
              description of discrete frontal corticobasal ganglia networks in
              a range of species has focused attention on the role particularly
              of the dorsal striatum in executive functions. Current evidence
              suggests that the dorsal striatum contributes directly to
              decision-making, especially to action selection and initiation,
              through the integration of sensorimotor, cognitive, and
              motivational/emotional information within specific
              corticostriatal circuits involving discrete regions of striatum.
              We review key evidence from recent studies in rodent, nonhuman
              primate, and human subjects.",
  journal  = "J. Neurosci.",
  volume   =  27,
  number   =  31,
  pages    = "8161--8165",
  month    =  aug,
  year     =  2007,
  language = "en"
}

@ARTICLE{Hanks2017-mu,
  title    = "Perceptual Decision Making in Rodents, Monkeys, and Humans",
  author   = "Hanks, Timothy D and Summerfield, Christopher",
  abstract = "Perceptual decision making is the process by which animals
              detect, discriminate, and categorize information from the senses.
              Over the past two decades, understanding how perceptual decisions
              are made has become a central theme in the neurosciences.
              Exceptional progress has been made by recording from single
              neurons in the cortex of the macaque monkey and using
              computational models from mathematical psychology to relate these
              neural data to behavior. More recently, however, the range of
              available techniques and paradigms has dramatically broadened,
              and researchers have begun to harness new approaches to explore
              how rodents and humans make perceptual decisions. The results
              have illustrated some striking convergences with findings from
              the monkey, but also raised new questions and provided new
              theoretical insights. In this review, we summarize key findings,
              and highlight open challenges, for understanding perceptual
              decision making in rodents, monkeys, and humans.",
  journal  = "Neuron",
  volume   =  93,
  number   =  1,
  pages    = "15--31",
  month    =  jan,
  year     =  2017,
  keywords = "confidence; decision making; functional neuroimaging; human;
              non-human primate; parietal cortex; psychophysics; rodent;
              single-cell recordings",
  language = "en"
}

@ARTICLE{Dalley2004-ta,
  title    = "Prefrontal executive and cognitive functions in rodents: neural
              and neurochemical substrates",
  author   = "Dalley, Jeffrey W and Cardinal, Rudolf N and Robbins, Trevor W",
  abstract = "The prefrontal cortex has been implicated in a variety of
              cognitive and executive processes, including working memory,
              decision-making, inhibitory response control, attentional
              set-shifting and the temporal integration of voluntary behaviour.
              This article reviews current progress in our understanding of the
              rodent prefrontal cortex, especially evidence for functional
              divergence of the anatomically distinct sub-regions of the rat
              prefrontal cortex. Recent findings suggest clear distinctions
              between the dorsal (precentral and anterior cingulate) and
              ventral (prelimbic, infralimbic and medial orbital) sub-divisions
              of the medial prefrontal cortex, and between the orbitofrontal
              cortex (ventral orbital, ventrolateral orbital, dorsal and
              ventral agranular cortices) and the adjacent medial wall of the
              prefrontal cortex. The dorso-medial prefrontal cortex is
              implicated in memory for motor responses, including response
              selection, and the temporal processing of information. Ventral
              regions of the medial prefrontal cortex are implicated in
              interrelated 'supervisory' attentional functions, including
              attention to stimulus features and task contingencies (or
              action-outcome rules), attentional set-shifting, and behavioural
              flexibility. The orbitofrontal cortex is implicated in
              lower-order discriminations, including reversal of
              stimulus-reward associations (reversal learning), and choice
              involving delayed reinforcement. It is anticipated that a greater
              understanding of the prefrontal cortex will come from using tasks
              that load specific cognitive and executive processes, in parallel
              with discovering new ways of manipulating the different
              sub-regions and neuromodulatory systems of the prefrontal cortex.",
  journal  = "Neurosci. Biobehav. Rev.",
  volume   =  28,
  number   =  7,
  pages    = "771--784",
  month    =  nov,
  year     =  2004,
  language = "en"
}

@ARTICLE{Coutlee2012-hy,
  title    = "The functional neuroanatomy of decision making: prefrontal
              control of thought and action",
  author   = "Coutlee, Christopher G and Huettel, Scott A",
  abstract = "Humans exhibit a remarkable capacity for flexible thought and
              action. Despite changing internal needs and external context,
              individuals maintain stable goals and pursue purposeful action.
              Functional neuroimaging research examining the neural
              underpinnings of such behavioral flexibility has progressed
              within several distinct traditions, as evident in the largely
              separate literatures on ``cognitive control'' and on ``decision
              making.'' Both topics investigate the formulation of desires and
              intentions, the integration of knowledge and context, and the
              resolution of conflict and uncertainty. Additionally, each
              recognizes the fundamental role of the prefrontal cortex in
              supporting flexible selection of behavior. But despite this
              notable overlap, neuroimaging studies in cognitive control and
              decision making have exerted only limited influence on each
              other, in part due to differences in their theoretical and
              experimental groundings. Additionally, the precise organization
              of control processing within prefrontal cortex has remained
              unclear, fostering an acceptance of vague descriptions of
              decision making in terms of canonical cognitive control functions
              such as ``inhibition'' or ``self-control.'' We suggest a unifying
              role for models of the hierarchical organization of action
              selection within prefrontal cortex. These models provide an
              important conceptual link between decision-making phenomena and
              cognitive-control processes, potentially facilitating
              cross-fertilization between these topics.",
  journal  = "Brain Res.",
  volume   =  1428,
  pages    = "3--12",
  month    =  jan,
  year     =  2012,
  language = "en"
}

@ARTICLE{Clark2004-oz,
  title    = "The neuropsychology of ventral prefrontal cortex: decision-making
              and reversal learning",
  author   = "Clark, L and Cools, R and Robbins, T W",
  abstract = "Converging evidence from human lesion, animal lesion, and human
              functional neuroimaging studies implicates overlapping neural
              circuitry in ventral prefrontal cortex in decision-making and
              reversal learning. The ascending 5-HT and dopamine
              neurotransmitter systems have a modulatory role in both
              processes. There is accumulating evidence that measures of
              decision-making and reversal learning may be useful as functional
              markers of ventral prefrontal cortex integrity in psychiatric and
              neurological disorders. Whilst existing measures of
              decision-making may have superior sensitivity, reversal learning
              may offer superior selectivity, particularly within prefrontal
              cortex. Effective decision-making on existing measures requires
              the ability to adapt behaviour on the basis of changes in
              emotional significance, and this may underlie the shared neural
              circuitry with reversal learning.",
  journal  = "Brain Cogn.",
  volume   =  55,
  number   =  1,
  pages    = "41--53",
  month    =  jun,
  year     =  2004,
  language = "en"
}

@ARTICLE{Doya2008-qf,
  title    = "Modulators of decision making",
  author   = "Doya, Kenji",
  abstract = "Human and animal decisions are modulated by a variety of
              environmental and intrinsic contexts. Here I consider
              computational factors that can affect decision making and review
              anatomical structures and neurochemical systems that are related
              to contextual modulation of decision making. Expectation of a
              high reward can motivate a subject to go for an action despite a
              large cost, a decision that is influenced by dopamine in the
              anterior cingulate cortex. Uncertainty of action outcomes can
              promote risk taking and exploratory choices, in which
              norepinephrine and the orbitofrontal cortex appear to be
              involved. Predictable environments should facilitate
              consideration of longer-delayed rewards, which depends on
              serotonin in the dorsal striatum and dorsal prefrontal cortex.
              This article aims to sort out factors that affect the process of
              decision making from the viewpoint of reinforcement learning
              theory and to bridge between such computational needs and their
              neurophysiological substrates.",
  journal  = "Nat. Neurosci.",
  volume   =  11,
  number   =  4,
  pages    = "410--416",
  month    =  apr,
  year     =  2008,
  language = "en"
}

@ARTICLE{Frank2006-an,
  title    = "Hold your horses: a dynamic computational role for the
              subthalamic nucleus in decision making",
  author   = "Frank, Michael J",
  abstract = "The basal ganglia (BG) coordinate decision making processes by
              facilitating adaptive frontal motor commands while suppressing
              others. In previous work, neural network simulations accounted
              for response selection deficits associated with BG dopamine
              depletion in Parkinson's disease. Novel predictions from this
              model have been subsequently confirmed in Parkinson patients and
              in healthy participants under pharmacological challenge.
              Nevertheless, one clear limitation of that model is in its
              omission of the subthalamic nucleus (STN), a key BG structure
              that participates in both motor and cognitive processes. The
              present model incorporates the STN and shows that by modulating
              when a response is executed, the STN reduces premature responding
              and therefore has substantial effects on which response is
              ultimately selected, particularly when there are multiple
              competing responses. Increased cortical response conflict leads
              to dynamic adjustments in response thresholds via
              cortico-subthalamic-pallidal pathways. The model accurately
              captures the dynamics of activity in various BG areas during
              response selection. Simulated dopamine depletion results in
              emergent oscillatory activity in BG structures, which has been
              linked with Parkinson's tremor. Finally, the model accounts for
              the beneficial effects of STN lesions on these oscillations, but
              suggests that this benefit may come at the expense of impaired
              decision making.",
  journal  = "Neural Netw.",
  volume   =  19,
  number   =  8,
  pages    = "1120--1136",
  month    =  oct,
  year     =  2006,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Olson2017-vi,
  title    = "Subiculum neurons map the current axis of travel",
  author   = "Olson, Jacob M and Tongprasearth, Kanyanat and Nitz, Douglas A",
  abstract = "Flexible navigation demands knowledge of boundaries, routes and
              their relationships. Within a multi-path environment, a
              subpopulation of subiculum neurons robustly encoded the axis of
              travel. The firing of axis-tuned neurons peaked bimodally, at
              head orientations 180° apart. Environmental manipulations showed
              these neurons to be anchored to environmental boundaries but to
              lack axis tuning in an open arena. Axis-tuned neurons thus
              provide a powerful mechanism for mapping relationships between
              routes and the larger environmental context.",
  journal  = "Nat. Neurosci.",
  volume   =  20,
  number   =  2,
  pages    = "170--172",
  month    =  feb,
  year     =  2017,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@UNPUBLISHED{Lee2019-qv,
  title    = "The statistical structure of the hippocampal code for space as a
              function of time, context, and value",
  author   = "Lee, Jae Sung and Briguglio, John and Romani, Sandro and Lee,
              Albert K",
  abstract = "Hippocampal activity represents many behaviorally important
              variables, including context, an animal9s location within a given
              environmental context, time, and reward. Here we used
              longitudinal calcium imaging in mice, multiple large virtual
              environments, and differing reward contingencies to derive a
              unified probabilistic model of hippocampal CA1 representations
              centered on a single feature − the field propensity. Each cell9s
              propensity governs how many place fields it has per unit space,
              predicts its reward−related activity, and is preserved across
              distinct environments and over months. The propensity is broadly
              distributed−with many low, and some very high, propensity cells
              −and thus strongly shapes hippocampal representations. The result
              is a range of spatial codes, from sparse to dense. Propensity
              varied ~10−fold between adjacent cells in a salt-and-pepper
              fashion, indicating substantial functional differences within a
              presumed cell type. The stability of each cell9s propensity
              across conditions suggests this fundamental property has
              anatomical, transcriptional, and/or developmental origins.",
  journal  = "bioRxiv",
  pages    = "615203",
  month    =  apr,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Pisupati2019-mc,
  title    = "Lapses in perceptual judgments reflect exploration",
  author   = "Pisupati, Sashank and Chartarifsky-Lynn, Lital and Khanal, Anup
              and Churchland, Anne K",
  abstract = "During perceptual decision making, subjects often display a
              constant rate of errors independent of evidence strength,
              referred to as lapses. Their proper treatment is crucial for
              accurate estimation of perceptual parameters, however they are
              often treated as a nuisance arising from motor errors or
              inattention. Here, we propose that lapses can instead reflect a
              dynamic form of exploration. We demonstrate that perceptual
              uncertainty modulates the probability of lapses both across and
              within modalities on a multisensory discrimination task in rats.
              These effects cannot be accounted for by inattention or motor
              error, however they are concisely explained by uncertainty-guided
              exploration. We confirm the predictions of the exploration model
              by showing that changing the magnitude or probability of reward
              associated with one of the decisions selectively affects the
              lapses associated with that decision in uncertain conditions,
              while leaving sure-bet decisions unchanged, as predicted by the
              model. Finally, we demonstrate that muscimol inactivations of
              secondary motor cortex and posterior striatum affect lapses
              asymmetrically across modalities. The inactivations can be
              captured by a devaluation of actions corresponding to the
              inactivated side, and do not affect sure-bet decisions. Together,
              our results suggest that far from being a nuisance, lapses are
              informative about subjects9 action values, and deficits thereof,
              during perceptual decisions.",
  journal  = "bioRxiv",
  pages    = "613828",
  month    =  apr,
  year     =  2019,
  language = "en"
}

@ARTICLE{De_Cheveigne2019-ab,
  title    = "Filters: When, Why, and How (Not) to Use Them",
  author   = "de Cheveign{\'e}, Alain and Nelken, Israel",
  abstract = "Filters are commonly used to reduce noise and improve data
              quality. Filter theory is part of a scientist's training, yet the
              impact of filters on interpreting data is not always fully
              appreciated. This paper reviews the issue and explains what a
              filter is, what problems are to be expected when using them, how
              to choose the right filter, and how to avoid filtering by using
              alternative tools. Time-frequency analysis shares some of the
              same problems that filters have, particularly in the case of
              wavelet transforms. We recommend reporting filter characteristics
              with sufficient details, including a plot of the impulse or step
              response as an inset.",
  journal  = "Neuron",
  volume   =  102,
  number   =  2,
  pages    = "280--293",
  month    =  apr,
  year     =  2019,
  keywords = "Fourier analysis; causality; distortions; filter; impulse
              response; oscillations; ringing; time-frequency representation",
  language = "en"
}

@ARTICLE{Berridge2004-eo,
  title     = "Motivation concepts in behavioral neuroscience",
  author    = "Berridge, Kent C",
  abstract  = "Concepts of motivation are vital to progress in behavioral
               neuroscience. Motivational concepts help us to understand what
               limbic brain systems are chiefly evolved to do, i.e., to mediate
               psychological processes that guide real behavior. This article
               evaluates some major motivation concepts that have historic
               importance or have influenced the interpretation of behavioral
               neuroscience research. These concepts include homeostasis,
               setpoints and settling points, intervening variables, hydraulic
               drives, drive reduction, appetitive and consummatory behavior,
               opponent processes, hedonic reactions, incentive motivation,
               drive centers, dedicated drive neurons (and drive neuropeptides
               and receptors), neural hierarchies, and new concepts from
               affective neuroscience such as allostasis, cognitive incentives,
               and reward 'liking' versus 'wanting'.",
  journal   = "Physiol. Behav.",
  publisher = "Elsevier",
  volume    =  81,
  number    =  2,
  pages     = "179--209",
  month     =  apr,
  year      =  2004,
  language  = "en"
}

@ARTICLE{Gottlieb2018-jh,
  title     = "Towards a neuroscience of active sampling and curiosity",
  author    = "Gottlieb, Jacqueline and Oudeyer, Pierre-Yves",
  abstract  = "In natural behaviour, animals actively interrogate their
               environments using endogenously generated 'question-and-answer'
               strategies. However, in laboratory settings participants
               typically engage with externally imposed stimuli and tasks, and
               the mechanisms of active sampling remain poorly understood. We
               review a nascent neuroscientific literature that examines
               active-sampling policies and their relation to attention and
               curiosity. We distinguish between information sampling, in which
               organisms reduce uncertainty relevant to a familiar task, and
               information search, in which they investigate in an open-ended
               fashion to discover new tasks. We review evidence that both
               sampling and search depend on individual preferences over
               cognitive states, including attitudes towards uncertainty,
               learning progress and types of information. We propose that,
               although these preferences are non-instrumental and can on
               occasion interfere with external goals, they are important
               heuristics that allow organisms to cope with the high complexity
               of both sampling and search, and generate curiosity-driven
               investigations in large, open environments in which rewards are
               sparse and ex ante unknown.",
  journal   = "Nat. Rev. Neurosci.",
  publisher = "nature.com",
  volume    =  19,
  number    =  12,
  pages     = "758--770",
  month     =  dec,
  year      =  2018,
  language  = "en"
}

@ARTICLE{Dayan2008-jq,
  title     = "Decision theory, reinforcement learning, and the brain",
  author    = "Dayan, Peter and Daw, Nathaniel D",
  abstract  = "Decision making is a core competence for animals and humans
               acting and surviving in environments they only partially
               comprehend, gaining rewards and punishments for their troubles.
               Decision-theoretic concepts permeate experiments and
               computational models in ethology, psychology, and neuroscience.
               Here, we review a well-known, coherent Bayesian approach to
               decision making, showing how it unifies issues in Markovian
               decision problems, signal detection psychophysics, sequential
               sampling, and optimal exploration and discuss paradigmatic
               psychological and neural examples of each problem. We discuss
               computational issues concerning what subjects know about their
               task and how ambitious they are in seeking optimal solutions; we
               address algorithmic topics concerning model-based and model-free
               methods for making choices; and we highlight key aspects of the
               neural implementation of decision making.",
  journal   = "Cogn. Affect. Behav. Neurosci.",
  publisher = "Springer",
  volume    =  8,
  number    =  4,
  pages     = "429--453",
  month     =  dec,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Jiang2019-in,
  title    = "{Short-Term} Influence of Recent Trial History on Perceptual
              Choice Changes with Stimulus Strength",
  author   = "Jiang, Weiqian and Liu, Jing and Zhang, Dinghong and Xie, Taorong
              and Yao, Haishan",
  abstract = "Perceptual decisions, especially for difficult stimuli, can be
              influenced by choices and outcomes in previous trials. However,
              it is not well understood how stimulus strength modulates the
              temporal characteristics as well as the magnitude of trial
              history influence. We addressed this question using a contrast
              detection task in freely moving mice. We found that, at lower as
              compared to higher stimulus contrast, the current choice of the
              mice was more influenced by choices and outcomes in the past
              trials and the influence emerged from a longer history. To
              examine the neural basis of stimulus strength-dependent history
              influence, we recorded from the secondary motor cortex (M2), a
              prefrontal region that plays an important role in cue-guided
              actions and memory-guided behaviors. We found that more M2
              neurons conveyed information about choices on the past two trials
              at lower than at higher contrast. Furthermore, history-trial
              activity in M2 was important for decoding upcoming choice at low
              contrast. Thus, trial history influence of perceptual choice is
              adaptive to the strength of sensory evidence, which may be
              important for action selection in a dynamic environment.",
  journal  = "Neuroscience",
  month    =  apr,
  year     =  2019,
  keywords = "choice history; contrast; decision making; rodent; secondary
              motor cortex",
  language = "en"
}

@ARTICLE{Lintz2019-sx,
  title    = "Spatial Representations in the Superior Colliculus Are Modulated
              by Competition among Targets",
  author   = "Lintz, Mario J and Essig, Jaclyn and Zylberberg, Joel and Felsen,
              Gidon",
  abstract = "Selecting and moving to spatial targets are critical components
              of goal-directed behavior, yet their neural bases are not well
              understood. The superior colliculus (SC) is thought to contain a
              topographic map of contralateral space in which the activity of
              specific neuronal populations corresponds to particular spatial
              locations. However, these spatial representations are modulated
              by several decision-related variables, suggesting that they
              reflect information beyond simply the location of an upcoming
              movement. Here, we examine the extent to which these
              representations arise from competitive spatial choice. We
              recorded SC activity in male mice performing a behavioral task
              requiring orienting movements to targets for a water reward in
              two contexts. In ``competitive'' trials, either the left or right
              target could be rewarded, depending on which stimulus was
              presented at the central port. In ``noncompetitive'' trials, the
              same target (e.g., left) was rewarded throughout an entire block.
              While both trial types required orienting movements to the same
              spatial targets, only in competitive trials do targets compete
              for selection. We found that in competitive trials, pre-movement
              SC activity predicted movement to contralateral targets, as
              expected. However, in noncompetitive trials, some neurons lost
              their spatial selectivity and in others activity predicted
              movement to ipsilateral targets. Consistent with these findings,
              unilateral optogenetic inactivation of pre-movement SC activity
              ipsiversively biased competitive, but not noncompetitive, trials.
              Incorporating these results into an attractor model of SC
              activity points to distinct pathways for orienting movements
              under competitive and noncompetitive conditions, with the SC
              specifically required for selecting among multiple potential
              targets.",
  journal  = "Neuroscience",
  month    =  apr,
  year     =  2019,
  keywords = "Superior colliculus; decision making; freely-moving mice; target
              selection",
  language = "en"
}

@ARTICLE{Churchland2008-av,
  title     = "Decision-making with multiple alternatives",
  author    = "Churchland, Anne K and Kiani, Roozbeh and Shadlen, Michael N",
  abstract  = "Simple perceptual tasks have laid the groundwork for
               understanding the neurobiology of decision-making. Here, we
               examined this foundation to explain how decision-making
               circuitry adjusts in the face of a more difficult task. We
               measured behavioral and physiological responses of monkeys on a
               two- and four-choice direction-discrimination decision task. For
               both tasks, firing rates in the lateral intraparietal area
               appeared to reflect the accumulation of evidence for or against
               each choice. Evidence accumulation began at a lower firing rate
               for the four-choice task, but reached a common level by the end
               of the decision process. The larger excursion suggests that the
               subjects required more evidence before making a choice.
               Furthermore, on both tasks, we observed a time-dependent rise in
               firing rates that may impose a deadline for deciding. These
               physiological observations constitute an effective strategy for
               handling increased task difficulty. The differences appear to
               explain subjects' accuracy and reaction times.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  11,
  number    =  6,
  pages     = "693--702",
  month     =  jun,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Louie2014-lo,
  title     = "Dynamic divisive normalization predicts time-varying value
               coding in decision-related circuits",
  author    = "Louie, Kenway and LoFaro, Thomas and Webb, Ryan and Glimcher,
               Paul W",
  abstract  = "Normalization is a widespread neural computation, mediating
               divisive gain control in sensory processing and implementing a
               context-dependent value code in decision-related frontal and
               parietal cortices. Although decision-making is a dynamic process
               with complex temporal characteristics, most models of
               normalization are time-independent and little is known about the
               dynamic interaction of normalization and choice. Here, we show
               that a simple differential equation model of normalization
               explains the characteristic phasic-sustained pattern of cortical
               decision activity and predicts specific normalization dynamics:
               value coding during initial transients, time-varying value
               modulation, and delayed onset of contextual information.
               Empirically, we observe these predicted dynamics in
               saccade-related neurons in monkey lateral intraparietal cortex.
               Furthermore, such models naturally incorporate a time-weighted
               average of past activity, implementing an intrinsic
               reference-dependence in value coding. These results suggest that
               a single network mechanism can explain both transient and
               sustained decision activity, emphasizing the importance of a
               dynamic view of normalization in neural coding.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  34,
  number    =  48,
  pages     = "16046--16057",
  month     =  nov,
  year      =  2014,
  keywords  = "computational modeling; decision-making; divisive normalization;
               dynamical system; reward",
  language  = "en"
}

@ARTICLE{Schacter_Daniel_L2007-rc,
  title     = "The cognitive neuroscience of constructive memory: remembering
               the past and imagining the future",
  author    = "{Schacter Daniel L} and {Addis Donna Rose}",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "Royal Society",
  volume    =  362,
  number    =  1481,
  pages     = "773--786",
  month     =  may,
  year      =  2007
}

@ARTICLE{Khamassi2005-rl,
  title     = "{Actor--Critic} Models of Reinforcement Learning in the Basal
               Ganglia: From Natural to Artificial Rats",
  author    = "Khamassi, Mehdi and Lach{\`e}ze, Lo{\"\i}c and Girard,
               Beno{\^\i}t and Berthoz, Alain and Guillot, Agn{\`e}s",
  abstract  = "Since 1995, numerous Actor?Critic architectures for
               reinforcement learning have been proposed as models of
               dopamine-like reinforcement learning mechanisms in the rat?s
               basal ganglia. However, these models were usually tested in
               different tasks, and it is then difficult to compare their
               efficiency for an autonomous animat. We present here the
               comparison of four architectures in an animat as it per forms
               the same reward-seeking task. This will illustrate the
               consequences of different hypotheses about the management of
               different Actor sub-modules and Critic units, and their more or
               less autono mously determined coordination. We show that the
               classical method of coordination of modules by mixture of
               experts, depending on each module?s performance, did not allow
               solving our task. Then we address the question of which
               principle should be applied efficiently to combine these units.
               Improve ments for Critic modeling and accuracy of Actor?Critic
               models for a natural task are finally discussed in the
               perspective of our Psikharpax project?an artificial rat having
               to survive autonomously in unpre dictable environments.",
  journal   = "Adapt. Behav.",
  publisher = "SAGE Publications Ltd STM",
  volume    =  13,
  number    =  2,
  pages     = "131--148",
  month     =  jun,
  year      =  2005
}

@ARTICLE{Joel2002-xo,
  title     = "Actor--critic models of the basal ganglia: new anatomical and
               computational perspectives",
  author    = "Joel, Daphna and Niv, Yael and Ruppin, Eytan",
  abstract  = "A large number of computational models of information processing
               in the basal ganglia have been developed in recent years.
               Prominent in these are actor--critic models of basal ganglia
               functioning, which build on the strong resemblance between
               dopamine neuron activity and the temporal difference prediction
               error signal in the critic, and between dopamine-dependent
               long-term synaptic plasticity in the striatum and learning
               guided by a prediction error signal in the actor. We selectively
               review several actor--critic models of the basal ganglia with an
               emphasis on two important aspects: the way in which models of
               the critic reproduce the temporal dynamics of dopamine firing,
               and the extent to which models of the actor take into account
               known basal ganglia anatomy and physiology. To complement the
               efforts to relate basal ganglia mechanisms to reinforcement
               learning (RL), we introduce an alternative approach to modeling
               a critic network, which uses Evolutionary Computation techniques
               to `evolve' an optimal RL mechanism, and relate the evolved
               mechanism to the basic model of the critic. We conclude our
               discussion of models of the critic by a critical discussion of
               the anatomical plausibility of implementations of a critic in
               basal ganglia circuitry, and conclude that such implementations
               build on assumptions that are inconsistent with the known
               anatomy of the basal ganglia. We return to the actor component
               of the actor--critic model, which is usually modeled at the
               striatal level with very little detail. We describe an
               alternative model of the basal ganglia which takes into account
               several important, and previously neglected, anatomical and
               physiological characteristics of basal ganglia--thalamocortical
               connectivity and suggests that the basal ganglia performs
               reinforcement-biased dimensionality reduction of cortical
               inputs. We further suggest that since such selective encoding
               may bias the representation at the level of the frontal cortex
               towards the selection of rewarded plans and actions, the
               reinforcement-driven dimensionality reduction framework may
               serve as a basis for basal ganglia actor models. We conclude
               with a short discussion of the dual role of the dopamine signal
               in RL and in behavioral switching.",
  journal   = "Neural Netw.",
  publisher = "Elsevier",
  volume    =  15,
  number    =  4,
  pages     = "535--547",
  month     =  jun,
  year      =  2002,
  keywords  = "Basal ganglia; Dopamine; Reinforcement learning; Actor--critic;
               Dimensionality reduction; Evolutionary computation; Behavioral
               switching; Striosomes/patches"
}

@ARTICLE{Lee2014-ji,
  title     = "Neural computations underlying arbitration between model-based
               and model-free learning",
  author    = "Lee, Sang Wan and Shimojo, Shinsuke and O'Doherty, John P",
  abstract  = "There is accumulating neural evidence to support the existence
               of two distinct systems for guiding action selection, a
               deliberative ``model-based'' and a reflexive ``model-free''
               system. However, little is known about how the brain determines
               which of these systems controls behavior at one moment in time.
               We provide evidence for an arbitration mechanism that allocates
               the degree of control over behavior by model-based and
               model-free systems as a function of the reliability of their
               respective predictions. We show that the inferior lateral
               prefrontal and frontopolar cortex encode both reliability
               signals and the output of a comparison between those signals,
               implicating these regions in the arbitration process. Moreover,
               connectivity between these regions and model-free valuation
               areas is negatively modulated by the degree of model-based
               control in the arbitrator, suggesting that arbitration may work
               through modulation of the model-free valuation system when the
               arbitrator deems that the model-based system should drive
               behavior.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  81,
  number    =  3,
  pages     = "687--699",
  month     =  feb,
  year      =  2014,
  language  = "en"
}

@ARTICLE{Papale2016-ml,
  title     = "Interplay between Hippocampal {Sharp-Wave-Ripple} Events and
               Vicarious Trial and Error Behaviors in Decision Making",
  author    = "Papale, Andrew E and Zielinski, Mark C and Frank, Loren M and
               Jadhav, Shantanu P and Redish, A David",
  abstract  = "Current theories posit that memories encoded during experiences
               are subsequently consolidated into longer-term storage.
               Hippocampal sharp-wave-ripple (SWR) events have been linked to
               this consolidation process during sleep, but SWRs also occur
               during awake immobility, where their role remains unclear. We
               report that awake SWR rates at the reward site are inversely
               related to the prevalence of vicarious trial and error (VTE)
               behaviors, thought to be involved in deliberation processes. SWR
               rates were diminished immediately after VTE behaviors and an
               increase in the rate of SWR events at the reward site predicted
               a decrease in subsequent VTE behaviors at the choice point.
               Furthermore, SWR disruptions increased VTE behaviors. These
               results suggest an inverse relationship between SWRs and VTE
               behaviors and suggest that awake SWRs and associated planning
               and memory consolidation mechanisms are engaged specifically in
               the context of higher levels of behavioral certainty.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  92,
  number    =  5,
  pages     = "975--982",
  month     =  dec,
  year      =  2016,
  language  = "en"
}

@ARTICLE{Van_der_Meer2010-ed,
  title     = "Expectancies in decision making, reinforcement learning, and
               ventral striatum",
  author    = "van der Meer, Matthijs A A and Redish, A David",
  abstract  = "Decisions can arise in different ways, such as from a gut
               feeling, doing what worked last time, or planful deliberation.
               Different decision-making systems are dissociable behaviorally,
               map onto distinct brain systems, and have different
               computational demands. For instance, ``model-free'' decision
               strategies use prediction errors to estimate scalar action
               values from previous experience, while ``model-based''
               strategies leverage internal forward models to generate and
               evaluate potentially rich outcome expectancies. Animal learning
               studies indicate that expectancies may arise from different
               sources, including not only forward models but also Pavlovian
               associations, and the flexibility with which such
               representations impact behavior may depend on how they are
               generated. In the light of these considerations, we review the
               results of van der Meer and Redish (2009a), who found that
               ventral striatal neurons that respond to reward delivery can
               also be activated at other points, notably at a decision point
               where hippocampal forward representations were also observed.
               These data suggest the possibility that ventral striatal reward
               representations contribute to model-based expectancies used in
               deliberative decision making.",
  journal   = "Front. Neurosci.",
  publisher = "frontiersin.org",
  volume    =  4,
  pages     = "6",
  month     =  may,
  year      =  2010,
  keywords  = "Pavlovian-instrumental transfer; actor--critic; planning;
               reinforcement learning; reward",
  language  = "en"
}

@ARTICLE{Alexander1990-rz,
  title     = "Functional architecture of basal ganglia circuits: neural
               substrates of parallel processing",
  author    = "Alexander, G E and Crutcher, M D",
  abstract  = "Concepts of basal ganglia organization have changed markedly
               over the past decade, due to significant advances in our
               understanding of the anatomy, physiology and pharmacology of
               these structures. Independent evidence from each of these fields
               has reinforced a growing perception that the functional
               architecture of the basal ganglia is essentially parallel in
               nature, regardless of the perspective from which these
               structures are viewed. This represents a significant departure
               from earlier concepts of basal ganglia organization, which
               generally emphasized the serial aspects of their connectivity.
               Current evidence suggests that the basal ganglia are organized
               into several structurally and functionally distinct 'circuits'
               that link cortex, basal ganglia and thalamus, with each circuit
               focused on a different portion of the frontal lobe. In this
               review, Garrett Alexander and Michael Crutcher, using the basal
               ganglia 'motor' circuit as the principal example, discuss recent
               evidence indicating that a parallel functional architecture may
               also be characteristic of the organization within each
               individual circuit.",
  journal   = "Trends Neurosci.",
  publisher = "Elsevier",
  volume    =  13,
  number    =  7,
  pages     = "266--271",
  month     =  jul,
  year      =  1990,
  language  = "en"
}

@ARTICLE{Dickinson1994-td,
  title     = "Motivational control of goal-directed action",
  author    = "Dickinson, Anthony and Balleine, Bernard",
  abstract  = "The control of goal-directed, instrumental actions by primary
               motivational states, such as hunger and thirst, is mediated by
               two processes. The first is engaged by the Pavlovian association
               between contextual or discriminative stimuli and the outcome or
               reinforcer presented during instrumental training. Such stimuli
               exert a motivational influence on instrumental performance that
               depends upon the relevance of the associated outcome to the
               current motivational state of the agent. Moreover, the
               motivational effects of these stimuli operate in the absence of
               prior experience with the outcome under the relevant
               motivational state. The second, instrumental, process is
               mediated by knowledge of the contingency between the action and
               its outcome and controls the value assigned to this outcome. In
               contrast to the Pavlovian process, motivational states do not
               influence the instrumental process directly; rather, the agent
               has to learn about the value of an outcome in a given
               motivational state by exposure to it while in that state. This
               incentive learning is similar in certain respects to the
               acquisition of ``cathexes'' envisaged by Tolman (1949a, 1949b).",
  journal   = "Anim. Learn. Behav.",
  publisher = "Springer",
  volume    =  22,
  number    =  1,
  pages     = "1--18",
  month     =  mar,
  year      =  1994
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Dickinson1985-pt,
  title     = "Actions and habits: the development of behavioural autonomy",
  author    = "Dickinson, Anthony",
  abstract  = "The study of animal behaviour has been dominated by two general
               models. According to the mechanistic stimulus-response model, a
               particular behaviour is either an innate or an acquired habit
               which is simply triggered by the appropriate stimulus. By
               contrast, the teleological model argues that, at least, some
               activities are purposive actions controlled by the current value
               of their goals through knowledge about the instrumental
               relations between the actions and their consequences. The type
               of control over any particular behaviour can …",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "The Royal Society London",
  volume    =  308,
  number    =  1135,
  pages     = "67--78",
  year      =  1985
}

@ARTICLE{Dayan1993-rr,
  title     = "Improving Generalization for Temporal Difference Learning: The
               Successor Representation",
  author    = "Dayan, Peter",
  abstract  = "Estimation of returns over time, the focus of temporal
               difference (TD) algorithms, imposes particular constraints on
               good function approximators or representations. Appropriate
               generalization between states is determined by how similar their
               successors are, and representations should follow suit. This
               paper shows how TD machinery can be used to learn such
               representations, and illustrates, using a navigation task, the
               appropriately distributed nature of the result.",
  journal   = "Neural Comput.",
  publisher = "MIT Press",
  volume    =  5,
  number    =  4,
  pages     = "613--624",
  month     =  jul,
  year      =  1993
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Ramachandran2007-tz,
  title     = "Bayesian Inverse Reinforcement Learning",
  author    = "Ramachandran, D and Amir, E",
  abstract  = "Abstract Inverse Reinforcement Learning (IRL) is the problem of
               learning the reward function underlying a Markov Decision
               Process given the dynamics of the system and the behaviour of an
               expert. IRL is motivated by situations where knowledge of the
               rewards is a goal by …",
  journal   = "IJCAI",
  publisher = "aaai.org",
  year      =  2007
}

@ARTICLE{noauthor_undated-wn,
  title = "icml00-irl.pdf"
}

@INCOLLECTION{Choi2011-ua,
  title     = "{MAP} Inference for Bayesian Inverse Reinforcement Learning",
  booktitle = "Advances in Neural Information Processing Systems 24",
  author    = "Choi, Jaedeug and Kim, Kee-Eung",
  editor    = "Shawe-Taylor, J and Zemel, R S and Bartlett, P L and Pereira, F
               and Weinberger, K Q",
  publisher = "Curran Associates, Inc.",
  pages     = "1989--1997",
  year      =  2011
}

@ARTICLE{Burton2015-am,
  title    = "From ventral-medial to dorsal-lateral striatum: neural correlates
              of reward-guided decision-making",
  author   = "Burton, Amanda C and Nakamura, Kae and Roesch, Matthew R",
  abstract = "The striatum is critical for reward-guided and habitual behavior.
              Anatomical and interference studies suggest a functional
              heterogeneity within striatum. Medial regions, such as nucleus
              accumbens core and dorsal medial striatum play roles in
              goal-directed behavior, while dorsal lateral striatum is critical
              for control of habitual action. Subdivisions of striatum are
              topographically connected with different cortical and subcortical
              structures forming channels that carry information related to
              limbic, associative, and sensorimotor functions. Here, we
              describe data showing that as one progresses from ventral-medial
              to dorsal-lateral striatum, there is a shift from more prominent
              value encoding to activity more closely related to associative
              and motor aspects of decision-making. In addition, we will
              describe data suggesting that striatal circuits work in parallel
              to control behavior and that regions within striatum can
              compensate for each other when functions are disrupted.",
  journal  = "Neurobiol. Learn. Mem.",
  volume   =  117,
  pages    = "51--59",
  month    =  jan,
  year     =  2015,
  keywords = "Goal; Habit; Monkey; Nucleus accumbens; Rat; Single unit;
              Striatum; Value",
  language = "en"
}

@ARTICLE{Guazzelli1998-ub,
  title     = "Affordances. Motivations, and the World Graph Theory",
  author    = "Guazzelli, Alex and Bota, Mihail and Corbacho, Fernando J and
               Arbib, Michael A",
  abstract  = "O'Keefe and Nadel (1978) distinguish two paradigms for
               navigation, the ``locale system'' for map-based navigation and
               the ``taxon (behavioral orientation) system'' for route
               navigation. This article models the taxon system, the map-based
               system, and their interaction, and argues that the map-based
               system involves the interaction of hippocampus and other
               systems.We relate taxes to the notion of an affordance. Just as
               a rat may have basic taxes for approaching food or avoiding a
               bright light, so does it have a wider repertoire of affordances
               for possible actions associated with immediate sensing of its
               environment. We propose that affordances are extracted by the
               rat posterior parietal cortex, which guides action selection by
               the premotor cortex and is influenced also by hypothalamic drive
               information.The taxon-affordances model (TAM) for taxon-based
               determination of movement direction is based on models of frog
               detour behavior, with expectations of future reward implemented
               using reinforcement learning. The specification of the direction
               of movement is refined by current affordances and motivational
               information to yield an appropriate course of action.The world
               graph (WG) theory expands the idea of a map by developing the
               hypothesis that cognitive and motivational states interact. This
               article describes an implementation of this theory, the WG
               model. The integrated TAM-WG model then allows us to explain
               data on the behavior of rats with and without fornix lesions,
               which disconnect the hippocampus from other neural systems.",
  journal   = "Adapt. Behav.",
  publisher = "SAGE Publications Ltd STM",
  volume    =  6,
  number    = "3-4",
  pages     = "435--471",
  month     =  jan,
  year      =  1998
}

@ARTICLE{Chersi2013-el,
  title     = "Mental imagery in the navigation domain: a computational model
               of sensory-motor simulation mechanisms",
  author    = "Chersi, Fabian and Donnarumma, Francesco and Pezzulo, Giovanni",
  abstract  = "Recent experimental evidence indicates that animals can use
               mental simulation to make decisions about the actions to take
               during goal-directed navigation. The principal brain areas found
               to be active during this process are the hippocampus, the
               ventral striatum and the sensory-motor cortex. In this paper, we
               present a computational model that includes biological aspects
               of this circuit and explains mechanistically how it may be used
               to imagine and evaluate future events. Its most salient
               characteristic is that choices about actions are made by
               simulating movements and their sensory effects using the same
               brain areas that are active during overt execution. More
               precisely, the simulation of an action (e.g., walking) creates a
               new sensory pattern that is evaluated in the same way as real
               inputs. The model is validated in a navigation task in which a
               simulated rat is placed in a complex maze. We show that
               hippocampal and striatal cells are activated to simulate paths,
               to retrieve their estimated value and to make decisions. We link
               these results with a general framework that sees the brain as a
               predictive device that can ?detach? itself from the here-and-now
               of current perception using mechanisms such as episodic
               memories, motor and visual imagery.",
  journal   = "Adapt. Behav.",
  publisher = "SAGE Publications Ltd STM",
  volume    =  21,
  number    =  4,
  pages     = "251--262",
  month     =  aug,
  year      =  2013
}

@ARTICLE{Lynn2018-pf,
  title         = "The physics of brain network structure, function, and
                   control",
  author        = "Lynn, Christopher W and Bassett, Danielle S",
  abstract      = "The brain is a complex organ characterized by heterogeneous
                   patterns of structural connections supporting unparalleled
                   feats of cognition and a wide range of behaviors. New
                   noninvasive imaging techniques now allow these patterns to
                   be carefully and comprehensively mapped in individual humans
                   and animals. Yet, it remains a fundamental challenge to
                   understand how the brain's structural wiring supports
                   cognitive processes, with major implications for the
                   personalized treatment of mental health disorders. Here, we
                   review recent efforts to meet this challenge that draw on
                   intuitions, models, and theories from physics, spanning the
                   domains of statistical mechanics, information theory, and
                   dynamical systems and control. We begin by considering the
                   organizing principles of brain network architecture
                   instantiated in structural wiring under constraints of
                   symmetry, spatial embedding, and energy minimization. We
                   next consider models of brain network function that
                   stipulate how neural activity propagates along these
                   structural connections, producing the long-range
                   interactions and collective dynamics that support a rich
                   repertoire of system functions. Finally, we consider
                   perturbative experiments and models for brain network
                   control, which leverage the physics of signal transmission
                   along structural wires to infer intrinsic control processes
                   that support goal-directed behavior and to inform
                   stimulation-based therapies for neurological disease and
                   psychiatric disorders. Throughout, we highlight several open
                   questions in the physics of brain network structure,
                   function, and control that will require creative efforts
                   from physicists willing to brave the complexities of living
                   matter.",
  month         =  sep,
  year          =  2018,
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.NC",
  eprint        = "1809.06441"
}

@UNPUBLISHED{Chalk2019-yt,
  title    = "Inferring the function performed by a recurrent neural network",
  author   = "Chalk, Matthew and Tkacik, Gasper and Marre, Olivier",
  abstract = "A central goal in systems neuroscience is to understand the
              functions performed by neural circuits. Previous top-down models
              addressed this question by comparing the behaviour of an ideal
              model circuit, optimised to perform a given function, with neural
              recordings. However, this requires guessing in advance what
              function is being performed, which may not be possible for many
              neural systems. Here, we propose an alternative approach that
              uses recorded neural responses to directly infer the function
              performed by a neural network. We assume that the goal of the
              network can be expressed via a reward function, which describes
              how desirable each state of the network is for carrying out a
              given objective. This allows us to frame the problem of
              optimising each neuron9s responses by viewing neurons as agents
              in a reinforcement learning (RL) paradigm; likewise the problem
              of inferring the reward function from the observed dynamics can
              be treated using inverse RL. Our framework encompasses previous
              influential theories of neural coding, such as efficient coding
              and attractor network models, as special cases, given specific
              choices of reward function. Finally, we can use the reward
              function inferred from recorded neural responses to make testable
              predictions about how the network dynamics will adapt depending
              on contextual changes, such as cell death and/or varying input
              statistics, so as to carry out the same underlying function with
              different constraints.",
  journal  = "bioRxiv",
  pages    = "598086",
  month    =  apr,
  year     =  2019,
  language = "en"
}

@ARTICLE{Janabi-Sharifi2000-tj,
  title    = "Discrete-time adaptive windowing for velocity estimation",
  author   = "Janabi-Sharifi, F and Hayward, V and -. J. Chen, C",
  abstract = "We present methods for velocity estimation from discrete and
              quantized position samples using adaptive windowing. Previous
              methods necessitate trade-offs between noise reduction, control
              delay, estimate accuracy, reliability, computational load,
              transient preservation, and difficulties with tuning. In
              contrast, a first-order adaptive windowing method is shown to be
              optimal in the sense that it minimizes the velocity error
              variance while maximizes the accuracy of the estimates, requiring
              no tradeoff. Variants of this method are also discussed. The
              effectiveness of the proposed technique is verified in simulation
              and by experiments on the control of a haptic device.",
  journal  = "IEEE Trans. Control Syst. Technol.",
  volume   =  8,
  number   =  6,
  pages    = "1003--1009",
  month    =  nov,
  year     =  2000,
  keywords = "haptic interfaces;velocity control;adaptive estimation;discrete
              time systems;filtering theory;optimisation;adaptive
              windowing;velocity estimation;discrete-time systems;control
              delay;haptic interface;optimisation;Delay estimation;Finite
              impulse response filter;Noise reduction;Haptic
              interfaces;Velocity control;Filtering;Finite difference
              methods;Intelligent robots;Machine intelligence;Size control"
}

@ARTICLE{Wang2015-ic,
  title     = "Covert rapid action-memory simulation ({CRAMS)}: A hypothesis of
               hippocampal--prefrontal interactions for adaptive behavior",
  author    = "Wang, Jane X and Cohen, Neal J and Voss, Joel L",
  abstract  = "Effective choices generally require memory, yet little is known
               regarding the cognitive or neural mechanisms that allow memory
               to influence choices. We outline a new framework proposing that
               covert memory processing of hippocampus interacts with
               action-generation processing of prefrontal cortex in order to
               arrive at optimal, memory-guided choices. Covert, rapid
               action-memory simulation (CRAMS) is proposed here as a framework
               for understanding cognitive and/or behavioral choices, whereby
               prefrontal--hippocampal interactions quickly provide multiple
               simulations of potential outcomes used to evaluate the set of
               possible choices. We hypothesize that this CRAMS process is
               automatic, obligatory, and covert, meaning that many cycles of
               action-memory simulation occur in response to choice conflict
               without an individual's necessary intention and generally
               without awareness of the simulations, leading to adaptive
               behavior with little perceived effort. CRAMS is thus distinct
               from influential proposals that adaptive memory-based behavior
               in humans requires consciously experienced memory-based
               construction of possible future scenarios and deliberate
               decisions among possible future constructions. CRAMS provides an
               account of why hippocampus has been shown to make critical
               contributions to the short-term control of behavior, and it
               motivates several new experimental approaches and hypotheses
               that could be used to better understand the ubiquitous role of
               prefrontal--hippocampal interactions in situations that require
               adaptively using memory to guide choices. Importantly, this
               framework provides a perspective that allows for testing
               decision-making mechanisms in a manner that translates well
               across human and nonhuman animal model systems.",
  journal   = "Neurobiol. Learn. Mem.",
  publisher = "Elsevier",
  volume    =  117,
  pages     = "22--33",
  month     =  jan,
  year      =  2015,
  keywords  = "Learning; Memory; Decision-making; Hippocampus; Prefrontal
               cortex; Simulation; Imagination; Adaptive function"
}

@ARTICLE{Preston2013-qk,
  title     = "Interplay of hippocampus and prefrontal cortex in memory",
  author    = "Preston, Alison R and Eichenbaum, Howard",
  abstract  = "Recent studies on the hippocampus and the prefrontal cortex have
               considerably advanced our understanding of the distinct roles of
               these brain areas in the encoding and retrieval of memories, and
               of how they interact in the prolonged process by which new
               memories are consolidated into our permanent storehouse of
               knowledge. These studies have led to a new model of how the
               hippocampus forms and replays memories and how the prefrontal
               cortex engages representations of the meaningful contexts in
               which related memories occur, as well as how these areas
               interact during memory retrieval. Furthermore, they have
               provided new insights into how interactions between the
               hippocampus and prefrontal cortex support the assimilation of
               new memories into pre-existing networks of knowledge, called
               schemas, and how schemas are modified in this process as the
               foundation of memory consolidation.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  23,
  number    =  17,
  pages     = "R764--73",
  month     =  sep,
  year      =  2013,
  language  = "en"
}


@ARTICLE{Schmidt2019-gu,
  title    = "Disrupting the medial Prefrontal Cortex Alters Hippocampal
              Sequences during Deliberative {Decision-Making}",
  author   = "Schmidt, Brandy and Duin, Anneke A and Redish, A David",
  abstract = "Current theories of deliberative decision-making suggest that
              deliberative decisions arise from imagined simulations that
              require interactions between the prefrontal cortex and
              hippocampus. In rodent navigation experiments, hippocampal theta
              sequences advance from the location of the rat ahead to the
              subsequent goal. In order to examine the role of the medial
              prefrontal cortex (mPFC) on the hippocampus, we disrupted the
              mPFC with DREADDs (Designer Receptors Exclusively Activated by
              Designer Drugs). Using the Restaurant Row foraging task, we found
              that mPFC disruption resulted in decreased vicarious trial and
              error (VTE) behavior, reduced the number of theta sequences, and
              impaired theta sequences in hippocampus. mPFC disruption led to
              larger changes in the initiation of the hippocampal theta
              sequences that represent the current location of the rat rather
              than to the later portions that represent the future outcomes.
              These data suggest that the mPFC likely provides an important
              component to the initiation of deliberative sequences, and
              provides support for an episodic-future thinking, working memory
              interpretation of deliberation.",
  journal  = "J. Neurophysiol.",
  month    =  mar,
  year     =  2019,
  keywords = "hippocampus; place cell; prelimbic cortex; theta; vicarious trial
              and error",
  language = "en"
}


@ARTICLE{Knill2004-uu,
  title    = "The Bayesian brain: the role of uncertainty in neural coding and
              computation",
  author   = "Knill, David C and Pouget, Alexandre",
  abstract = "To use sensory information efficiently to make judgments and
              guide action in the world, the brain must represent and use
              information about uncertainty in its computations for perception
              and action. Bayesian methods have proven successful in building
              computational theories for perception and sensorimotor control,
              and psychophysics is providing a growing body of evidence that
              human perceptual computations are ``Bayes' optimal''. This leads
              to the ``Bayesian coding hypothesis'': that the brain represents
              sensory information probabilistically, in the form of probability
              distributions. Several computational schemes have recently been
              proposed for how this might be achieved in populations of
              neurons. Neurophysiological data on the hypothesis, however, is
              almost non-existent. A major challenge for neuroscientists is to
              test these ideas experimentally, and so determine whether and how
              neurons code information about sensory uncertainty.",
  journal  = "Trends Neurosci.",
  volume   =  27,
  number   =  12,
  pages    = "712--719",
  month    =  dec,
  year     =  2004,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Friston2012-rd,
  title     = "The history of the future of the Bayesian brain",
  author    = "Friston, Karl",
  abstract  = "The slight perversion of the original title of this piece (The
               Future of the Bayesian Brain ) reflects my attempt to write
               prospectively about 'Science and Stories' over the past 20
               years. I will meet this challenge by dealing with the future and
               then turning to its history. The future of …",
  journal   = "Neuroimage",
  publisher = "Elsevier",
  volume    =  62,
  number    =  2,
  pages     = "1230--1233",
  year      =  2012
}

@ARTICLE{Havenith2019-st,
  title    = "The {Virtual-Environment-Foraging} Task enables rapid training
              and single-trial metrics of rule acquisition and reversal in
              head-fixed mice",
  author   = "Havenith, Martha N and Zijderveld, Peter M and van Heukelum,
              Sabrina and Abghari, Shaghayegh and Tiesinga, Paul and Glennon,
              Jeffrey C",
  abstract = "Behavioural flexibility is an essential survival skill, yet our
              understanding of its neuronal substrates is still limited. While
              mouse research offers unique tools to dissect the neuronal
              circuits involved, the measurement of flexible behaviour in mice
              often suffers from long training times, poor experimental
              control, and temporally imprecise binary (hit/miss) performance
              readouts. Here we present a virtual-environment task for mice
              that tackles these limitations. It offers fast training of
              vision-based rule reversals (~100 trials per reversal) with full
              stimulus control and continuous behavioural readouts. By
              generating multiple non-binary performance metrics per trial, it
              provides single-trial estimates not only of response accuracy and
              speed, but also of underlying processes like choice certainty and
              alertness (discussed in detail in a companion paper). Based on
              these metrics, we show that mice can predict new task rules long
              before they are able to execute them, and that this delay varies
              across animals. We also provide and validate single-trial
              estimates of whether an error was committed with or without
              awareness of the task rule. By tracking in unprecedented detail
              the cognitive dynamics underlying flexible behaviour, this task
              enables new investigations into the neuronal interactions that
              shape behavioural flexibility moment by moment.",
  journal  = "Sci. Rep.",
  volume   =  9,
  number   =  1,
  pages    = "4790",
  month    =  mar,
  year     =  2019,
  language = "en"
}

@UNPUBLISHED{Russek2017-vw,
  title    = "Predictive representations can link model-based reinforcement
              learning to model-free mechanisms",
  author   = "Russek, Evan M and Momennejad, Ida and Botvinick, Matthew M and
              Gershman, Samuel J and Daw, Nathaniel D",
  abstract = "Humans and animals are capable of evaluating actions by
              considering their long-run future rewards through a process
              described using model-based reinforcement learning (RL)
              algorithms. The mechanisms by which neural circuits perform the
              computations prescribed by model-based RL remain largely unknown;
              however, multiple lines of evidence suggest that neural circuits
              supporting model-based behavior are structurally homologous to
              and overlapping with those thought to carry out model-free
              temporal difference (TD) learning. Here, we lay out a family of
              approaches by which model-based computation may be built upon a
              core of TD learning. The foundation of this framework is the
              successor representation, a predictive state representation that,
              when combined with TD learning of value predictions, can produce
              a subset of the behaviors associated with model-based learning at
              a fraction of the computational cost. Using simulations, we
              delineate the precise behavioral capabilities enabled by
              evaluating actions using this approach, and compare them to those
              demonstrated by biological organisms. We then introduce two new
              algorithms that build upon the successor representation while
              progressively mitigating its limitations. Because this framework
              can account for the full range of observed putatively model-based
              behaviors while still utilizing a core TD framework, we suggest
              that it represents a neurally plausible family of mechanisms for
              model-based evaluation.",
  journal  = "bioRxiv",
  pages    = "083857",
  month    =  aug,
  year     =  2017,
  language = "en"
}

@ARTICLE{Sul2010-js,
  title     = "Distinct roles of rodent orbitofrontal and medial prefrontal
               cortex in decision making",
  author    = "Sul, Jung Hoon and Kim, Hoseok and Huh, Namjung and Lee, Daeyeol
               and Jung, Min Whan",
  abstract  = "We investigated how different subregions of rodent prefrontal
               cortex contribute to value-based decision making, by comparing
               neural signals related to animal's choice, its outcome, and
               action value in orbitofrontal cortex (OFC) and medial prefrontal
               cortex (mPFC) of rats performing a dynamic two-armed bandit
               task. Neural signals for upcoming action selection arose in the
               mPFC, including the anterior cingulate cortex, only immediately
               before the behavioral manifestation of animal's choice,
               suggesting that rodent prefrontal cortex is not involved in
               advanced action planning. Both OFC and mPFC conveyed signals
               related to the animal's past choices and their outcomes over
               multiple trials, but neural signals for chosen value and reward
               prediction error were more prevalent in the OFC. Our results
               suggest that rodent OFC and mPFC serve distinct roles in
               value-based decision making and that the OFC plays a prominent
               role in updating the values of outcomes expected from chosen
               actions.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  66,
  number    =  3,
  pages     = "449--460",
  month     =  may,
  year      =  2010,
  language  = "en"
}

@ARTICLE{Ito2011-yi,
  title     = "Multiple representations and algorithms for reinforcement
               learning in the cortico-basal ganglia circuit",
  author    = "Ito, Makoto and Doya, Kenji",
  abstract  = "Accumulating evidence shows that the neural network of the
               cerebral cortex and the basal ganglia is critically involved in
               reinforcement learning. Recent studies found functional
               heterogeneity within the cortico-basal ganglia circuit,
               especially in its ventromedial to dorsolateral axis. Here we
               review computational issues in reinforcement learning and
               propose a working hypothesis on how multiple reinforcement
               learning algorithms are implemented in the cortico-basal ganglia
               circuit using different representations of states, values, and
               actions.",
  journal   = "Curr. Opin. Neurobiol.",
  publisher = "Elsevier",
  volume    =  21,
  number    =  3,
  pages     = "368--373",
  month     =  jun,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Solway2012-bf,
  title     = "Goal-directed decision making as probabilistic inference: a
               computational framework and potential neural correlates",
  author    = "Solway, Alec and Botvinick, Matthew M",
  abstract  = "Recent work has given rise to the view that reward-based
               decision making is governed by two key controllers: a habit
               system, which stores stimulus-response associations shaped by
               past reward, and a goal-oriented system that selects actions
               based on their anticipated outcomes. The current literature
               provides a rich body of computational theory addressing habit
               formation, centering on temporal-difference learning mechanisms.
               Less progress has been made toward formalizing the processes
               involved in goal-directed decision making. We draw on recent
               work in cognitive neuroscience, animal conditioning, cognitive
               and developmental psychology, and machine learning to outline a
               new theory of goal-directed decision making. Our basic proposal
               is that the brain, within an identifiable network of cortical
               and subcortical structures, implements a probabilistic
               generative model of reward, and that goal-directed decision
               making is effected through Bayesian inversion of this model. We
               present a set of simulations implementing the account, which
               address benchmark behavioral and neuroscientific findings, and
               give rise to a set of testable predictions. We also discuss the
               relationship between the proposed framework and other models of
               decision making, including recent models of perceptual choice,
               to which our theory bears a direct connection.",
  journal   = "Psychol. Rev.",
  publisher = "psycnet.apa.org",
  volume    =  119,
  number    =  1,
  pages     = "120--154",
  month     =  jan,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Huys2012-my,
  title     = "Bonsai trees in your head: how the pavlovian system sculpts
               goal-directed choices by pruning decision trees",
  author    = "Huys, Quentin J M and Eshel, Neir and O'Nions, Elizabeth and
               Sheridan, Luke and Dayan, Peter and Roiser, Jonathan P",
  abstract  = "When planning a series of actions, it is usually infeasible to
               consider all potential future sequences; instead, one must prune
               the decision tree. Provably optimal pruning is, however, still
               computationally ruinous and the specific approximations humans
               employ remain unknown. We designed a new sequential
               reinforcement-based task and showed that human subjects adopted
               a simple pruning strategy: during mental evaluation of a
               sequence of choices, they curtailed any further evaluation of a
               sequence as soon as they encountered a large loss. This pruning
               strategy was Pavlovian: it was reflexively evoked by large
               losses and persisted even when overwhelmingly counterproductive.
               It was also evident above and beyond loss aversion. We found
               that the tendency towards Pavlovian pruning was selectively
               predicted by the degree to which subjects exhibited sub-clinical
               mood disturbance, in accordance with theories that ascribe
               Pavlovian behavioural inhibition, via serotonin, a role in mood
               disorders. We conclude that Pavlovian behavioural inhibition
               shapes highly flexible, goal-directed choices in a manner that
               may be important for theories of decision-making in mood
               disorders.",
  journal   = "PLoS Comput. Biol.",
  publisher = "journals.plos.org",
  volume    =  8,
  number    =  3,
  pages     = "e1002410",
  month     =  mar,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Collins2012-sn,
  title     = "How much of reinforcement learning is working memory, not
               reinforcement learning? A behavioral, computational, and
               neurogenetic analysis",
  author    = "Collins, Anne G E and Frank, Michael J",
  abstract  = "Instrumental learning involves corticostriatal circuitry and the
               dopaminergic system. This system is typically modeled in the
               reinforcement learning (RL) framework by incrementally
               accumulating reward values of states and actions. However, human
               learning also implicates prefrontal cortical mechanisms involved
               in higher level cognitive functions. The interaction of these
               systems remains poorly understood, and models of human behavior
               often ignore working memory (WM) and therefore incorrectly
               assign behavioral variance to the RL system. Here we designed a
               task that highlights the profound entanglement of these two
               processes, even in simple learning problems. By systematically
               varying the size of the learning problem and delay between
               stimulus repetitions, we separately extracted WM-specific
               effects of load and delay on learning. We propose a new
               computational model that accounts for the dynamic integration of
               RL and WM processes observed in subjects' behavior.
               Incorporating capacity-limited WM into the model allowed us to
               capture behavioral variance that could not be captured in a pure
               RL framework even if we (implausibly) allowed separate RL
               systems for each set size. The WM component also allowed for a
               more reasonable estimation of a single RL process. Finally, we
               report effects of two genetic polymorphisms having relative
               specificity for prefrontal and basal ganglia functions. Whereas
               the COMT gene coding for catechol-O-methyl transferase
               selectively influenced model estimates of WM capacity, the GPR6
               gene coding for G-protein-coupled receptor 6 influenced the RL
               learning rate. Thus, this study allowed us to specify distinct
               influences of the high-level and low-level cognitive functions
               on instrumental learning, beyond the possibilities offered by
               simple RL models.",
  journal   = "Eur. J. Neurosci.",
  publisher = "Wiley Online Library",
  volume    =  35,
  number    =  7,
  pages     = "1024--1035",
  month     =  apr,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Ruediger2012-lx,
  title     = "Goal-oriented searching mediated by ventral hippocampus early in
               trial-and-error learning",
  author    = "Ruediger, Sarah and Spirig, Dominique and Donato, Flavio and
               Caroni, Pico",
  abstract  = "Most behavioral learning in biology is trial and error, but how
               these learning processes are influenced by individual brain
               systems is poorly understood. Here we show that
               ventral-to-dorsal hippocampal subdivisions have specific and
               sequential functions in trial-and-error maze navigation, with
               ventral hippocampus (vH) mediating early task-specific
               goal-oriented searching. Although performance and strategy
               deployment progressed continuously at the population level,
               individual mice showed discrete learning phases, each
               characterized by particular search habits. Transitions in
               learning phases reflected feedforward inhibitory connectivity
               (FFI) growth occurring sequentially in ventral, then
               intermediate, then dorsal hippocampal subdivisions. FFI growth
               at vH occurred abruptly upon behavioral learning of goal-task
               relationships. vH lesions or the absence of vH FFI growth
               delayed early learning and disrupted performance consistency.
               Intermediate hippocampus lesions impaired intermediate place
               learning, whereas dorsal hippocampus lesions specifically
               disrupted late spatial learning. Trial-and-error navigational
               learning processes in naive mice thus involve a stereotype
               sequence of increasingly precise subtasks learned through
               distinct hippocampal subdivisions. Because of its unique
               connectivity, vH may relate specific goals to internal states in
               learning under healthy and pathological conditions.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  15,
  number    =  11,
  pages     = "1563--1571",
  month     =  nov,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Glascher2010-ne,
  title     = "States versus rewards: dissociable neural prediction error
               signals underlying model-based and model-free reinforcement
               learning",
  author    = "Gl{\"a}scher, Jan and Daw, Nathaniel and Dayan, Peter and
               O'Doherty, John P",
  abstract  = "Reinforcement learning (RL) uses sequential experience with
               situations (``states'') and outcomes to assess actions. Whereas
               model-free RL uses this experience directly, in the form of a
               reward prediction error (RPE), model-based RL uses it
               indirectly, building a model of the state transition and outcome
               structure of the environment, and evaluating actions by
               searching this model. A state prediction error (SPE) plays a
               central role, reporting discrepancies between the current model
               and the observed state transitions. Using functional magnetic
               resonance imaging in humans solving a probabilistic Markov
               decision task, we found the neural signature of an SPE in the
               intraparietal sulcus and lateral prefrontal cortex, in addition
               to the previously well-characterized RPE in the ventral
               striatum. This finding supports the existence of two unique
               forms of learning signal in humans, which may form the basis of
               distinct computational strategies for guiding behavior.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  66,
  number    =  4,
  pages     = "585--595",
  month     =  may,
  year      =  2010,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Tolman1930-yp,
  title     = "Introduction and removal of reward, and maze performance in rats",
  author    = "Tolman, E C and Honzik, C H",
  abstract  = "Two groups of rats, one which ran the maze with reward, and one
               which ran the maze without reward, were tested to determine the
               influence upon the learning curve of a sudden removal, or a
               sudden introduction, of a food reward. The maze was a 14-unit
               T-maze. Reliability coefficients ranged from. 876 to. 965. When
               the food reward was removed from the maze the error scores and
               time scores of the rewarded rats showed a large increase. When
               reward was introduced into the maze the non-rewarded rats showed
               a large decrease …",
  journal   = "Univ. Calif. Publ. Zool.",
  publisher = "psycnet.apa.org",
  year      =  1930
}

@ARTICLE{Doya2002-bl,
  title     = "Multiple model-based reinforcement learning",
  author    = "Doya, Kenji and Samejima, Kazuyuki and Katagiri, Ken-Ichi and
               Kawato, Mitsuo",
  abstract  = "We propose a modular reinforcement learning architecture for
               nonlinear, nonstationary control tasks, which we call multiple
               model-based reinforcement learning (MMRL). The basic idea is to
               decompose a complex task into multiple domains in space and time
               based on the predictability of the environmental dynamics. The
               system is composed of multiple modules, each of which consists
               of a state prediction model and a reinforcement learning
               controller. The ``responsibility signal,'' which is given by the
               softmax function of the prediction errors, is used to weight the
               outputs of multiple modules, as well as to gate the learning of
               the prediction models and the reinforcement learning
               controllers. We formulate MMRL for both discrete-time,
               finite-state case and continuous-time, continuous-state case.
               The performance of MMRL was demonstrated for discrete case in a
               nonstationary hunting task in a grid world and for continuous
               case in a nonlinear, nonstationary control task of swinging up a
               pendulum with variable physical parameters.",
  journal   = "Neural Comput.",
  publisher = "MIT Press",
  volume    =  14,
  number    =  6,
  pages     = "1347--1369",
  month     =  jun,
  year      =  2002,
  language  = "en"
}

@ARTICLE{Dayan2009-zu,
  title     = "Goal-directed control and its antipodes",
  author    = "Dayan, Peter",
  abstract  = "In instrumental conditioning, there is a rather precise
               definition of goal-directed control, and therefore an acute
               boundary between it and the somewhat more amorphous category
               comprising its opposites. Here, we review this division in terms
               of the various distinctions that accompany it in the fields of
               reinforcement learning and cognitive architectures, considering
               issues such as declarative and procedural control, the effect of
               prior distributions over environments, the neural substrates
               involved, and the differing views about the relative rationality
               of the various forms of control. Our overall aim is to reconnect
               some presently far-flung relations.",
  journal   = "Neural Netw.",
  publisher = "Elsevier",
  volume    =  22,
  number    =  3,
  pages     = "213--219",
  month     =  apr,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Balleine1998-ur,
  title     = "Goal-directed instrumental action: contingency and incentive
               learning and their cortical substrates",
  author    = "Balleine, B W and Dickinson, A",
  abstract  = "Instrumental behaviour is controlled by two systems: a
               stimulus-response habit mechanism and a goal-directed process
               that involves two forms of learning. The first is learning about
               the instrumental contingency between the response and reward,
               whereas the second consists of the acquisition of incentive
               value by the reward. Evidence for contingency learning comes
               from studies of reward devaluation and from demonstrations that
               instrumental performance is sensitive not only the probability
               of contiguous reward but also to the probability of unpaired
               rewards. The process of incentive learning is evident in the
               acquisition of control over performance by primary motivational
               states. Preliminary lesion studies of the rat suggest that the
               prelimbic area of prefrontal cortex plays a role in the
               contingency learning, whereas the incentive learning for food
               rewards involves the insular cortex.",
  journal   = "Neuropharmacology",
  publisher = "Elsevier",
  volume    =  37,
  number    = "4-5",
  pages     = "407--419",
  month     =  apr,
  year      =  1998,
  language  = "en"
}

@ARTICLE{Doll2009-ki,
  title     = "Instructional control of reinforcement learning: a behavioral
               and neurocomputational investigation",
  author    = "Doll, Bradley B and Jacobs, W Jake and Sanfey, Alan G and Frank,
               Michael J",
  abstract  = "Humans learn how to behave directly through environmental
               experience and indirectly through rules and instructions.
               Behavior analytic research has shown that instructions can
               control behavior, even when such behavior leads to sub-optimal
               outcomes (Hayes, S. (Ed.). 1989. Rule-governed behavior:
               cognition, contingencies, and instructional control. Plenum
               Press.). Here we examine the control of behavior through
               instructions in a reinforcement learning task known to depend on
               striatal dopaminergic function. Participants selected between
               probabilistically reinforced stimuli, and were (incorrectly)
               told that a specific stimulus had the highest (or lowest)
               reinforcement probability. Despite experience to the contrary,
               instructions drove choice behavior. We present neural network
               simulations that capture the interactions between
               instruction-driven and reinforcement-driven behavior via two
               potential neural circuits: one in which the striatum is
               inaccurately trained by instruction representations coming from
               prefrontal cortex/hippocampus (PFC/HC), and another in which the
               striatum learns the environmentally based reinforcement
               contingencies, but is ``overridden'' at decision output. Both
               models capture the core behavioral phenomena but, because they
               differ fundamentally on what is learned, make distinct
               predictions for subsequent behavioral and neuroimaging
               experiments. Finally, we attempt to distinguish between the
               proposed computational mechanisms governing instructed behavior
               by fitting a series of abstract ``Q-learning'' and Bayesian
               models to subject data. The best-fitting model supports one of
               the neural models, suggesting the existence of a ``confirmation
               bias'' in which the PFC/HC system trains the reinforcement
               system by amplifying outcomes that are consistent with
               instructions while diminishing inconsistent outcomes.",
  journal   = "Brain Res.",
  publisher = "Elsevier",
  volume    =  1299,
  pages     = "74--94",
  month     =  nov,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Otto2013-yk,
  title     = "The curse of planning: dissecting multiple
               reinforcement-learning systems by taxing the central executive",
  author    = "Otto, A Ross and Gershman, Samuel J and Markman, Arthur B and
               Daw, Nathaniel D",
  abstract  = "A number of accounts of human and animal behavior posit the
               operation of parallel and competing valuation systems in the
               control of choice behavior. In these accounts, a flexible but
               computationally expensive model-based reinforcement-learning
               system has been contrasted with a less flexible but more
               efficient model-free reinforcement-learning system. The factors
               governing which system controls behavior-and under what
               circumstances-are still unclear. Following the hypothesis that
               model-based reinforcement learning requires cognitive resources,
               we demonstrated that having human decision makers perform a
               demanding secondary task engenders increased reliance on a
               model-free reinforcement-learning strategy. Further, we showed
               that, across trials, people negotiate the trade-off between the
               two systems dynamically as a function of concurrent
               executive-function demands, and people's choice latencies
               reflect the computational expenses of the strategy they employ.
               These results demonstrate that competition between multiple
               learning systems can be controlled on a trial-by-trial basis by
               modulating the availability of cognitive resources.",
  journal   = "Psychol. Sci.",
  publisher = "journals.sagepub.com",
  volume    =  24,
  number    =  5,
  pages     = "751--761",
  month     =  may,
  year      =  2013,
  keywords  = "cognitive neuroscience; decision making",
  language  = "en"
}

@ARTICLE{Wolpert1996-cd,
  title     = "The Lack of A Priori Distinctions Between Learning Algorithms",
  author    = "Wolpert, David H",
  abstract  = "This is the first of two papers that use off-training set (OTS)
               error to investigate the assumption-free relationship between
               learning algorithms. This first paper discusses the senses in
               which there are no a priori distinctions between learning
               algorithms. (The second paper discusses the senses in which
               there are such distinctions.) In this first paper it is shown,
               loosely speaking, that for any two algorithms A and B, there are
               ?as many? targets (or priors over targets) for which A has lower
               expected OTS error than B as vice versa, for loss functions like
               zero-one loss. In particular, this is true if A is
               cross-validation and B is ?anti-cross-validation? (choose the
               learning algorithm with largest cross-validation error). This
               paper ends with a discussion of the implications of these
               results for computational learning theory. It is shown that one
               cannot say: if empirical misclassification rate is low, the
               Vapnik-Chervonenkis dimension of your generalizer is small, and
               the training set is large, then with high probability your OTS
               error is small. Other implications for ?membership queries?
               algorithms and ?punting? algorithms are also discussed.",
  journal   = "Neural Comput.",
  publisher = "MIT Press",
  volume    =  8,
  number    =  7,
  pages     = "1341--1390",
  month     =  oct,
  year      =  1996
}

@ARTICLE{Evans2019-tq,
  title    = "Cognitive Control of Escape Behaviour",
  author   = "Evans, Dominic A and Stempel, A Vanessa and Vale, Ruben and
              Branco, Tiago",
  abstract = "When faced with potential predators, animals instinctively decide
              whether there is a threat they should escape from, and also when,
              how, and where to take evasive action. While escape is often
              viewed in classical ethology as an action that is released upon
              presentation of specific stimuli, successful and adaptive escape
              behaviour relies on integrating information from sensory systems,
              stored knowledge, and internal states. From a neuroscience
              perspective, escape is an incredibly rich model that provides
              opportunities for investigating processes such as perceptual and
              value-based decision-making, or action selection, in an
              ethological setting. We review recent research from laboratory
              and field studies that explore, at the behavioural and
              mechanistic levels, how elements from multiple information
              streams are integrated to generate flexible escape behaviour.",
  journal  = "Trends Cogn. Sci.",
  volume   =  23,
  number   =  4,
  pages    = "334--348",
  month    =  apr,
  year     =  2019,
  keywords = "behavioural flexibility; defence; instinctive decisions; threat",
  language = "en"
}

@UNPUBLISHED{Zador2019-fj,
  title    = "A Critique of Pure Learning: What Artificial Neural Networks can
              Learn from Animal Brains",
  author   = "Zador, Anthony",
  abstract = "Over the last decade, artificial neural networks (ANNs), have
              undergone a revolution, catalyzed in large part by better tools
              for supervised learning. However, training such networks requires
              enormous data sets of labeled examples, whereas young animals
              (including humans) typically learn with few or no labeled
              examples. This stark contrast with biological learning has led
              many in the ANN community posit that instead of supervised
              paradigms, animals must rely instead primarily on unsupervised
              learning, leading the search for better unsupervised algorithms.
              Here we argue that much of an animal9s behavioral repertoire is
              not the result of clever learning algorithms--supervised or
              unsupervised--but arises instead from behavior programs already
              present at birth. These programs arise through evolution, are
              encoded in the genome, and emerge as a consequence of wiring up
              the brain. Specifically, animals are born with highly structured
              brain connectivity, which enables them learn very rapidly.
              Recognizing the importance of the highly structured connectivity
              suggests a path toward building ANNs capable of rapid learning.",
  journal  = "bioRxiv",
  pages    = "582643",
  month    =  mar,
  year     =  2019,
  language = "en"
}

@ARTICLE{Ahrlund-Richter2019-ff,
  title    = "A whole-brain atlas of monosynaptic input targeting four
              different cell types in the medial prefrontal cortex of the mouse",
  author   = "{\"A}hrlund-Richter, Sofie and Xuan, Yang and van Lunteren,
              Josina Anna and Kim, Hoseok and Ortiz, Cantin and Pollak Dorocic,
              Iskra and Meletis, Konstantinos and Carl{\'e}n, Marie",
  abstract = "The local and long-range connectivity of cortical neurons are
              considered instrumental to the functional repertoire of the
              cortical region in which they reside. In cortical networks,
              distinct cell types build local circuit structures enabling
              computational operations. Computations in the medial prefrontal
              cortex (mPFC) are thought to be central to cognitive operation,
              including decision-making and memory. We used a retrograde
              trans-synaptic rabies virus system to generate brain-wide maps of
              the input to excitatory neurons as well as three inhibitory
              interneuron subtypes in the mPFC. On the global scale the input
              patterns were found to be mainly cell type independent, with
              quantitative differences in key brain regions, including the
              basal forebrain. Mapping of the local mPFC network revealed high
              connectivity between the different subtypes of interneurons. The
              connectivity mapping gives insight into the information that the
              mPFC processes and the structural architecture underlying the
              mPFC's unique functions.",
  journal  = "Nat. Neurosci.",
  month    =  mar,
  year     =  2019,
  language = "en"
}

@ARTICLE{Saxena2019-it,
  title    = "Towards the neural population doctrine",
  author   = "Saxena, Shreya and Cunningham, John P",
  abstract = "Across neuroscience, large-scale data recording and
              population-level analysis methods have experienced explosive
              growth. While the underlying hardware and computational
              techniques have been well reviewed, we focus here on the novel
              science that these technologies have enabled. We detail four
              areas of the field where the joint analysis of neural populations
              has significantly furthered our understanding of computation in
              the brain: correlated variability, decoding, neural dynamics, and
              artificial neural networks. Together, these findings suggest an
              exciting trend towards a new era where neural populations are
              understood to be the essential unit of computation in many brain
              regions, a classic idea that has been given new life.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  55,
  pages    = "103--111",
  month    =  mar,
  year     =  2019,
  language = "en"
}

@ARTICLE{Gershman2018-gf,
  title    = "The Successor Representation: Its Computational Logic and Neural
              Substrates",
  author   = "Gershman, Samuel J",
  abstract = "Reinforcement learning is the process by which an agent learns to
              predict long-term future reward. We now understand a great deal
              about the brain's reinforcement learning algorithms, but we know
              considerably less about the representations of states and actions
              over which these algorithms operate. A useful starting point is
              asking what kinds of representations we would want the brain to
              have, given the constraints on its computational architecture.
              Following this logic leads to the idea of the successor
              representation, which encodes states of the environment in terms
              of their predictive relationships with other states. Recent
              behavioral and neural studies have provided evidence for the
              successor representation, and computational studies have explored
              ways to extend the original idea. This paper reviews progress on
              these fronts, organizing them within a broader framework for
              understanding how the brain negotiates tradeoffs between
              efficiency and flexibility for reinforcement learning.",
  journal  = "J. Neurosci.",
  volume   =  38,
  number   =  33,
  pages    = "7193--7200",
  month    =  aug,
  year     =  2018,
  keywords = "cognitive map; dopamine; hippocampus; reinforcement learning;
              reward",
  language = "en"
}

@ARTICLE{De_Martino2013-rw,
  title    = "Confidence in value-based choice",
  author   = "De Martino, Benedetto and Fleming, Stephen M and Garrett, Neil
              and Dolan, Raymond J",
  abstract = "Decisions are never perfect, with confidence in one's choices
              fluctuating over time. How subjective confidence and valuation of
              choice options interact at the level of brain and behavior is
              unknown. Using a dynamic model of the decision process, we show
              that confidence reflects the evolution of a decision variable
              over time, explaining the observed relation between confidence,
              value, accuracy and reaction time. As predicted by our dynamic
              model, we show that a functional magnetic resonance imaging
              signal in human ventromedial prefrontal cortex (vmPFC) reflects
              both value comparison and confidence in the value comparison
              process. Crucially, individuals varied in how they related
              confidence to accuracy, allowing us to show that this
              introspective ability is predicted by a measure of functional
              connectivity between vmPFC and rostrolateral prefrontal cortex.
              Our findings provide a mechanistic link between noise in value
              comparison and metacognitive awareness of choice, enabling us
              both to want and to express knowledge of what we want.",
  journal  = "Nat. Neurosci.",
  volume   =  16,
  number   =  1,
  pages    = "105--110",
  month    =  jan,
  year     =  2013,
  language = "en"
}

@ARTICLE{Cortese2018-hj,
  title         = "The neural and cognitive architecture for learning from a
                   small sample",
  author        = "Cortese, Aurelio and De Martino, Benedetto and Kawato,
                   Mitsuo",
  abstract      = "Artificial intelligence algorithms are capable of fantastic
                   exploits, yet they are still grossly inefficient compared
                   with the brain's ability to learn from few exemplars or
                   solve problems that have not been explicitly defined. What
                   is the secret that the evolution of human intelligence has
                   unlocked? Generalization is one answer, but there is more to
                   it. The brain does not directly solve difficult problems, it
                   is able to recast them into new and more tractable problems.
                   Here we propose a model whereby higher cognitive functions
                   profoundly interact with reinforcement learning to
                   drastically reduce the degrees of freedom of the search
                   space, simplifying complex problems and fostering more
                   efficient learning.",
  month         =  oct,
  year          =  2018,
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.NC",
  eprint        = "1810.02476"
}

@ARTICLE{Burgess2007-hn,
  title    = "An oscillatory interference model of grid cell firing",
  author   = "Burgess, Neil and Barry, Caswell and O'Keefe, John",
  abstract = "We expand upon our proposal that the oscillatory interference
              mechanism proposed for the phase precession effect in place cells
              underlies the grid-like firing pattern of dorsomedial entorhinal
              grid cells (O'Keefe and Burgess (2005) Hippocampus 15:853-866).
              The original one-dimensional interference model is generalized to
              an appropriate two-dimensional mechanism. Specifically, dendritic
              subunits of layer II medial entorhinal stellate cells provide
              multiple linear interference patterns along different directions,
              with their product determining the firing of the cell. Connection
              of appropriate speed- and direction-dependent inputs onto
              dendritic subunits could result from an unsupervised learning
              rule which maximizes postsynaptic firing (e.g. competitive
              learning). These inputs cause the intrinsic oscillation of
              subunit membrane potential to increase above theta frequency by
              an amount proportional to the animal's speed of running in the
              ``preferred'' direction. The phase difference between this
              oscillation and a somatic input at theta-frequency essentially
              integrates velocity so that the interference of the two
              oscillations reflects distance traveled in the preferred
              direction. The overall grid pattern is maintained in
              environmental location by phase reset of the grid cell by place
              cells receiving sensory input from the environment, and
              environmental boundaries in particular. We also outline possible
              variations on the basic model, including the generation of
              grid-like firing via the interaction of multiple cells rather
              than via multiple dendritic subunits. Predictions of the
              interference model are given for the frequency composition of EEG
              power spectra and temporal autocorrelograms of grid cell firing
              as functions of the speed and direction of running and the
              novelty of the environment.",
  journal  = "Hippocampus",
  volume   =  17,
  number   =  9,
  pages    = "801--812",
  year     =  2007,
  language = "en"
}

@ARTICLE{OKeefe1996-rj,
  title    = "Geometric determinants of the place fields of hippocampal neurons",
  author   = "O'Keefe, J and Burgess, N",
  abstract = "The human hippocampus has been implicated in memory, in
              particular episodic or declarative memory. In rats, hippocampal
              lesions cause selective spatial deficits, and hippocampal complex
              spike cells (place cells) exhibit spatially localized firing,
              suggesting a role in spatial memory, although broader functions
              have also been suggested. Here we report the identification of
              the environmental features controlling the location and shape of
              the receptive fields (place fields) of the place cells. This was
              done by recording from the same cell in four rectangular boxes
              that differed solely in the length of one or both sides. Most of
              our results are explained by a model in which the place field is
              formed by the summation of gaussian tuning curves, each oriented
              perpendicular to a box wall and peaked at a fixed distance from
              it.",
  journal  = "Nature",
  volume   =  381,
  number   =  6581,
  pages    = "425--428",
  month    =  may,
  year     =  1996,
  language = "en"
}

@ARTICLE{Akrami2018-xc,
  title    = "Posterior parietal cortex represents sensory history and mediates
              its effects on behaviour",
  author   = "Akrami, Athena and Kopec, Charles D and Diamond, Mathew E and
              Brody, Carlos D",
  abstract = "Many models of cognition and of neural computations posit the use
              and estimation of prior stimulus statistics: it has long been
              known that working memory and perception are strongly impacted by
              previous sensory experience, even when that sensory history is
              not relevant to the current task at hand. Nevertheless, the
              neural mechanisms and regions of the brain that are necessary for
              computing and using such prior experience are unknown. Here we
              report that the posterior parietal cortex (PPC) is a critical
              locus for the representation and use of prior stimulus
              information. We trained rats in an auditory parametric working
              memory task, and found that they displayed substantial and
              readily quantifiable behavioural effects of sensory-stimulus
              history, similar to those observed in humans and monkeys. Earlier
              proposals that the PPC supports working memory predict that
              optogenetic silencing of this region would impair behaviour in
              our working memory task. Contrary to this prediction, we found
              that silencing the PPC significantly improved performance.
              Quantitative analyses of behaviour revealed that this improvement
              was due to the selective reduction of the effects of prior
              sensory stimuli. Electrophysiological recordings showed that PPC
              neurons carried far more information about the sensory stimuli of
              previous trials than about the stimuli of the current trial.
              Furthermore, for a given rat, the more information about previous
              trial sensory history in the neural firing rates of the PPC, the
              greater the behavioural effect of sensory history, suggesting a
              tight link between behaviour and PPC representations of stimulus
              history. Our results indicate that the PPC is a central component
              in the processing of sensory-stimulus history, and could enable
              further neurobiological investigation of long-standing questions
              regarding how perception and working memory are affected by prior
              sensory information.",
  journal  = "Nature",
  volume   =  554,
  number   =  7692,
  pages    = "368--372",
  month    =  feb,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Duan2018-yh,
  title    = "Collicular circuits for flexible sensorimotor routing",
  author   = "Duan, Chunyu A and Pagan, Marino and Piet, Alex T and Kopec,
              Charles D and Akrami, Athena and Riordan, Alexander J and Erlich,
              Jeffrey C and Brody, Carlos D",
  abstract = "Flexible and fast sensorimotor routing, based on relevant
              environmental context, is a central component of executive
              control, with prefrontal cortex (PFC) thought of as playing a
              critical role and the midbrain superior colliculus (SC) more
              traditionally viewed as the output of cortical flexible routing.
              Here, using a rat task in which subjects switch rapidly between
              task contexts that demand changes in sensorimotor mappings, we
              report that silencing of the SC during a delay period, during
              which task context is encoded in SC activity, impaired choice
              accuracy. But inactivations during the subsequent choice period,
              during which the subject selects their motor response, did not.
              Furthermore, a defined subset of SC neurons encoded task context
              more strongly than PFC neurons, and encoded the subject9s motor
              output choice faster than PFC neurons or other SC neurons. These
              data suggest cognitive and decision-making roles for the SC. We
              used computational methods to identify different SC circuit
              architectures that could account for these results. We found
              numerous, highly varied SC model circuits that matched our
              experimental data, including circuits without inhibitory
              connections between units representing opposite decision outputs.
              But all successful model circuits had inhibitory connections
              between units on the same side of the brain representing opposite
              contexts. This anatomical feature appears to be a key
              experimental prediction for models in which the SC plays a
              decision-making role during executive control.",
  journal  = "bioRxiv",
  pages    = "245613",
  month    =  jan,
  year     =  2018,
  language = "en"
}

@ARTICLE{noauthor_undated-cn,

}

@ARTICLE{Erdem2012-xv,
  title     = "A goal-directed spatial navigation model using forward
               trajectory planning based on grid cells",
  author    = "Erdem, U{\u g}ur M and Hasselmo, Michael",
  abstract  = "A goal-directed navigation model is proposed based on forward
               linear look-ahead probe of trajectories in a network of head
               direction cells, grid cells, place cells and prefrontal cortex
               (PFC) cells. The model allows selection of new goal-directed
               trajectories. In a novel environment, the virtual rat
               incrementally creates a map composed of place cells and PFC
               cells by random exploration. After exploration, the rat
               retrieves memory of the goal location, picks its next movement
               direction by forward linear look-ahead probe of trajectories in
               several candidate directions while stationary in one location,
               and finds the one activating PFC cells with the highest reward
               signal. Each probe direction involves activation of a static
               pattern of head direction cells to drive an interference model
               of grid cells to update their phases in a specific direction.
               The updating of grid cell spiking drives place cells along the
               probed look-ahead trajectory similar to the forward replay
               during waking seen in place cell recordings. Directions are
               probed until the look-ahead trajectory activates the reward
               signal and the corresponding direction is used to guide
               goal-finding behavior. We report simulation results in several
               mazes with and without barriers. Navigation with barriers
               requires a PFC map topology based on the temporal vicinity of
               visited place cells and a reward signal diffusion process. The
               interaction of the forward linear look-ahead trajectory probes
               with the reward diffusion allows discovery of never-before
               experienced shortcuts towards a goal location.",
  journal   = "Eur. J. Neurosci.",
  publisher = "Wiley Online Library",
  volume    =  35,
  number    =  6,
  pages     = "916--931",
  month     =  mar,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Vikbladh2019-qe,
  title     = "Hippocampal Contributions to {Model-Based} Planning and Spatial
               Memory",
  author    = "Vikbladh, Oliver M and Meager, Michael R and King, John and
               Blackmon, Karen and Devinsky, Orrin and Shohamy, Daphna and
               Burgess, Neil and Daw, Nathaniel D",
  abstract  = "SummaryLittle is known about the neural mechanisms that allow
               humans and animals to plan actions using knowledge of task
               contingencies. Emerging theories hypothesize that it involves
               the same hippocampal mechanisms that support self-localization
               and memory for locations. Yet limited direct evidence supports
               the link between planning and the hippocampal place map. We
               addressed this by investigating model-based planning and place
               memory in healthy controls and epilepsy patients treated using
               unilateral anterior temporal lobectomy with hippocampal
               resection. Both functions were impaired in the patient group.
               Specifically, the planning impairment was related to right
               hippocampal lesion size, controlling for overall lesion size.
               Furthermore, although planning and boundary-driven place memory
               covaried in the control group, this relationship was attenuated
               in patients, consistent with both functions relying on the same
               structure in the healthy brain. These findings clarify both the
               neural mechanism of model-based planning and the scope of
               hippocampal contributions to behavior.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  0,
  number    =  0,
  month     =  mar,
  year      =  2019,
  keywords  = "decision-making; model-based; reinforcement learning; planning;
               spatial; memory; human; hippocampus; anterior temporal lobe;
               lesion",
  language  = "en"
}

@ARTICLE{Alvernhe2008-dx,
  title     = "Different {CA1} and {CA3} representations of novel routes in a
               shortcut situation",
  author    = "Alvernhe, Alice and Van Cauter, Tiffany and Save, Etienne and
               Poucet, Bruno",
  abstract  = "Place cells are hippocampal neurons whose discharge is strongly
               related to a rat's location in its environment. The existence of
               place cells has led to the proposal that they are part of an
               integrated neural system dedicated to spatial navigation. To
               further understand the relationships between place cell firing
               and spatial problem solving, we examined the discharge of CA1
               and CA3 place cells as rats were exposed to a shortcut in a
               runway maze. On specific sessions, a wall section of the maze
               was removed so as to open a shorter novel route within the
               otherwise familiar maze. We found that the discharge of both CA1
               and CA3 cells was strongly affected in the vicinity of the
               shortcut region but was much less affected farther away. In
               addition, CA3 fields away from the shortcut were more altered
               than CA1 fields. Thus, place cell firing appears to reflect more
               than just the animal's spatial location and may provide
               additional information about possible motions, or routes, within
               the environment. This kinematic representation appears to be
               spatially more extended in CA3 than in CA1, suggesting
               interesting computational differences between the two
               subregions.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  28,
  number    =  29,
  pages     = "7324--7333",
  month     =  jul,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Alvernhe2011-st,
  title     = "Local remapping of place cell firing in the Tolman detour task",
  author    = "Alvernhe, Alice and Save, Etienne and Poucet, Bruno",
  abstract  = "The existence of place cells, whose discharge is strongly
               related to a rat's location in its environment, has led to the
               proposal that they form part of an integrated neural system
               dedicated to spatial navigation. It has been suggested that this
               system could represent space as a cognitive map, which is
               flexibly used by animals to plan new shortcuts or efficient
               detours. To further understand the relationships between
               hippocampal place cell firing and cognitive maps, we examined
               the discharge of place cells as rats were exposed to a
               Tolman-type detour problem. In specific sessions, a transparent
               barrier was placed onto the maze so as to block the shortest
               central path between the two rewarded end locations of a
               familiar three-way maze. We found that rats rapidly and
               consistently chose the shortest alternative detour. Furthermore,
               both CA1 and CA3 place cells that had a field in the vicinity of
               the barrier displayed local remapping. In contrast, neither CA1
               nor CA3 cells that had a field away from the barrier were
               affected. This finding, at odds with our previous report of
               altered CA3 discharge for distant fields in a shortcut task,
               suggests that the availability of a novel path and the blocking
               of a familiar path are not equivalent and could lead to
               different responses of the CA3 place cell population. Together,
               the two studies point to a specific role of CA3 in the
               representation of spatial connectivity and sequences.",
  journal   = "Eur. J. Neurosci.",
  publisher = "Wiley Online Library",
  volume    =  33,
  number    =  9,
  pages     = "1696--1705",
  month     =  may,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Simon2011-ky,
  title     = "Neural correlates of forward planning in a spatial decision task
               in humans",
  author    = "Simon, Dylan Alexander and Daw, Nathaniel D",
  abstract  = "Although reinforcement learning (RL) theories have been
               influential in characterizing the mechanisms for reward-guided
               choice in the brain, the predominant temporal difference (TD)
               algorithm cannot explain many flexible or goal-directed actions
               that have been demonstrated behaviorally. We investigate such
               actions by contrasting an RL algorithm that is model based, in
               that it relies on learning a map or model of the task and
               planning within it, to traditional model-free TD learning. To
               distinguish these approaches in humans, we used functional
               magnetic resonance imaging in a continuous spatial navigation
               task, in which frequent changes to the layout of the maze forced
               subjects continually to relearn their favored routes, thereby
               exposing the RL mechanisms used. We sought evidence for the
               neural substrates of such mechanisms by comparing choice
               behavior and blood oxygen level-dependent (BOLD) signals to
               decision variables extracted from simulations of either
               algorithm. Both choices and value-related BOLD signals in
               striatum, although most often associated with TD learning, were
               better explained by the model-based theory. Furthermore,
               predecessor quantities for the model-based value computation
               were correlated with BOLD signals in the medial temporal lobe
               and frontal cortex. These results point to a significant
               extension of both the computational and anatomical substrates
               for RL in the brain.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  31,
  number    =  14,
  pages     = "5526--5539",
  month     =  apr,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Gustafson2011-ua,
  title    = "Grid cells, place cells, and geodesic generalization for spatial
              reinforcement learning",
  author   = "Gustafson, Nicholas J and Daw, Nathaniel D",
  abstract = "Reinforcement learning (RL) provides an influential
              characterization of the brain's mechanisms for learning to make
              advantageous choices. An important problem, though, is how
              complex tasks can be represented in a way that enables efficient
              learning. We consider this problem through the lens of spatial
              navigation, examining how two of the brain's location
              representations--hippocampal place cells and entorhinal grid
              cells--are adapted to serve as basis functions for approximating
              value over space for RL. Although much previous work has focused
              on these systems' roles in combining upstream sensory cues to
              track location, revisiting these representations with a focus on
              how they support this downstream decision function offers
              complementary insights into their characteristics. Rather than
              localization, the key problem in learning is generalization
              between past and present situations, which may not match
              perfectly. Accordingly, although neural populations collectively
              offer a precise representation of position, our simulations of
              navigational tasks verify the suggestion that RL gains efficiency
              from the more diffuse tuning of individual neurons, which allows
              learning about rewards to generalize over longer distances given
              fewer training experiences. However, work on generalization in RL
              suggests the underlying representation should respect the
              environment's layout. In particular, although it is often assumed
              that neurons track location in Euclidean coordinates (that a
              place cell's activity declines ``as the crow flies'' away from
              its peak), the relevant metric for value is geodesic: the
              distance along a path, around any obstacles. We formalize this
              intuition and present simulations showing how Euclidean, but not
              geodesic, representations can interfere with RL by generalizing
              inappropriately across barriers. Our proposal that place and grid
              responses should be modulated by geodesic distances suggests
              novel predictions about how obstacles should affect spatial
              firing fields, which provides a new viewpoint on data concerning
              both spatial codes.",
  journal  = "PLoS Comput. Biol.",
  volume   =  7,
  number   =  10,
  pages    = "e1002235",
  month    =  oct,
  year     =  2011,
  language = "en"
}

@INCOLLECTION{Lengyel2008-xy,
  title     = "Hippocampal Contributions to Control: The Third Way",
  booktitle = "Advances in Neural Information Processing Systems 20",
  author    = "Lengyel, M{\'a}t{\'e} and Dayan, Peter",
  editor    = "Platt, J C and Koller, D and Singer, Y and Roweis, S T",
  publisher = "Curran Associates, Inc.",
  pages     = "889--896",
  year      =  2008
}

@ARTICLE{Bennett1996-wj,
  title    = "Do animals have cognitive maps?",
  author   = "Bennett, A T",
  abstract = "Drawing on studies of humans, rodents, birds and arthropods, I
              show that 'cognitive maps' have been used to describe a wide
              variety of spatial concepts. There are, however, two main
              definitions. One, sensu Tolman, O'Keefe and Nadel, is that a
              cognitive map is a powerful memory of landmarks which allows
              novel short-cutting to occur. The other, sensu Gallistel, is that
              a cognitive map is any representation of space held by an animal.
              Other definitions with quite different meanings are also
              summarised. I argue that no animal has been conclusively shown to
              have a cognitive map, sensu Tolman, O'Keefe and Nadel, because
              simpler explanations of the crucial novel short-cutting results
              are invariably possible. Owing to the repeated inability of
              experimenters to eliminate these simpler explanations over at
              least 15 years, and the confusion caused by the numerous
              contradictory definitions of a cognitive map, I argue that the
              cognitive map is no longer a useful hypothesis for elucidating
              the spatial behaviour of animals and that use of the term should
              be avoided.",
  journal  = "J. Exp. Biol.",
  volume   =  199,
  number   = "Pt 1",
  pages    = "219--224",
  month    =  jan,
  year     =  1996,
  language = "en"
}

@UNPUBLISHED{Alvarez2019-gb,
  title    = "Modeling decision-making under uncertainty: a direct comparison
              study between human and mouse gambling data",
  author   = "Alvarez, Lidia Cabeza and Giustiniani, Julie and Chabin, Thibault
              and Ramadan, Bahrie and Joucla, Coralie and Nicolier, Magali and
              Pazart, Lionel and Haffen, Emmanuel and Fellmann, Dominique and
              Gabriel, Damien and Peterschmitt, Yvan",
  abstract = "Decision-making is a conserved evolutionary process enabling to
              choose one option among several alternatives, and relying on
              reward and cognitive control systems. The Iowa Gambling Task
              allows to assess human decision-making under uncertainty by
              presenting four cards decks with various cost-benefit
              probabilities. Participants seek to maximize their monetary gains
              by developing long-term optimal choice strategies. Animal
              versions have been adapted with nutritional rewards but
              interspecies data comparisons are still scarce. Our study
              directly compared physiological decision-making performances
              between humans and wild-type C57BL/6 mice. Human subjects
              fulfilled an electronic Iowa Gambling Task version while mice
              performed a maze-based adaptation with four arms baited in a
              probabilistic way. Our data show closely matching performances
              among species with similar patterns of choice behaviors.
              Moreover, both populations clustered into good, intermediate, and
              poor decision-making categories with similar proportions.
              Remarkably, mice good decision-makers behaved as humans of the
              same category, but slight differences among species have been
              evidenced for the other two subpopulations. Overall, our direct
              comparative study confirms the good face validity of the rodent
              gambling task. Extended behavioral characterization and
              pathological animal models should help strengthen its construct
              validity and disentangle determinants of decision-making in
              animals and humans.",
  journal  = "bioRxiv",
  pages    = "570499",
  month    =  mar,
  year     =  2019,
  language = "en"
}

@ARTICLE{Spiers2015-fh,
  title    = "Solving the detour problem in navigation: a model of prefrontal
              and hippocampal interactions",
  author   = "Spiers, Hugo J and Gilbert, Sam J",
  abstract = "Adapting behavior to accommodate changes in the environment is an
              important function of the nervous system. A universal problem for
              motile animals is the discovery that a learned route is blocked
              and a detour is required. Given the substantial neuroscience
              research on spatial navigation and decision-making it is
              surprising that so little is known about how the brain solves the
              detour problem. Here we review the limited number of relevant
              functional neuroimaging, single unit recording and lesion
              studies. We find that while the prefrontal cortex (PFC)
              consistently responds to detours, the hippocampus does not.
              Recent evidence suggests the hippocampus tracks information about
              the future path distance to the goal. Based on this evidence we
              postulate a conceptual model in which: Lateral PFC provides a
              prediction error signal about the change in the path, frontopolar
              and superior PFC support the re-formulation of the route plan as
              a novel subgoal and the hippocampus simulates the new path. More
              data will be required to validate this model and understand (1)
              how the system processes the different options; and (2) deals
              with situations where a new path becomes available (i.e.,
              shortcuts).",
  journal  = "Front. Hum. Neurosci.",
  volume   =  9,
  pages    = "125",
  month    =  mar,
  year     =  2015,
  keywords = "artificial intelligence; goals; hippocampus; place cells;
              planning; prediction error; reinforcement learning; virtual
              reality",
  language = "en"
}

@ARTICLE{Pezzulo2013-jy,
  title    = "The mixed instrumental controller: using value of information to
              combine habitual choice and mental simulation",
  author   = "Pezzulo, Giovanni and Rigoli, Francesco and Chersi, Fabian",
  abstract = "Instrumental behavior depends on both goal-directed and habitual
              mechanisms of choice. Normative views cast these mechanisms in
              terms of model-free and model-based methods of reinforcement
              learning, respectively. An influential proposal hypothesizes that
              model-free and model-based mechanisms coexist and compete in the
              brain according to their relative uncertainty. In this paper we
              propose a novel view in which a single Mixed Instrumental
              Controller produces both goal-directed and habitual behavior by
              flexibly balancing and combining model-based and model-free
              computations. The Mixed Instrumental Controller performs a
              cost-benefits analysis to decide whether to chose an action
              immediately based on the available ``cached'' value of actions
              (linked to model-free mechanisms) or to improve value estimation
              by mentally simulating the expected outcome values (linked to
              model-based mechanisms). Since mental simulation entails
              cognitive effort and increases the reward delay, it is activated
              only when the associated ``Value of Information'' exceeds its
              costs. The model proposes a method to compute the Value of
              Information, based on the uncertainty of action values and on the
              distance of alternative cached action values. Overall, the model
              by default chooses on the basis of lighter model-free estimates,
              and integrates them with costly model-based predictions only when
              useful. Mental simulation uses a sampling method to produce
              reward expectancies, which are used to update the cached value of
              one or more actions; in turn, this updated value is used for the
              choice. The key predictions of the model are tested in different
              settings of a double T-maze scenario. Results are discussed in
              relation with neurobiological evidence on the hippocampus -
              ventral striatum circuit in rodents, which has been linked to
              goal-directed spatial navigation.",
  journal  = "Front. Psychol.",
  volume   =  4,
  pages    = "92",
  month    =  mar,
  year     =  2013,
  keywords = "exploration-exploitation; forward sweeps; goal-directed
              decision-making; hippocampus; model-based reinforcement learning;
              value of information; ventral striatum",
  language = "en"
}

@ARTICLE{Lansink2012-ha,
  title    = "Reward cues in space: commonalities and differences in neural
              coding by hippocampal and ventral striatal ensembles",
  author   = "Lansink, Carien S and Jackson, Jadin C and Lankelma, Jan V and
              Ito, Rutsuko and Robbins, Trevor W and Everitt, Barry J and
              Pennartz, Cyriel M A",
  abstract = "Forming place-reward associations critically depends on the
              integrity of the hippocampal-ventral striatal system. The ventral
              striatum (VS) receives a strong hippocampal input conveying
              spatial-contextual information, but it is unclear how this
              structure integrates this information to invigorate
              reward-directed behavior. Neuronal ensembles in rat hippocampus
              (HC) and VS were simultaneously recorded during a conditioning
              task in which navigation depended on path integration. In
              contrast to HC, ventral striatal neurons showed low spatial
              selectivity, but rather coded behavioral task phases toward
              reaching goal sites. Outcome-predicting cues induced a remapping
              of firing patterns in the HC, consistent with its role in
              episodic memory. VS remapped in conjunction with the HC,
              indicating that remapping can take place in multiple brain
              regions engaged in the same task. Subsets of ventral striatal
              neurons showed a ``flip'' from high activity when cue lights were
              illuminated to low activity in intertrial intervals, or vice
              versa. The cues induced an increase in spatial information
              transmission and sparsity in both structures. These effects were
              paralleled by an enhanced temporal specificity of ensemble coding
              and a more accurate reconstruction of the animal's position from
              population firing patterns. Altogether, the results reveal strong
              differences in spatial processing between hippocampal area CA1
              and VS, but indicate similarities in how discrete cues impact on
              this processing.",
  journal  = "J. Neurosci.",
  volume   =  32,
  number   =  36,
  pages    = "12444--12459",
  month    =  sep,
  year     =  2012,
  language = "en"
}

@ARTICLE{Pezzulo2014-ph,
  title    = "Internally generated sequences in learning and executing
              goal-directed behavior",
  author   = "Pezzulo, Giovanni and van der Meer, Matthijs A A and Lansink,
              Carien S and Pennartz, Cyriel M A",
  abstract = "A network of brain structures including hippocampus (HC),
              prefrontal cortex, and striatum controls goal-directed behavior
              and decision making. However, the neural mechanisms underlying
              these functions are unknown. Here, we review the role of
              'internally generated sequences': structured, multi-neuron firing
              patterns in the network that are not confined to signaling the
              current state or location of an agent, but are generated on the
              basis of internal brain dynamics. Neurophysiological studies
              suggest that such sequences fulfill functions in memory
              consolidation, augmentation of representations, internal
              simulation, and recombination of acquired information. Using
              computational modeling, we propose that internally generated
              sequences may be productively considered a component of
              goal-directed decision systems, implementing a sampling-based
              inference engine that optimizes goal acquisition at multiple
              timescales of on-line choice, action control, and learning.",
  journal  = "Trends Cogn. Sci.",
  volume   =  18,
  number   =  12,
  pages    = "647--657",
  month    =  dec,
  year     =  2014,
  keywords = "decision making; forward sweep; generative models; hippocampus;
              inference; prospection; reinforcement learning; replay; spatial
              navigation; theta rhythm; ventral striatum",
  language = "en"
}

@ARTICLE{Daw2014-nr,
  title     = "The algorithmic anatomy of model-based evaluation",
  author    = "Daw, Nathaniel D and Dayan, Peter",
  abstract  = "Despite many debates in the first half of the twentieth century,
               it is now largely a truism that humans and other animals build
               models of their environments and use them for prediction and
               control. However, model-based (MB) reasoning presents severe
               computational challenges. Alternative, computationally simpler,
               model-free (MF) schemes have been suggested in the reinforcement
               learning literature, and have afforded influential accounts of
               behavioural and neural data. Here, we study the realization of
               MB calculations, and the ways that this might be woven together
               with MF values and evaluation methods. There are as yet mostly
               only hints in the literature as to the resulting tapestry, so we
               offer more preview than review.",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "royalsocietypublishing.org",
  volume    =  369,
  number    =  1655,
  month     =  nov,
  year      =  2014,
  keywords  = "Monte Carlo tree search; model-based reasoning; model-free
               reasoning; orbitofrontal cortex; reinforcement learning;
               striatum",
  language  = "en"
}

@ARTICLE{Dolan2013-rb,
  title    = "Goals and habits in the brain",
  author   = "Dolan, Ray J and Dayan, Peter",
  abstract = "An enduring and richly elaborated dichotomy in cognitive
              neuroscience is that of reflective versus reflexive decision
              making and choice. Other literatures refer to the two ends of
              what is likely to be a spectrum with terms such as goal-directed
              versus habitual, model-based versus model-free or prospective
              versus retrospective. One of the most rigorous traditions of
              experimental work in the field started with studies in rodents
              and graduated via human versions and enrichments of those
              experiments to a current state in which new paradigms are probing
              and challenging the very heart of the distinction. We review four
              generations of work in this tradition and provide pointers to the
              forefront of the field's fifth generation.",
  journal  = "Neuron",
  volume   =  80,
  number   =  2,
  pages    = "312--325",
  month    =  oct,
  year     =  2013,
  language = "en"
}

@ARTICLE{Nitz2012-rm,
  title    = "Spaces within spaces: rat parietal cortex neurons register
              position across three reference frames",
  author   = "Nitz, Douglas A",
  abstract = "We recorded parietal cortex neurons as rats traversed squared
              spiral tracks. Spatial firing patterns distinguished the
              behaviorally identical track segments composing loops, yet
              recurred with increasing or decreasing amplitude across the five
              loops composing the full track. These results indicate that
              parietal cortex neurons simultaneously respond to spatial
              relationships in multiple external reference frames, a phenomenon
              that may reflect a neural mechanism for relating parts to a
              whole.",
  journal  = "Nat. Neurosci.",
  volume   =  15,
  number   =  10,
  pages    = "1365--1367",
  month    =  oct,
  year     =  2012,
  keywords = "Locomotion",
  language = "en"
}

@ARTICLE{noauthor_undated-uu,
  title = "Prefrontal cortex creates novel navigation sequences from
           hippocampal place-cell replay with spatial reward propagation"
}

@ARTICLE{Hok2007-zu,
  title    = "Goal-related activity in hippocampal place cells",
  author   = "Hok, Vincent and Lenck-Santini, Pierre-Pascal and Roux,
              S{\'e}bastien and Save, Etienne and Muller, Robert U and Poucet,
              Bruno",
  abstract = "Place cells are hippocampal neurons whose discharge is strongly
              related to a rat's location in its environment. The existence of
              place cells has led to the proposal that they are part of an
              integrated neural system dedicated to spatial navigation, an idea
              supported by the discovery of strong relationships between place
              cell activity and spatial problem solving. To further understand
              such relationships, we examined the discharge of place cells
              recorded while rats solved a place navigation task. We report
              that, in addition to having widely distributed firing fields,
              place cells also discharge selectively while the hungry rat waits
              in an unmarked goal location to release a food pellet. Such
              firing is not duplicated in other locations outside the main
              firing field even when the rat's behavior is constrained to be
              extremely similar to the behavior at the goal. We therefore
              propose that place cells provide both a geometric representation
              of the current environment and a reflection of the rat's
              expectancy that it is located correctly at the goal. This on-line
              feedback about a critical aspect of navigational performance is
              proposed to be signaled by the synchronous activity of the large
              fraction of place cells active at the goal. In combination with
              other (prefrontal) cells that provide coarse encoding of goal
              location, hippocampal place cells may therefore participate in a
              neural network allowing the rat to plan accurate trajectories in
              space.",
  journal  = "J. Neurosci.",
  volume   =  27,
  number   =  3,
  pages    = "472--482",
  month    =  jan,
  year     =  2007,
  language = "en"
}

@ARTICLE{Botvinick2012-ez,
  title    = "Hierarchical reinforcement learning and decision making",
  author   = "Botvinick, Matthew Michael",
  abstract = "The hierarchical structure of human and animal behavior has been
              of critical interest in neuroscience for many years. Yet
              understanding the neural processes that give rise to such
              structure remains an open challenge. In recent research, a new
              perspective on hierarchical behavior has begun to take shape,
              inspired by ideas from machine learning, and in particular the
              framework of hierarchical reinforcement learning. Hierarchical
              reinforcement learning builds on traditional reinforcement
              learning mechanisms, extending them to accommodate temporally
              extended behaviors or subroutines. The resulting computational
              paradigm has begun to influence both theoretical and empirical
              work in neuroscience, conceptually aligning the study of
              hierarchical behavior with research on other aspects of learning
              and decision making, and giving rise to some thought-provoking
              new findings.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "956--962",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Barto2003-bz,
  title     = "Recent Advances in Hierarchical Reinforcement Learning",
  author    = "Barto, Andrew G and Mahadevan, Sridhar",
  abstract  = "Reinforcement learning is bedeviled by the curse of
               dimensionality: the number of parameters to be learned grows
               exponentially with the size of any compact encoding of a state.
               Recent attempts to combat the curse of dimensionality have
               turned to principled ways of exploiting temporal abstraction,
               where decisions are not required at each step, but rather invoke
               the execution of temporally-extended activities which follow
               their own policies until termination. This leads naturally to
               hierarchical control architectures and associated learning
               algorithms. We review several approaches to temporal abstraction
               and hierarchical organization that machine learning researchers
               have recently developed. Common to these approaches is a
               reliance on the theory of semi-Markov decision processes, which
               we emphasize in our review. We then discuss extensions of these
               ideas to concurrent activities, multiagent coordination, and
               hierarchical memory for addressing partial observability.
               Concluding remarks address open challenges facing the further
               development of reinforcement learning in a hierarchical setting.",
  journal   = "Discrete Event Dyn. Syst.: Theory Appl.",
  publisher = "Springer",
  volume    =  13,
  number    =  1,
  pages     = "41--77",
  month     =  jan,
  year      =  2003
}

@ARTICLE{Dosovitskiy2016-au,
  title         = "Learning to Act by Predicting the Future",
  author        = "Dosovitskiy, Alexey and Koltun, Vladlen",
  abstract      = "We present an approach to sensorimotor control in immersive
                   environments. Our approach utilizes a high-dimensional
                   sensory stream and a lower-dimensional measurement stream.
                   The cotemporal structure of these streams provides a rich
                   supervisory signal, which enables training a sensorimotor
                   control model by interacting with the environment. The model
                   is trained using supervised learning techniques, but without
                   extraneous supervision. It learns to act based on raw
                   sensory input from a complex three-dimensional environment.
                   The presented formulation enables learning without a fixed
                   goal at training time, and pursuing dynamically changing
                   goals at test time. We conduct extensive experiments in
                   three-dimensional simulations based on the classical
                   first-person game Doom. The results demonstrate that the
                   presented approach outperforms sophisticated prior
                   formulations, particularly on challenging tasks. The results
                   also show that trained models successfully generalize across
                   environments and goals. A model trained using the presented
                   approach won the Full Deathmatch track of the Visual Doom AI
                   Competition, which was held in previously unseen
                   environments.",
  month         =  nov,
  year          =  2016,
  archivePrefix = "arXiv",
  primaryClass  = "cs.LG",
  eprint        = "1611.01779"
}

@ARTICLE{Lei2018-ih,
  title    = "Dynamic Path Planning of Unknown Environment Based on Deep
              Reinforcement Learning",
  author   = "Lei, Xiaoyun and Zhang, Zhian and Dong, Peifang",
  abstract = "PDF | Dynamic path planning of unknown environment has always
              been a challenge for mobile robots. In this paper, we apply
              double Q-network (DDQN) deep reinforcement learning proposed by
              DeepMind in 2016 to dynamic path planning of unknown environment.
              The reward and punishment...",
  journal  = "Journal of Robotics",
  volume   =  2018,
  number   =  12,
  pages    = "1--10",
  month    =  sep,
  year     =  2018
}

@INPROCEEDINGS{Mannucci2016-ja,
  title     = "A hierarchical maze navigation algorithm with Reinforcement
               Learning and mapping",
  booktitle = "2016 {IEEE} Symposium Series on Computational Intelligence
               ({SSCI})",
  author    = "Mannucci, T and van Kampen, E",
  abstract  = "Goal-finding in an unknown maze is a challenging problem for a
               Reinforcement Learning agent, because the corresponding state
               space can be large if not intractable, and the agent does not
               usually have a model of the environment. Hierarchical
               Reinforcement Learning has been shown in the past to improve
               tractability and learning time of complex problems, as well as
               facilitate learning a coherent transition model for the
               environment. Nonetheless, considerable time is still needed to
               learn the transition model, so that initially the agent can
               perform poorly by getting trapped into dead ends and colliding
               with obstacles. This paper proposes a strategy for maze
               exploration that, by means of sequential tasking and off-line
               training on an abstract environment, provides the agent with a
               minimal level of performance from the very beginning of
               exploration. In particular, this approach allows to prevent
               collisions with obstacles, thus enforcing a safety restraint on
               the agent.",
  pages     = "1--8",
  month     =  dec,
  year      =  2016,
  keywords  = "learning (artificial intelligence);safety restraint;off-line
               training;sequential tasking;maze exploration;reinforcement
               learning;hierarchical maze navigation
               algorithm;Trajectory;Navigation;Robot sensing systems;Learning
               (artificial intelligence);Training;Sonar"
}

@ARTICLE{Oess2017-fp,
  title    = "A Computational Model for Spatial Navigation Based on Reference
              Frames in the Hippocampus, Retrosplenial Cortex, and Posterior
              Parietal Cortex",
  author   = "Oess, Timo and Krichmar, Jeffrey L and R{\"o}hrbein, Florian",
  abstract = "Behavioral studies for humans, monkeys, and rats have shown that,
              while traversing an environment, these mammals tend to use
              different frames of reference and frequently switch between them.
              These frames represent allocentric, egocentric, or route-centric
              views of the environment. However, combinations of either of them
              are often deployed. Neurophysiological studies on rats have
              indicated that the hippocampus, the retrosplenial cortex, and the
              posterior parietal cortex contribute to the formation of these
              frames and mediate the transformation between those. In this
              paper, we construct a computational model of the posterior
              parietal cortex and the retrosplenial cortex for spatial
              navigation. We demonstrate how the transformation of reference
              frames could be realized in the brain and suggest how different
              brain areas might use these reference frames to form navigational
              strategies and predict under what conditions an animal might use
              a specific type of reference frame. Our simulated navigation
              experiments demonstrate that the model's results closely resemble
              behavioral findings in humans and rats. These results suggest
              that navigation strategies may depend on the animal's reliance in
              a particular reference frame and shows how low confidence in a
              reference frame can lead to fluid adaptation and deployment of
              alternative navigation strategies. Because of its flexibility,
              our biologically inspired navigation system may be applied to
              autonomous robots.",
  journal  = "Front. Neurorobot.",
  volume   =  11,
  pages    = "4",
  month    =  feb,
  year     =  2017,
  keywords = "computational model; frames of reference; hippocampus; posterior
              parietal cortex; retrosplenial cortex; spatial navigation",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Darekar2018-xd,
  title    = "Modeling spatial navigation in the presence of dynamic obstacles:
              a differential games approach",
  author   = "Darekar, Anuja and Goussev, Valery and McFadyen, Bradford J and
              Lamontagne, Anouk and Fung, Joyce",
  abstract = "Obstacle circumvention strategies can be shaped by the dynamic
              interaction of an individual (evader) and an obstacle (pursuer).
              We have developed a mathematical model with predictive and
              emergent components, using experimental data from seven healthy
              young adults walking toward a target while avoiding collision
              with a stationary or moving obstacle (approaching head-on, or
              diagonally 30° left or right) in a virtual environment. Two
              linear properties from the predictive component enable the evader
              to predict the minimum distance between itself and the obstacle
              at all times, including the future intersection of trajectories.
              The emergent component uses the classical differential games
              model to solve for an optimal circumvention while reaching the
              target, wherein the locomotor strategy is influenced by the
              obstacle, target, and the evader velocity. Both model components
              were fitted to a different set of experimental data obtained from
              five poststroke and healthy participants to derive the minimum
              predicted distance (predictive component) and obstacle influence
              dimensions (emergent component) during circumvention. Minimum
              predicted distance between evader and pursuer was kept constant
              when the evader was closest to the obstacle in all participants.
              Obstacle influence dimensions varied depending on obstacle
              approach condition and preferred side of circumvention,
              reflecting differences in locomotor strategies between poststroke
              and healthy individuals. Additionally, important associations
              between model outputs and observed experimental outcomes were
              found. The model, supported by experimental data, suggests that
              both predictive and emergent processes can shape obstacle
              circumvention strategies in healthy and poststroke individuals.
              NEW \& NOTEWORTHY Obstacle circumvention during goal-directed
              locomotion is modeled with a new mathematical approach comprising
              both predictive and emergent elements. The major novelty is using
              differential games solutions to illustrate the dynamic
              interactions between the individual as an evader and the
              approaching obstacle as a pursuer. The model is supported by
              experimental evidence that explains the behavior along the
              continuum of locomotor adaptation displayed by healthy subjects
              and individuals with stroke.",
  journal  = "J. Neurophysiol.",
  volume   =  119,
  number   =  3,
  pages    = "990--1004",
  month    =  mar,
  year     =  2018,
  keywords = "collision avoidance; locomotion; modeling; obstacle
              circumvention; stroke;Locomotion",
  language = "en"
}

@ARTICLE{Panov2018-xf,
  title    = "Grid Path Planning with Deep Reinforcement Learning: Preliminary
              Results",
  author   = "Panov, Aleksandr I and Yakovlev, Konstantin S and Suvorov, Roman",
  abstract = "Single-shot grid-based path finding is an important problem with
              the applications in robotics, video games etc. Typically in AI
              community heuristic search methods (based on A* and its
              variations) are used to solve it. In this work we present the
              results of preliminary studies on how neural networks can be
              utilized to path planning on square grids, e.g. how well they can
              cope with path finding tasks by themselves within the well-known
              reinforcement problem statement. Conducted experiments show that
              the agent using neural Q-learning algorithm robustly learns to
              achieve the goal on small maps and demonstrate promising results
              on the maps have ben never seen by him before.",
  journal  = "Procedia Comput. Sci.",
  volume   =  123,
  pages    = "347--353",
  month    =  jan,
  year     =  2018,
  keywords = "path planning; reinforcement learning; neural networks;
              Q-learning; convolution networks; Q-network"
}

@ARTICLE{Schmidhuber2015-ym,
  title         = "On Learning to Think: Algorithmic Information Theory for
                   Novel Combinations of Reinforcement Learning Controllers and
                   Recurrent Neural World Models",
  author        = "Schmidhuber, Juergen",
  abstract      = "This paper addresses the general problem of reinforcement
                   learning (RL) in partially observable environments. In 2013,
                   our large RL recurrent neural networks (RNNs) learned from
                   scratch to drive simulated cars from high-dimensional video
                   input. However, real brains are more powerful in many ways.
                   In particular, they learn a predictive model of their
                   initially unknown environment, and somehow use it for
                   abstract (e.g., hierarchical) planning and reasoning. Guided
                   by algorithmic information theory, we describe RNN-based AIs
                   (RNNAIs) designed to do the same. Such an RNNAI can be
                   trained on never-ending sequences of tasks, some of them
                   provided by the user, others invented by the RNNAI itself in
                   a curious, playful fashion, to improve its RNN-based world
                   model. Unlike our previous model-building RNN-based RL
                   machines dating back to 1990, the RNNAI learns to actively
                   query its model for abstract reasoning and planning and
                   decision making, essentially ``learning to think.'' The
                   basic ideas of this report can be applied to many other
                   cases where one RNN-like system exploits the algorithmic
                   information content of another. They are taken from a grant
                   proposal submitted in Fall 2014, and also explain concepts
                   such as ``mirror neurons.'' Experimental results will be
                   described in separate papers.",
  month         =  nov,
  year          =  2015,
  archivePrefix = "arXiv",
  primaryClass  = "cs.AI",
  eprint        = "1511.09249"
}

@ARTICLE{Arulkumaran2017-bm,
  title         = "A Brief Survey of Deep Reinforcement Learning",
  author        = "Arulkumaran, Kai and Deisenroth, Marc Peter and Brundage,
                   Miles and Bharath, Anil Anthony",
  abstract      = "Deep reinforcement learning is poised to revolutionise the
                   field of AI and represents a step towards building
                   autonomous systems with a higher level understanding of the
                   visual world. Currently, deep learning is enabling
                   reinforcement learning to scale to problems that were
                   previously intractable, such as learning to play video games
                   directly from pixels. Deep reinforcement learning algorithms
                   are also applied to robotics, allowing control policies for
                   robots to be learned directly from camera inputs in the real
                   world. In this survey, we begin with an introduction to the
                   general field of reinforcement learning, then progress to
                   the main streams of value-based and policy-based methods.
                   Our survey will cover central algorithms in deep
                   reinforcement learning, including the deep $Q$-network,
                   trust region policy optimisation, and asynchronous advantage
                   actor-critic. In parallel, we highlight the unique
                   advantages of deep neural networks, focusing on visual
                   understanding via reinforcement learning. To conclude, we
                   describe several current areas of research within the field.",
  month         =  aug,
  year          =  2017,
  archivePrefix = "arXiv",
  primaryClass  = "cs.LG",
  eprint        = "1708.05866"
}

@ARTICLE{Madl2015-wd,
  title    = "Computational cognitive models of spatial memory in navigation
              space: a review",
  author   = "Madl, Tamas and Chen, Ke and Montaldi, Daniela and Trappl, Robert",
  abstract = "Spatial memory refers to the part of the memory system that
              encodes, stores, recognizes and recalls spatial information about
              the environment and the agent's orientation within it. Such
              information is required to be able to navigate to goal locations,
              and is vitally important for any embodied agent, or model
              thereof, for reaching goals in a spatially extended environment.
              In this paper, a number of computationally implemented cognitive
              models of spatial memory are reviewed and compared. Three
              categories of models are considered: symbolic models, neural
              network models, and models that are part of a systems-level
              cognitive architecture. Representative models from each category
              are described and compared in a number of dimensions along which
              simulation models can differ (level of modeling, types of
              representation, structural accuracy, generality and abstraction,
              environment complexity), including their possible mapping to the
              underlying neural substrate. Neural mappings are rarely
              explicated in the context of behaviorally validated models, but
              they could be useful to cognitive modeling research by providing
              a new approach for investigating a model's plausibility. Finally,
              suggested experimental neuroscience methods are described for
              verifying the biological plausibility of computational cognitive
              models of spatial memory, and open questions for the field of
              spatial memory modeling are outlined.",
  journal  = "Neural Netw.",
  volume   =  65,
  pages    = "18--43",
  month    =  may,
  year     =  2015,
  keywords = "Computational cognitive modeling; Spatial memory models",
  language = "en"
}

@ARTICLE{Ha2018-sa,
  title     = "World Models",
  author    = "Ha, David and Schmidhuber, J{\"u}rgen",
  abstract  = "We explore building generative neural network models of popular
               reinforcement learning environments. Our world model can be
               trained quickly in an unsupervised manner to learn a compressed
               spatial and temporal representation of the environment. By using
               features extracted from the world model as inputs to an agent,
               we can train a very compact and simple policy that can solve the
               required task. We can even train our agent entirely inside of
               its own hallucinated dream generated by its world model, and
               transfer this policy back into the actual environment. An
               interactive version of this article is available at
               worldmodels.github.io.",
  publisher = "Zenodo",
  year      =  2018
}

@ARTICLE{Stoianov2018-og,
  title    = "Model-based spatial navigation in the hippocampus-ventral
              striatum circuit: A computational analysis",
  author   = "Stoianov, Ivilin Peev and Pennartz, Cyriel M A and Lansink,
              Carien S and Pezzulo, Giovani",
  abstract = "While the neurobiology of simple and habitual choices is
              relatively well known, our current understanding of goal-directed
              choices and planning in the brain is still limited. Theoretical
              work suggests that goal-directed computations can be productively
              associated to model-based (reinforcement learning) computations,
              yet a detailed mapping between computational processes and
              neuronal circuits remains to be fully established. Here we report
              a computational analysis that aligns Bayesian nonparametrics and
              model-based reinforcement learning (MB-RL) to the functioning of
              the hippocampus (HC) and the ventral striatum (vStr)-a neuronal
              circuit that increasingly recognized to be an appropriate model
              system to understand goal-directed (spatial) decisions and
              planning mechanisms in the brain. We test the MB-RL agent in a
              contextual conditioning task that depends on intact hippocampus
              and ventral striatal (shell) function and show that it solves the
              task while showing key behavioral and neuronal signatures of the
              HC-vStr circuit. Our simulations also explore the benefits of
              biological forms of look-ahead prediction (forward sweeps) during
              both learning and control. This article thus contributes to fill
              the gap between our current understanding of computational
              algorithms and biological realizations of (model-based)
              reinforcement learning.",
  journal  = "PLoS Comput. Biol.",
  volume   =  14,
  number   =  9,
  pages    = "e1006316",
  month    =  sep,
  year     =  2018,
  language = "en"
}

@ARTICLE{Frank2000-xi,
  title    = "Trajectory encoding in the hippocampus and entorhinal cortex",
  author   = "Frank, L M and Brown, E N and Wilson, M",
  abstract = "We recorded from single neurons in the hippocampus and entorhinal
              cortex (EC) of rats to investigate the role of these structures
              in navigation and memory representation. Our results revealed two
              novel phenomena: first, many cells in CA1 and the EC fired at
              significantly different rates when the animal was in the same
              position depending on where the animal had come from or where it
              was going. Second, cells in deep layers of the EC, the targets of
              hippocampal outputs, appeared to represent the similarities
              between locations on spatially distinct trajectories through the
              environment. Our findings suggest that the hippocampus represents
              the animal's position in the context of a trajectory through
              space and that the EC represents regularities across different
              trajectories that could allow for generalization across
              experiences.",
  journal  = "Neuron",
  volume   =  27,
  number   =  1,
  pages    = "169--178",
  month    =  jul,
  year     =  2000,
  keywords = "Non-programmatic",
  language = "en"
}

@ARTICLE{Trullier1997-gt,
  title    = "Biologically based artificial navigation systems: review and
              prospects",
  author   = "Trullier, O and Wiener, S I and Berthoz, A and Meyer, J A",
  abstract = "Diverse theories of animal navigation aim at explaining how to
              determine and maintain a course from one place to another in the
              environment, although each presents a particular perspective with
              its own terminologies. These vocabularies sometimes overlap, but
              unfortunately with different meanings. This paper attempts to
              define precisely the existing concepts and terminologies, so as
              to describe comprehensively the different theories and models
              within the same unifying framework. We present navigation
              strategies within a four-level hierarchical framework based upon
              levels of complexity of required processing (Guidance, Place
              recognition-triggered Response, Topological navigation, Metric
              navigation). This classification is based upon what information
              is perceived, represented and processed. It contrasts with common
              distinctions based upon the availability of certain sensors or
              cues and rather stresses the information structure and content of
              central processors. We then review computational models of animal
              navigation, i.e. of animats. These are introduced along with the
              underlying conceptual basis in biological data drawn from
              behavioral and physiological experiments, with emphasis on
              theories of ``spatial cognitive maps''. The goal is to aid in
              deriving algorithms based upon insights into these processes,
              algorithms that can be useful both for psychobiologists and
              roboticists. The main observation is, however, that despite the
              fact that all reviewed models claim to have biological
              inspiration and that some of them explicitly use ``Cognitive
              Map''-like mechanisms, they correspond to different levels of our
              proposed hierarchy and that none of them exhibits the main
              capabilities of real ``Cognitive Maps''--in Tolman's sense--that
              is, a robust capacity for detour and shortcut behaviors.",
  journal  = "Prog. Neurobiol.",
  volume   =  51,
  number   =  5,
  pages    = "483--544",
  month    =  apr,
  year     =  1997,
  language = "en"
}

@ARTICLE{Olafsdottir2018-on,
  title    = "The Role of Hippocampal Replay in Memory and Planning",
  author   = "{\'O}lafsd{\'o}ttir, H Freyja and Bush, Daniel and Barry, Caswell",
  abstract = "The mammalian hippocampus is important for normal memory
              function, particularly memory for places and events. Place cells,
              neurons within the hippocampus that have spatial receptive
              fields, represent information about an animal's position. During
              periods of rest, but also during active task engagement, place
              cells spontaneously recapitulate past trajectories. Such 'replay'
              has been proposed as a mechanism necessary for a range of
              neurobiological functions, including systems memory
              consolidation, recall and spatial working memory, navigational
              planning, and reinforcement learning. Focusing mainly, but not
              exclusively, on work conducted in rodents, we describe the
              methodologies used to analyse replay and review evidence for its
              putative roles. We identify outstanding questions as well as
              apparent inconsistencies in existing data, making suggestions as
              to how these might be resolved. In particular, we find support
              for the involvement of replay in disparate processes, including
              the maintenance of hippocampal memories and decision making. We
              propose that the function of replay changes dynamically according
              to task demands placed on an organism and its current level of
              arousal.",
  journal  = "Curr. Biol.",
  volume   =  28,
  number   =  1,
  pages    = "R37--R50",
  month    =  jan,
  year     =  2018,
  language = "en"
}

@ARTICLE{Stella2019-ap,
  title     = "Hippocampal Reactivation of Random Trajectories Resembling
               Brownian Diffusion",
  author    = "Stella, Federico and Baracskay, Peter and O'Neill, Joseph and
               Csicsvari, Jozsef",
  abstract  = "SummaryHippocampal activity patterns representing movement
               trajectories are reactivated in immobility and sleep periods, a
               process associated with memory recall, consolidation, and
               decision making. It is thought that only fixed, behaviorally
               relevant patterns can be reactivated, which are stored across
               hippocampal synaptic connections. To test whether some
               generalized rules govern reactivation, we examined trajectory
               reactivation following non-stereotypical exploration of familiar
               open-field environments. We found that random trajectories of
               varying lengths and timescales were reactivated, resembling that
               of Brownian motion of particles. The animals' behavioral
               trajectory did not follow Brownian diffusion demonstrating that
               the exact behavioral experience is not reactivated. Therefore,
               hippocampal circuits are able to generate random trajectories of
               any recently active map by following diffusion dynamics. This
               ability of hippocampal circuits to generate representations of
               all behavioral outcome combinations, experienced or not, may
               underlie a wide variety of hippocampal-dependent cognitive
               functions such as learning, generalization, and planning.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  0,
  number    =  0,
  month     =  feb,
  year      =  2019,
  language  = "en"
}

@BOOK{Pfeifer2006-sa,
  title     = "How the Body Shapes the Way We Think: A New View of Intelligence",
  author    = "Pfeifer, Rolf and Bongard, Josh",
  abstract  = "An exploration of embodied intelligence and its implications
               points toward a theory of intelligence in general; with case
               studies of intelligent systems in ubiquitous computing, business
               and management, human memory, and robotics.How could the body
               influence our thinking when it seems obvious that the brain
               controls the body? In How the Body Shapes the Way We Think, Rolf
               Pfeifer and Josh Bongard demonstrate that thought is not
               independent of the body but is tightly constrained, and at the
               same time enabled, by it. They argue that the kinds of thoughts
               we are capable of have their foundation in our embodiment---in
               our morphology and the material properties of our bodies.This
               crucial notion of embodiment underlies fundamental changes in
               the field of artificial intelligence over the past two decades,
               and Pfeifer and Bongard use the basic methodology of artificial
               intelligence---``understanding by building''---to describe their
               insights. If we understand how to design and build intelligent
               systems, they reason, we will better understand intelligence in
               general. In accessible, nontechnical language, and using many
               examples, they introduce the basic concepts by building on
               recent developments in robotics, biology, neuroscience, and
               psychology to outline a possible theory of intelligence. They
               illustrate applications of such a theory in ubiquitous
               computing, business and management, and the psychology of human
               memory. Embodied intelligence, as described by Pfeifer and
               Bongard, has important implications for our understanding of
               both natural and artificial intelligence.",
  publisher = "MIT Press",
  month     =  oct,
  year      =  2006,
  keywords  = "books;Books",
  language  = "en"
}

@ARTICLE{Stephenson-Jones2016-wq,
  title    = "A basal ganglia circuit for evaluating action outcomes",
  author   = "Stephenson-Jones, Marcus and Yu, Kai and Ahrens, Sandra and
              Tucciarone, Jason M and van Huijstee, Aile N and Mejia, Luis A
              and Penzo, Mario A and Tai, Lung-Hao and Wilbrecht, Linda and Li,
              Bo",
  abstract = "The basal ganglia, a group of subcortical nuclei, play a crucial
              role in decision-making by selecting actions and evaluating their
              outcomes. While much is known about the function of the basal
              ganglia circuitry in selection, how these nuclei contribute to
              outcome evaluation is less clear. Here we show that neurons in
              the habenula-projecting globus pallidus (GPh) in mice are
              essential for evaluating action outcomes and are regulated by a
              specific set of inputs from the basal ganglia. We find in a
              classical conditioning task that individual mouse GPh neurons
              bidirectionally encode whether an outcome is better or worse than
              expected. Mimicking these evaluation signals with optogenetic
              inhibition or excitation is sufficient to reinforce or discourage
              actions in a decision-making task. Moreover, cell-type-specific
              synaptic manipulations reveal that the inhibitory and excitatory
              inputs to the GPh are necessary for mice to appropriately
              evaluate positive and negative feedback, respectively. Finally,
              using rabies-virus-assisted monosynaptic tracing, we show that
              the GPh is embedded in a basal ganglia circuit wherein it
              receives inhibitory input from both striosomal and matrix
              compartments of the striatum, and excitatory input from the
              'limbic' regions of the subthalamic nucleus. Our results provide
              evidence that information about the selection and evaluation of
              actions is channelled through distinct sets of basal ganglia
              circuits, with the GPh representing a key locus in which
              information of opposing valence is integrated to determine
              whether action outcomes are better or worse than expected.",
  journal  = "Nature",
  volume   =  539,
  number   =  7628,
  pages    = "289--293",
  month    =  nov,
  year     =  2016,
  language = "en"
}

@ARTICLE{Rolls2004-wu,
  title    = "The functions of the orbitofrontal cortex",
  author   = "Rolls, Edmund T",
  abstract = "The orbitofrontal cortex contains the secondary taste cortex, in
              which the reward value of taste is represented. It also contains
              the secondary and tertiary olfactory cortical areas, in which
              information about the identity and also about the reward value of
              odours is represented. The orbitofrontal cortex also receives
              information about the sight of objects from the temporal lobe
              cortical visual areas, and neurons in it learn and reverse the
              visual stimulus to which they respond when the association of the
              visual stimulus with a primary reinforcing stimulus (such as
              taste) is reversed. This is an example of stimulus-reinforcement
              association learning, and is a type of stimulus-stimulus
              association learning. More generally, the stimulus might be a
              visual or olfactory stimulus, and the primary (unlearned)
              positive or negative reinforcer a taste or touch. A somatosensory
              input is revealed by neurons that respond to the texture of food
              in the mouth, including a population that responds to the mouth
              feel of fat. In complementary neuroimaging studies in humans, it
              is being found that areas of the orbitofrontal cortex are
              activated by pleasant touch, by painful touch, by taste, by
              smell, and by more abstract reinforcers such as winning or losing
              money. Damage to the orbitofrontal cortex can impair the learning
              and reversal of stimulus-reinforcement associations, and thus the
              correction of behavioural responses when there are no longer
              appropriate because previous reinforcement contingencies change.
              The information which reaches the orbitofrontal cortex for these
              functions includes information about faces, and damage to the
              orbitofrontal cortex can impair face (and voice) expression
              identification. This evidence thus shows that the orbitofrontal
              cortex is involved in decoding and representing some primary
              reinforcers such as taste and touch; in learning and reversing
              associations of visual and other stimuli to these primary
              reinforcers; and in controlling and correcting reward-related and
              punishment-related behavior, and thus in emotion. The approach
              described here is aimed at providing a fundamental understanding
              of how the orbitofrontal cortex actually functions, and thus in
              how it is involved in motivational behavior such as feeding and
              drinking, in emotional behavior, and in social behavior.",
  journal  = "Brain Cogn.",
  volume   =  55,
  number   =  1,
  pages    = "11--29",
  month    =  jun,
  year     =  2004,
  language = "en"
}

@ARTICLE{Ernst2005-xn,
  title    = "Neurobiology of decision making: a selective review from a
              neurocognitive and clinical perspective",
  author   = "Ernst, Monique and Paulus, Martin P",
  abstract = "We present a temporal map of key processes that occur during
              decision making, which consists of three stages: 1) formation of
              preferences among options, 2) selection and execution of an
              action, and 3) experience or evaluation of an outcome. This
              framework can be used to integrate findings of traditional choice
              psychology, neuropsychology, brain lesion studies, and functional
              neuroimaging. Decision making is distributed across various brain
              centers, which are differentially active across these stages of
              decision making. This approach can be used to follow
              developmental trajectories of the different stages of decision
              making and to identify unique deficits associated with distinct
              psychiatric disorders.",
  journal  = "Biol. Psychiatry",
  volume   =  58,
  number   =  8,
  pages    = "597--604",
  month    =  oct,
  year     =  2005,
  language = "en"
}

@ARTICLE{Wallis2011-jp,
  title    = "Cross-species studies of orbitofrontal cortex and value-based
              decision-making",
  author   = "Wallis, Jonathan D",
  abstract = "Recent work has emphasized the role that orbitofrontal cortex
              (OFC) has in value-based decision-making. However, it is also
              clear that a number of discrepancies have arisen when comparing
              the findings from animal models to those from humans. Here, we
              examine several possibilities that might explain these
              discrepancies, including anatomical difference between species,
              the behavioral tasks used to probe decision-making and the
              methodologies used to assess neural function. Understanding how
              these differences affect the interpretation of experimental
              results will help us to better integrate future results from
              animal models. This will enable us to fully realize the benefits
              of using multiple approaches to understand OFC function.",
  journal  = "Nat. Neurosci.",
  volume   =  15,
  number   =  1,
  pages    = "13--19",
  month    =  nov,
  year     =  2011,
  language = "en"
}


@ARTICLE{Jones2012-oh,
  title    = "Orbitofrontal cortex supports behavior and learning using
              inferred but not cached values",
  author   = "Jones, Joshua L and Esber, Guillem R and McDannald, Michael A and
              Gruber, Aaron J and Hernandez, Alex and Mirenzi, Aaron and
              Schoenbaum, Geoffrey",
  abstract = "Computational and learning theory models propose that behavioral
              control reflects value that is both cached (computed and stored
              during previous experience) and inferred (estimated on the fly on
              the basis of knowledge of the causal structure of the
              environment). The latter is thought to depend on the
              orbitofrontal cortex. Yet some accounts propose that the
              orbitofrontal cortex contributes to behavior by signaling
              ``economic'' value, regardless of the associative basis of the
              information. We found that the orbitofrontal cortex is critical
              for both value-based behavior and learning when value must be
              inferred but not when a cached value is sufficient. The
              orbitofrontal cortex is thus fundamental for accessing
              model-based representations of the environment to compute value
              rather than for signaling value per se.",
  journal  = "Science",
  volume   =  338,
  number   =  6109,
  pages    = "953--956",
  month    =  nov,
  year     =  2012,
  language = "en"
}

@ARTICLE{Gershman2014-ll,
  title    = "Retrospective revaluation in sequential decision making: a tale
              of two systems",
  author   = "Gershman, Samuel J and Markman, Arthur B and Otto, A Ross",
  abstract = "Recent computational theories of decision making in humans and
              animals have portrayed 2 systems locked in a battle for control
              of behavior. One system--variously termed model-free or
              habitual--favors actions that have previously led to reward,
              whereas a second--called the model-based or goal-directed
              system--favors actions that causally lead to reward according to
              the agent's internal model of the environment. Some evidence
              suggests that control can be shifted between these systems using
              neural or behavioral manipulations, but other evidence suggests
              that the systems are more intertwined than a competitive account
              would imply. In 4 behavioral experiments, using a retrospective
              revaluation design and a cognitive load manipulation, we show
              that human decisions are more consistent with a cooperative
              architecture in which the model-free system controls behavior,
              whereas the model-based system trains the model-free system by
              replaying and simulating experience.",
  journal  = "J. Exp. Psychol. Gen.",
  volume   =  143,
  number   =  1,
  pages    = "182--194",
  month    =  feb,
  year     =  2014,
  language = "en"
}

@ARTICLE{Richard_R_Sutton2015-ot,
  title    = "Reinforcement Learning - An introduction",
  author   = "Richard R. Sutton, Andrew G Burton",
  journal  = "The MIT Press",
  year     =  2015,
  keywords = "books;Books"
}

@ARTICLE{Akam2014-ig,
  title    = "When brains flip coins",
  author   = "Akam, Thomas and Costa, Rui M",
  abstract = "In a recent study in the journal Cell, Tervo et al. (2014) show
              that animals can implement stochastic choice policies in
              environments unfavorable to predictive strategies. The shift
              toward stochastic behavior was driven by noradrenergic signaling
              in the anterior cingulate cortex.",
  journal  = "Neuron",
  volume   =  84,
  number   =  1,
  pages    = "9--11",
  month    =  oct,
  year     =  2014,
  language = "en"
}

@ARTICLE{Tervo2014-uw,
  title    = "Behavioral variability through stochastic choice and its gating
              by anterior cingulate cortex",
  author   = "Tervo, Dougal G R and Proskurin, Mikhail and Manakov, Maxim and
              Kabra, Mayank and Vollmer, Alison and Branson, Kristin and
              Karpova, Alla Y",
  abstract = "Behavioral choices that ignore prior experience promote
              exploration and unpredictability but are seemingly at odds with
              the brain's tendency to use experience to optimize behavioral
              choice. Indeed, when faced with virtual competitors, primates
              resort to strategic counter prediction rather than to stochastic
              choice. Here, we show that rats also use history- and model-based
              strategies when faced with similar competitors but can switch to
              a ``stochastic'' mode when challenged with a competitor that they
              cannot defeat by counter prediction. In this mode, outcomes
              associated with an animal's actions are ignored, and normal
              engagement of anterior cingulate cortex (ACC) is suppressed.
              Using circuit perturbations in transgenic rats, we demonstrate
              that switching between strategic and stochastic behavioral modes
              is controlled by locus coeruleus input into ACC. Our findings
              suggest that, under conditions of uncertainty about environmental
              rules, changes in noradrenergic input alter ACC output and
              prevent erroneous beliefs from guiding decisions, thus enabling
              behavioral variation. PAPERCLIP:",
  journal  = "Cell",
  volume   =  159,
  number   =  1,
  pages    = "21--32",
  month    =  sep,
  year     =  2014,
  language = "en"
}

@ARTICLE{Koechlin2016-yb,
  title    = "Prefrontal executive function and adaptive behavior in complex
              environments",
  author   = "Koechlin, Etienne",
  abstract = "The prefrontal cortex (PFC) subserves higher cognitive abilities
              such as planning, reasoning and creativity. Here we review recent
              findings from both empirical and theoretical studies providing
              new insights about these cognitive abilities and their neural
              underpinnings in the PFC as overcoming key adaptive limitations
              in reinforcement learning. We outline a unified theoretical
              framework describing the PFC function as implementing an
              algorithmic solution approximating statistically optimal, but
              computationally intractable, adaptive processes. The resulting
              PFC functional architecture combines learning, planning,
              reasoning and creativity processes for balancing exploitation and
              exploration behaviors and optimizing behavioral adaptations in
              uncertain, variable and open-ended environments.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  37,
  pages    = "1--6",
  month    =  apr,
  year     =  2016,
  language = "en"
}

@UNPUBLISHED{Zhang2019-bo,
  title    = "A Sequence Learning Model for Decision Making in the Brain",
  author   = "Zhang, Zhewei and Cheng, Huzi and Lin, Zhongqiao and Yang,
              Tianming",
  abstract = "Decision making is often modelled as a competition between
              options. Currently, a great number of popular models to explain
              the accuracy and speed in decision making are based on variations
              of drift diffusion models (DDM), in which the options compete by
              accumulating evidence toward decision bounds. Attractor-based
              recurrent neural networks have been proposed to explain the
              underlying neural mechanism. Yet, it is questionable that either
              the DDM or attractor network is the brain9s general solution for
              decision making. Here, we propose an alternative recurrent neural
              network modeling approach based on gated recurrent units and
              sequence learning. Our network model is trained to learn the
              statistical structure of temporal sequences of sensory events,
              action events, and reward events. We demonstrate its learning
              with a reaction-time version of the weather prediction task
              previously studied in monkey experiments, in which both the
              animals9 behavior and the neuronal responses were consistent with
              the DDM. The network model9s performance is able to reflect the
              accuracy and reaction time pattern of the animals9 choice
              behavior. The analyses of the unit responses in the network
              reveal that they match important experimental findings. Notably,
              we find units encoding the accumulated evidence and the urgency
              signal. We further identify two groups of units based on their
              connection weights to the choice output units. Simulated lesions
              of each group of units produce doubly-dissociable effects on the
              network9s choice and reaction time behavior. Graph analyses
              reveal that these two groups of units belong to one highly
              inter-connected sub-network. Finally, we show that the network is
              capable of making predictions consistent with the predictive
              coding and Bayesian inference framework. Our work offers
              experimentally testable predictions of how decision making is
              achieved in the brain. It provides an approach that may piece
              together experimental findings of decision making, reinforcement
              learning, and predictive coding. In particular, it suggests that
              the DDM may be a manifestation of a more general computational
              mechanism in the brain.",
  journal  = "bioRxiv",
  pages    = "555862",
  month    =  feb,
  year     =  2019,
  language = "en"
}

@ARTICLE{Amemiya2018-ym,
  title    = "Hippocampal {Theta-Gamma} Coupling Reflects {State-Dependent}
              Information Processing in Decision Making",
  author   = "Amemiya, Seiichiro and Redish, A David",
  abstract = "During decision making, hippocampal activity encodes information
              sometimes about present and sometimes about potential future
              plans. The mechanisms underlying this transition remain unknown.
              Building on the evidence that gamma oscillations at different
              frequencies (low gamma [LG], 30-55 Hz; high gamma [HG], 60-90 Hz;
              and epsilon, 100-140 Hz) reflect inputs from different circuits,
              we identified how changes in those frequencies reflect different
              information-processing states. Using a unique noradrenergic
              manipulation by clonidine, which shifted both neural
              representations and gamma states, we found that future
              representations depended on gamma components. These changes were
              identifiable on each cycle of theta as asymmetries in the theta
              cycle, which arose from changes within the ratio of LG and HG
              power and the underlying phases of those gamma rhythms within the
              theta cycle. These changes in asymmetry of the theta cycle
              reflected changes in representations of present and future on
              each theta cycle.",
  journal  = "Cell Rep.",
  volume   =  22,
  number   =  12,
  pages    = "3328--3338",
  month    =  mar,
  year     =  2018,
  keywords = "decision making; gamma; hippocampus; local field potential;
              noradrenaline; norepinephrine; place cell; theta; vicarious trial
              and error",
  language = "en"
}

@ARTICLE{Sweis2018-ep,
  title    = "Mice learn to avoid regret",
  author   = "Sweis, Brian M and Thomas, Mark J and Redish, A David",
  abstract = "Regret can be defined as the subjective experience of recognizing
              that one has made a mistake and that a better alternative could
              have been selected. The experience of regret is thought to carry
              negative utility. This typically takes two distinct forms:
              augmenting immediate postregret valuations to make up for losses,
              and augmenting long-term changes in decision-making strategies to
              avoid future instances of regret altogether. While the short-term
              changes in valuation have been studied in human psychology,
              economics, neuroscience, and even recently in nonhuman-primate
              and rodent neurophysiology, the latter long-term process has
              received far less attention, with no reports of regret avoidance
              in nonhuman decision-making paradigms. We trained 31 mice in a
              novel variant of the Restaurant Row economic decision-making
              task, in which mice make decisions of whether to spend time from
              a limited budget to achieve food rewards of varying costs
              (delays). Importantly, we tested mice longitudinally for 70
              consecutive days, during which the task provided their only
              source of food. Thus, decision strategies were interdependent
              across both trials and days. We separated principal commitment
              decisions from secondary reevaluation decisions across space and
              time and found evidence for regret-like behaviors following
              change-of-mind decisions that corrected prior economically
              disadvantageous choices. Immediately following change-of-mind
              events, subsequent decisions appeared to make up for lost effort
              by altering willingness to wait, decision speed, and pellet
              consumption speed, consistent with past reports of regret in
              rodents. As mice were exposed to an increasingly reward-scarce
              environment, we found they adapted and refined distinct economic
              decision-making strategies over the course of weeks to maximize
              reinforcement rate. However, we also found that even without
              changes in reinforcement rate, mice transitioned from an early
              strategy rooted in foraging to a strategy rooted in deliberation
              and planning that prevented future regret-inducing change-of-mind
              episodes from occurring. These data suggest that mice are
              learning to avoid future regret, independent of and separate from
              reinforcement rate maximization.",
  journal  = "PLoS Biol.",
  volume   =  16,
  number   =  6,
  pages    = "e2005853",
  month    =  jun,
  year     =  2018,
  language = "en"
}

@ARTICLE{Knierim2009-ze,
  title    = "Imagining the possibilities: ripples, routes, and reactivation",
  author   = "Knierim, James J",
  abstract = "Hippocampal place cells fire selectively when a rat occupies a
              particular location. Under certain conditions, the cells briefly
              represent trajectories along locations away from the rat's
              current location. New results lend important insight into this
              phenomenon and demonstrate spatiotemporally coherent, cognitive
              representations that are independent of current sensory input.",
  journal  = "Neuron",
  volume   =  63,
  number   =  4,
  pages    = "421--423",
  month    =  aug,
  year     =  2009,
  language = "en"
}

@ARTICLE{Deshmukh2013-nc,
  title    = "Influence of local objects on hippocampal representations:
              Landmark vectors and memory",
  author   = "Deshmukh, Sachin S and Knierim, James J",
  abstract = "The hippocampus is thought to represent nonspatial information in
              the context of spatial information. An animal can derive both
              spatial information as well as nonspatial information from the
              objects (landmarks) it encounters as it moves around in an
              environment. In this article, correlates of both object-derived
              spatial as well as nonspatial information in the hippocampus of
              rats foraging in the presence of objects are demonstrated. A new
              form of CA1 place cells, called landmark-vector cells, that
              encode spatial locations as a vector relationship to local
              landmarks is described. Such landmark vector relationships can be
              dynamically encoded. Of the 26 CA1 neurons that developed new
              fields in the course of a day's recording sessions, in eight
              cases, the new fields were located at a similar distance and
              direction from a landmark as the initial field was located
              relative to a different landmark. In addition, object-location
              memory in the hippocampus is also described. When objects were
              removed from an environment or moved to new locations, a small
              number of neurons in CA1 and CA3 increased firing at the
              locations where the objects used to be. In some neurons, this
              increase occurred only in one location, indicating object + place
              conjunctive memory; in other neurons, the increase in firing was
              seen at multiple locations where an object used to be. Taken
              together, these results demonstrate that the spatially restricted
              firing of hippocampal neurons encode multiple types of
              information regarding the relationship between an animal's
              location and the location of objects in its environment.",
  journal  = "Hippocampus",
  volume   =  23,
  number   =  4,
  pages    = "253--267",
  month    =  apr,
  year     =  2013,
  keywords = "boundary vector cell; hippocampus; landmark; memory; objects",
  language = "en"
}

@ARTICLE{Knierim_James_J2014-wd,
  title     = "Functional correlates of the lateral and medial entorhinal
               cortex: objects, path integration and local--global reference
               frames",
  author    = "{Knierim James J.} and {Neunuebel Joshua P.} and {Deshmukh
               Sachin S.}",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "Royal Society",
  volume    =  369,
  number    =  1635,
  pages     = "20130369",
  month     =  feb,
  year      =  2014
}

@ARTICLE{Knierim2016-cx,
  title    = "Tracking the flow of hippocampal computation: Pattern separation,
              pattern completion, and attractor dynamics",
  author   = "Knierim, James J and Neunuebel, Joshua P",
  abstract = "Classic computational theories of the mnemonic functions of the
              hippocampus ascribe the processes of pattern separation to the
              dentate gyrus (DG) and pattern completion to the CA3 region.
              Until the last decade, the large majority of single-unit studies
              of the hippocampus in behaving animals were from the CA1 region.
              The lack of data from the DG, CA3, and the entorhinal inputs to
              the hippocampus severely hampered the ability to test these
              theories with neurophysiological techniques. The past ten years
              have seen a major increase in the recordings from the CA3 region
              and the medial entorhinal cortex (MEC), with an increasing (but
              still limited) number of experiments from the lateral entorhinal
              cortex (LEC) and DG. This paper reviews a series of studies in a
              local-global cue mismatch (double-rotation) experiment in which
              recordings were made from cells in the anterior thalamus, MEC,
              LEC, DG, CA3, and CA1 regions. Compared to the standard cue
              environment, the change in the DG representation of the
              cue-mismatch environment was greater than the changes in its
              entorhinal inputs, providing support for the theory of pattern
              separation in the DG. In contrast, the change in the CA3
              representation of the cue-mismatch environment was less than the
              changes in its entorhinal and DG inputs, providing support for a
              pattern completion/error correction function of CA3. The results
              are interpreted in terms of continuous attractor network models
              of the hippocampus and the relationship of these models to
              pattern separation and pattern completion theories. Whereas DG
              may perform an automatic pattern separation function, the
              attractor dynamics of CA3 allow it to perform a pattern
              separation or pattern completion function, depending on the
              nature of its inputs and the relative strength of the internal
              attractor dynamics.",
  journal  = "Neurobiol. Learn. Mem.",
  volume   =  129,
  pages    = "38--49",
  month    =  mar,
  year     =  2016,
  keywords = "Attractors; CA3; Dentate gyrus; Pattern completion; Pattern
              separation; Place cells",
  language = "en"
}

@ARTICLE{Davidson2009-cn,
  title     = "Hippocampal replay of extended experience",
  author    = "Davidson, Thomas J and Kloosterman, Fabian and Wilson, Matthew A",
  abstract  = "During pauses in exploration, ensembles of place cells in the
               rat hippocampus re-express firing sequences corresponding to
               recent spatial experience. Such ``replay'' co-occurs with ripple
               events: short-lasting (approximately 50-120 ms), high-frequency
               (approximately 200 Hz) oscillations that are associated with
               increased hippocampal-cortical communication. In previous
               studies, rats exploring small environments showed replay
               anchored to the rat's current location and compressed in time
               into a single ripple event. Here, we show, using a neural
               decoding approach, that firing sequences corresponding to long
               runs through a large environment are replayed with high fidelity
               and that such replay can begin at remote locations on the track.
               Extended replay proceeds at a characteristic virtual speed of
               approximately 8 m/s and remains coherent across trains of ripple
               events. These results suggest that extended replay is composed
               of chains of shorter subsequences, which may reflect a strategy
               for the storage and flexible expression of memories of prolonged
               experience.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  63,
  number    =  4,
  pages     = "497--507",
  month     =  aug,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Foster2000-uu,
  title     = "A model of hippocampally dependent navigation, using the
               temporal difference learning rule",
  author    = "Foster, D J and Morris, R G and Dayan, P",
  abstract  = "This paper presents a model of how hippocampal place cells might
               be used for spatial navigation in two watermaze tasks: the
               standard reference memory task and a delayed matching-to-place
               task. In the reference memory task, the escape platform occupies
               a single location and rats gradually learn relatively direct
               paths to the goal over the course of days, in each of which they
               perform a fixed number of trials. In the delayed
               matching-to-place task, the escape platform occupies a novel
               location on each day, and rats gradually acquire one-trial
               learning, i.e., direct paths on the second trial of each day.
               The model uses a local, incremental, and statistically efficient
               connectionist algorithm called temporal difference learning in
               two distinct components. The first is a reinforcement-based
               ``actor-critic'' network that is a general model of classical
               and instrumental conditioning. In this case, it is applied to
               navigation, using place cells to provide information about
               state. By itself, the actor-critic can learn the reference
               memory task, but this learning is inflexible to changes to the
               platform location. We argue that one-trial learning in the
               delayed matching-to-place task demands a goal-independent
               representation of space. This is provided by the second
               component of the model: a network that uses temporal difference
               learning and self-motion information to acquire consistent
               spatial coordinates in the environment. Each component of the
               model is necessary at a different stage of the task; the
               actor-critic provides a way of transferring control to the
               component that performs best. The model successfully captures
               gradual acquisition in both tasks, and, in particular, the
               ultimate development of one-trial learning in the delayed
               matching-to-place task. Place cells report a form of stable,
               allocentric information that is well-suited to the various kinds
               of learning in the model.",
  journal   = "Hippocampus",
  publisher = "Wiley Online Library",
  volume    =  10,
  number    =  1,
  pages     = "1--16",
  year      =  2000,
  language  = "en"
}

@ARTICLE{Jacob2019-iv,
  title     = "Path integration maintains spatial periodicity of grid cell
               firing in a {1D} circular track",
  author    = "Jacob, Pierre-Yves and Capitano, Fabrizio and Poucet, Bruno and
               Save, Etienne and Sargolini, Francesca",
  abstract  = "Entorhinal grid cells are thought to provide a 2D spatial metric
               of the environment. In this study we demonstrate that in a
               familiar 1D circular track (i.e., a continuous space) grid cells
               display a novel 1D equidistant firing pattern based on
               integrated distance rather than travelled distance or time. In
               addition, field spacing is increased compared to a 2D open
               field, probably due to a reduced access to the visual cue in the
               track. This metrical modification is accompanied by a change in
               LFP theta oscillations, but no change in intrinsic grid cell
               rhythmicity, or firing activity of entorhinal speed and
               head-direction cells. These results suggest that in a 1D
               circular space grid cell spatial selectivity is shaped by path
               integration processes, while grid scale relies on external
               information.",
  journal   = "Nat. Commun.",
  publisher = "Nature Publishing Group",
  volume    =  10,
  number    =  1,
  pages     = "840",
  month     =  feb,
  year      =  2019,
  language  = "en"
}

@ARTICLE{Minderer2019-kz,
  title    = "The Spatial Structure of Neural Encoding in Mouse Posterior
              Cortex during Navigation",
  author   = "Minderer, Matthias and Brown, Kristen D and Harvey, Christopher D",
  abstract = "Navigation engages many cortical areas, including visual,
              parietal, and retrosplenial cortices. These regions have been
              mapped anatomically and with sensory stimuli and studied
              individually during behavior. Here, we investigated how
              behaviorally driven neural activity is distributed and combined
              across these regions. We performed dense sampling of
              single-neuron activity across the mouse posterior cortex and
              developed unbiased methods to relate neural activity to behavior
              and anatomical space. Most parts of the posterior cortex encoded
              most behavior-related features. However, the relative strength
              with which features were encoded varied across space. Therefore,
              the posterior cortex could be divided into discriminable areas
              based solely on behaviorally relevant neural activity, revealing
              functional structure in association regions. Multimodal
              representations combining sensory and movement signals were
              strongest in posterior parietal cortex, where gradients of
              single-feature representations spatially overlapped. We propose
              that encoding of behavioral features is not constrained by
              retinotopic borders and instead varies smoothly over space within
              association regions.",
  journal  = "Neuron",
  month    =  feb,
  year     =  2019,
  keywords = "calcium imaging; cortical architecture; mouse cortex; navigation;
              optogenetics; parietal cortex; virtual reality; visual cortex",
  language = "en"
}

@ARTICLE{Stachenfeld2017-yp,
  title    = "The hippocampus as a predictive map",
  author   = "Stachenfeld, Kimberly L and Botvinick, Matthew M and Gershman,
              Samuel J",
  abstract = "A cognitive map has long been the dominant metaphor for
              hippocampal function, embracing the idea that place cells encode
              a geometric representation of space. However, evidence for
              predictive coding, reward sensitivity and policy dependence in
              place cells suggests that the representation is not purely
              spatial. We approach this puzzle from a reinforcement learning
              perspective: what kind of spatial representation is most useful
              for maximizing future reward? We show that the answer takes the
              form of a predictive representation. This representation captures
              many aspects of place cell responses that fall outside the
              traditional view of a cognitive map. Furthermore, we argue that
              entorhinal grid cells encode a low-dimensionality basis set for
              the predictive representation, useful for suppressing noise in
              predictions and extracting multiscale structure for hierarchical
              planning.",
  journal  = "Nat. Neurosci.",
  volume   =  20,
  number   =  11,
  pages    = "1643--1653",
  month    =  nov,
  year     =  2017,
  language = "en"
}

@ARTICLE{Foster2012-lf,
  title     = "Sequence learning and the role of the hippocampus in rodent
               navigation",
  author    = "Foster, David J and Knierim, James J",
  abstract  = "The hippocampus has long been associated with navigation and
               spatial representations, but it has been difficult to link
               directly the neurophysiological correlates of hippocampal place
               cells with navigational planning and action. In recent years,
               large-scale population recordings of place cells have revealed
               that spatial sequences are stored and activated in ways that may
               support navigational strategies. Plasticity mechanisms allow the
               hippocampus to store learned sequences of locations that may
               allow predictions of future locations based on past experience.
               These sequences can also be activated during navigational
               behavior in ways that may allow the animal to learn trajectories
               toward goals. Task-dependent alterations in place cell firing
               patterns may reflect the operation of the hippocampus in
               associating locations with navigationally relevant decision
               variables.",
  journal   = "Curr. Opin. Neurobiol.",
  publisher = "Elsevier",
  volume    =  22,
  number    =  2,
  pages     = "294--300",
  month     =  apr,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Whitlock2008-wa,
  title     = "Navigating from hippocampus to parietal cortex",
  author    = "Whitlock, Jonathan R and Sutherland, Robert J and Witter, Menno
               P and Moser, May-Britt and Moser, Edvard I",
  abstract  = "The navigational system of the mammalian cortex comprises a
               number of interacting brain regions. Grid cells in the medial
               entorhinal cortex and place cells in the hippocampus are thought
               to participate in the formation of a dynamic representation of
               the animal's current location, and these cells are presumably
               critical for storing the representation in memory. To traverse
               the environment, animals must be able to translate coordinate
               information from spatial maps in the entorhinal cortex and
               hippocampus into body-centered representations that can be used
               to direct locomotion. How this is done remains an enigma. We
               propose that the posterior parietal cortex is critical for this
               transformation.",
  journal   = "Proc. Natl. Acad. Sci. U. S. A.",
  publisher = "National Acad Sciences",
  volume    =  105,
  number    =  39,
  pages     = "14755--14762",
  month     =  sep,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Chersi2015-qr,
  title    = "The Cognitive Architecture of Spatial Navigation: Hippocampal and
              Striatal Contributions",
  author   = "Chersi, Fabian and Burgess, Neil",
  abstract = "Spatial navigation can serve as a model system in cognitive
              neuroscience, in which specific neural representations, learning
              rules, and control strategies can be inferred from the vast
              experimental literature that exists across many species,
              including humans. Here, we review this literature, focusing on
              the contributions of hippocampal and striatal systems, and
              attempt to outline a minimal cognitive architecture that is
              consistent with the experimental literature and that synthesizes
              previous related computational modeling. The resulting
              architecture includes striatal reinforcement learning based on
              egocentric representations of sensory states and actions,
              incidental Hebbian association of sensory information with
              allocentric state representations in the hippocampus, and
              arbitration of the outputs of both systems based on
              confidence/uncertainty in medial prefrontal cortex. We discuss
              the relationship between this architecture and learning in
              model-free and model-based systems, episodic memory, imagery, and
              planning, including some open questions and directions for
              further experiments.",
  journal  = "Neuron",
  volume   =  88,
  number   =  1,
  pages    = "64--77",
  month    =  oct,
  year     =  2015,
  language = "en"
}

@ARTICLE{Maaswinkel1999-yb,
  title    = "Homing with locale, taxon, and dead reckoning strategies by
              foraging rats: sensory hierarchy in spatial navigation",
  author   = "Maaswinkel, H and Whishaw, I Q",
  abstract = "Studies on foraging rats suggest that they can use visual,
              olfactory, and self-movement cues for spatial guidance, but their
              relative reliance on these different cues is not well understood.
              In the present study, rats left a hidden refuge to search for a
              large food pellet located somewhere on a circular table, and the
              accuracy with which they returned to the refuge with the food
              pellet was measured. Cue use was manipulated by administering
              probe trials from novel locations, blindfolding, moving the home
              cage relative to the table, rotating the table and using
              combinations of these manipulations. When visual cues were
              available and a consistent starting location used, a visual
              strategy dominated performance. When blindfolded, the rats used
              olfactory cues from the surface of the table and from the
              starting hole. When olfactory stimuli were made uninformative, by
              changing the starting hole and rotating the table, the rats still
              homed accurately, suggesting they used self-movement cues. In a
              number of cue combinations, in which cues gave conflicting
              information, performance degraded. The results suggest that rats
              display a hierarchical preference in using visual, olfactory and
              self-movement cues while at the same time being able to reaffirm
              or switch between various cue combinations. The results are
              discussed in relation to ideas concerning the neural basis of
              spatial navigation.",
  journal  = "Behav. Brain Res.",
  volume   =  99,
  number   =  2,
  pages    = "143--152",
  month    =  mar,
  year     =  1999,
  language = "en"
}

@ARTICLE{Cheung2007-hd,
  title     = "Animal navigation: the difficulty of moving in a straight line",
  author    = "Cheung, Allen and Zhang, Shaowu and Stricker, Christian and
               Srinivasan, Mandyam V",
  abstract  = "In principle, there are two strategies for navigating a straight
               course. One is to use an external directional reference and
               continually reorienting with reference to it, while the other is
               to infer body rotations from internal sensory information only.
               We show here that, while the first strategy will enable an
               animal or mobile agent to move arbitrarily far away from its
               starting point, the second strategy will not do so, even after
               an infinite number of steps. Thus, an external directional
               reference-some form of compass-is indispensable for ensuring
               progress away from home. This limitation must place significant
               constraints on the evolution of biological navigation systems.
               Some specific examples are discussed. An important corollary
               arising from the analysis of compassless navigation is that the
               maximum expected displacement represents a robust measure of the
               straightness of a path.",
  journal   = "Biol. Cybern.",
  publisher = "Springer",
  volume    =  97,
  number    =  1,
  pages     = "47--61",
  month     =  jul,
  year      =  2007,
  language  = "en"
}

@ARTICLE{Zhang2014-nb,
  title     = "Spatial representations of place cells in darkness are supported
               by path integration and border information",
  author    = "Zhang, Sijie and Sch{\"o}nfeld, Fabian and Wiskott, Laurenz and
               Manahan-Vaughan, Denise",
  abstract  = "Effective spatial navigation is enabled by reliable reference
               cues that derive from sensory information from the external
               environment, as well as from internal sources such as the
               vestibular system. The integration of information from these
               sources enables dead reckoning in the form of path integration.
               Navigation in the dark is associated with the accumulation of
               errors in terms of perception of allocentric position and this
               may relate to error accumulation in path integration. We
               assessed this by recording from place cells in the dark under
               circumstances where spatial sensory cues were suppressed.
               Spatial information content, spatial coherence, place field
               size, and peak and infield firing rates decreased whereas
               sparsity increased following exploration in the dark compared to
               the light. Nonetheless it was observed that place field
               stability in darkness was sustained by border information in a
               subset of place cells. To examine the impact of encountering the
               environment's border on navigation, we analyzed the trajectory
               and spiking data gathered during navigation in the dark. Our
               data suggest that although error accumulation in path
               integration drives place field drift in darkness, under
               circumstances where border contact is possible, this information
               is integrated to enable retention of spatial representations.",
  journal   = "Front. Behav. Neurosci.",
  publisher = "frontiersin.org",
  volume    =  8,
  pages     = "222",
  month     =  jun,
  year      =  2014,
  keywords  = "CA1; hippocampus; place cells; sensory",
  language  = "en"
}

@ARTICLE{Battaglia2004-ef,
  title     = "Local sensory cues and place cell directionality: additional
               evidence of prospective coding in the hippocampus",
  author    = "Battaglia, Francesco P and Sutherland, Gary R and McNaughton,
               Bruce L",
  abstract  = "In tasks involving goal-directed, stereotyped trajectories on
               uniform tracks, the spatially selective activity of hippocampal
               principal cells depends on the animal's direction of motion.
               Principal cell ensemble activity while the rat moves in opposite
               directions through a given location is typically uncorrelated.
               It is shown here, with data from three experiments, that
               multimodal, local sensory cues can change the directional
               properties of CA1 pyramidal cells, inducing bidirectionality in
               a significant proportion of place cells. For a majority of these
               bidirectional place cells, place field centers in the two
               directions of motion were displaced relative to one another, as
               would be the case if the cells were representing a position in
               space approximately 5-10 cm ahead of the rat or if place cells
               were subject to strong accommodation or inhibition in the latter
               half of their input fields. However, place field density was not
               affected by the presence of local cues, but in the experimental
               condition with the most salient sensory cues, the CA1 population
               vectors in the ``cue-rich'' condition were sparser and changed
               more quickly in space than in the ``cue-poor'' condition. These
               results suggest that ``view-invariant'' object representations
               are projected to the hippocampus from lower cortical areas and
               can have the effect of increasing the correlation of the
               hippocampal input vectors in the two directions, hence
               decreasing the orthogonality of hippocampal output.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  24,
  number    =  19,
  pages     = "4541--4550",
  month     =  may,
  year      =  2004,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Doya1999-jy,
  title     = "What are the computations of the cerebellum, the basal ganglia
               and the cerebral cortex?",
  author    = "Doya, K",
  abstract  = "The classical notion that the cerebellum and the basal ganglia
               are dedicated to motor control is under dispute given increasing
               evidence of their involvement in non-motor functions. Is it then
               impossible to characterize the functions of the cerebellum, the
               basal ganglia and the cerebral cortex in a simplistic manner?
               This paper presents a novel view that their computational roles
               can be characterized not by asking what are the ``goals'' of
               their computation, such as motor or sensory, but by asking what
               are the ``methods'' of their …",
  journal   = "Neural Netw.",
  publisher = "Elsevier",
  year      =  1999
}

@ARTICLE{Killcross2003-ij,
  title     = "Coordination of actions and habits in the medial prefrontal
               cortex of rats",
  author    = "Killcross, Simon and Coutureau, Etienne",
  abstract  = "As animals learn novel behavioural responses, performance is
               maintained by two dissociable influences. Initial responding is
               goal-directed and under voluntary control, but overtraining of
               the same response routine leads to behavioural autonomy and the
               development of habits that are no longer voluntary or
               goal-directed. Rats normally show goal-directed performance
               after limited training, indexed by sensitivity to changes in the
               value of reward, but this sensitivity to goal value is lost with
               extended training. Rats with selective lesions of the prelimbic
               medial prefrontal cortex showed no sensitivity to goal value
               after either limited or extended training, whereas rats with
               lesions of the infralimbic region of the medial prefrontal
               cortex showed the opposite pattern of deficit, a marked
               sensitivity to goal value after both limited and extended
               training. This double-dissociation suggests that the prelimbic
               region is responsible for voluntary response performance and the
               infralimbic cortex mediates the incremental ability of extended
               training to override this goal-directed behaviour.",
  journal   = "Cereb. Cortex",
  publisher = "academic.oup.com",
  volume    =  13,
  number    =  4,
  pages     = "400--408",
  month     =  apr,
  year      =  2003,
  language  = "en"
}

@ARTICLE{Doya2000-wf,
  title    = "Complementary roles of basal ganglia and cerebellum in learning
              and motor control",
  author   = "Doya, K",
  abstract = "The classical notion that the basal ganglia and the cerebellum
              are dedicated to motor control has been challenged by the
              accumulation of evidence revealing their involvement in
              non-motor, cognitive functions. From a computational viewpoint,
              it has been suggested that the cerebellum, the basal ganglia, and
              the cerebral cortex are specialized for different types of
              learning: namely, supervised learning, reinforcement learning and
              unsupervised learning, respectively. This idea of
              learning-oriented specialization is helpful in understanding the
              complementary roles of the basal ganglia and the cerebellum in
              motor control and cognitive functions.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  10,
  number   =  6,
  pages    = "732--739",
  month    =  dec,
  year     =  2000,
  language = "en"
}

@ARTICLE{Botvinick2009-wz,
  title    = "Hierarchically organized behavior and its neural foundations: a
              reinforcement learning perspective",
  author   = "Botvinick, Matthew M and Niv, Yael and Barto, Andrew C",
  abstract = "Research on human and animal behavior has long emphasized its
              hierarchical structure-the divisibility of ongoing behavior into
              discrete tasks, which are comprised of subtask sequences, which
              in turn are built of simple actions. The hierarchical structure
              of behavior has also been of enduring interest within
              neuroscience, where it has been widely considered to reflect
              prefrontal cortical functions. In this paper, we reexamine
              behavioral hierarchy and its neural substrates from the point of
              view of recent developments in computational reinforcement
              learning. Specifically, we consider a set of approaches known
              collectively as hierarchical reinforcement learning, which extend
              the reinforcement learning paradigm by allowing the learning
              agent to aggregate actions into reusable subroutines or skills. A
              close look at the components of hierarchical reinforcement
              learning suggests how they might map onto neural structures, in
              particular regions within the dorsolateral and orbital prefrontal
              cortex. It also suggests specific ways in which hierarchical
              reinforcement learning might provide a complement to existing
              psychological models of hierarchically structured behavior. A
              particularly important question that hierarchical reinforcement
              learning brings to the fore is that of how learning identifies
              new action routines that are likely to provide useful building
              blocks in solving a wide range of future problems. Here and at
              many other points, hierarchical reinforcement learning offers an
              appealing framework for investigating the computational and
              neural underpinnings of hierarchically structured behavior.",
  journal  = "Cognition",
  volume   =  113,
  number   =  3,
  pages    = "262--280",
  month    =  dec,
  year     =  2009,
  language = "en"
}

@ARTICLE{Dezfouli2013-ik,
  title    = "Actions, action sequences and habits: evidence that goal-directed
              and habitual action control are hierarchically organized",
  author   = "Dezfouli, Amir and Balleine, Bernard W",
  abstract = "Behavioral evidence suggests that instrumental conditioning is
              governed by two forms of action control: a goal-directed and a
              habit learning process. Model-based reinforcement learning (RL)
              has been argued to underlie the goal-directed process; however,
              the way in which it interacts with habits and the structure of
              the habitual process has remained unclear. According to a flat
              architecture, the habitual process corresponds to model-free RL,
              and its interaction with the goal-directed process is coordinated
              by an external arbitration mechanism. Alternatively, the
              interaction between these systems has recently been argued to be
              hierarchical, such that the formation of action sequences
              underlies habit learning and a goal-directed process selects
              between goal-directed actions and habitual sequences of actions
              to reach the goal. Here we used a two-stage decision-making task
              to test predictions from these accounts. The hierarchical account
              predicts that, because they are tied to each other as an action
              sequence, selecting a habitual action in the first stage will be
              followed by a habitual action in the second stage, whereas the
              flat account predicts that the statuses of the first and second
              stage actions are independent of each other. We found, based on
              subjects' choices and reaction times, that human subjects
              combined single actions to build action sequences and that the
              formation of such action sequences was sufficient to explain
              habitual actions. Furthermore, based on Bayesian model
              comparison, a family of hierarchical RL models, assuming a
              hierarchical interaction between habit and goal-directed
              processes, provided a better fit of the subjects' behavior than a
              family of flat models. Although these findings do not rule out
              all possible model-free accounts of instrumental conditioning,
              they do show such accounts are not necessary to explain habitual
              actions and provide a new basis for understanding how
              goal-directed and habitual action control interact.",
  journal  = "PLoS Comput. Biol.",
  volume   =  9,
  number   =  12,
  pages    = "e1003364",
  month    =  dec,
  year     =  2013,
  language = "en"
}

@ARTICLE{Pennartz2011-jd,
  title    = "The hippocampal-striatal axis in learning, prediction and
              goal-directed behavior",
  author   = "Pennartz, C M A and Ito, R and Verschure, P F M J and Battaglia,
              F P and Robbins, T W",
  abstract = "The hippocampal formation and striatum subserve declarative and
              procedural memory, respectively. However, experimental evidence
              suggests that the ventral striatum, as opposed to the dorsal
              striatum, does not lend itself to being part of either system.
              Instead, it may constitute a system integrating inputs from the
              amygdala, prefrontal cortex and hippocampus to generate
              motivational, outcome-predicting signals that invigorate
              goal-directed behaviors. Inspired by reinforcement learning
              models, we suggest an alternative scheme for computational
              functions of the striatum. Dorsal and ventral striatum are
              proposed to compute outcome predictions largely in parallel,
              using different types of information as input. The nature of the
              inputs to striatum is furthermore combinatorial, and the
              specificity of predictions transcends the level of scalar value
              signals, incorporating episodic information.",
  journal  = "Trends Neurosci.",
  volume   =  34,
  number   =  10,
  pages    = "548--559",
  month    =  oct,
  year     =  2011,
  language = "en"
}

@ARTICLE{Verschure_Paul_F_M_J2014-hg,
  title     = "The why, what, where, when and how of goal-directed choice:
               neuronal and computational principles",
  author    = "{Verschure Paul F. M. J.} and {Pennartz Cyriel M. A.} and
               {Pezzulo Giovanni}",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "Royal Society",
  volume    =  369,
  number    =  1655,
  pages     = "20130483",
  month     =  nov,
  year      =  2014
}

@ARTICLE{Balleine2015-wp,
  title    = "Hierarchical control of goal-directed action in the
              cortical--basal ganglia network",
  author   = "Balleine, Bernard W and Dezfouli, Amir and Ito, Makato and Doya,
              Kenji",
  abstract = "Goal-directed control depends on constructing a model of the
              world that maps actions onto specific outcomes, allowing choice
              to remain adaptive when the values of outcomes change. In complex
              environments, however, such models can become computationally
              unwieldy. One solution to this problem is to develop a
              hierarchical control structure within which more complex, or
              abstract, actions are built from simpler ones. Here we review
              findings suggesting that the acquisition, evaluation and
              execution of goal-directed actions accords well with predictions
              from hierarchical models. We describe recent evidence that
              hierarchical action control is implemented in a series of
              feedback loops integrating secondary motor areas with the basal
              ganglia and describe how such a structure not only overcomes
              issues of dimensionality, but also helps to explain the formation
              of actions sequences, action chunking and the relationship
              between goal-directed actions and habits.",
  journal  = "Current Opinion in Behavioral Sciences",
  volume   =  5,
  pages    = "1--7",
  month    =  oct,
  year     =  2015
}

@ARTICLE{Mobbs2015-ag,
  title    = "Neuroethological studies of fear, anxiety, and risky
              decision-making in rodents and humans",
  author   = "Mobbs, Dean and Kim, Jeansok J",
  abstract = "Prey are relentlessly faced with a series of survival problems to
              solve. One enduring problem is predation, where the prey's
              answers rely on the complex interaction between actions
              cultivated during its life course and defense reactions passed
              down by descendants. To understand the proximate neural responses
              to analogous threats, affective neuroscientists have favored
              well-controlled associative learning paradigms, yet researchers
              are now creating semi-realistic environments that examine the
              dynamic flow of decision-making and escape calculations that
              mimic the prey's real world choices. In the context of research
              from the field of ethology and behavioral ecology, we review some
              of the recent literature in rodent and human neuroscience and
              discuss how these studies have the potential to provide new
              insights into the behavioral expression, computations, and the
              neural circuits that underlie healthy and pathological fear and
              anxiety.",
  journal  = "Curr Opin Behav Sci",
  volume   =  5,
  pages    = "8--15",
  month    =  oct,
  year     =  2015,
  language = "en"
}

@ARTICLE{Ito2016-tm,
  title    = "The role of the hippocampus in approach-avoidance conflict
              decision-making: Evidence from rodent and human studies",
  author   = "Ito, Rutsuko and Lee, Andy C H",
  abstract = "The hippocampus (HPC) has been traditionally considered to
              subserve mnemonic processing and spatial cognition. Over the past
              decade, however, there has been increasing interest in its
              contributions to processes beyond these two domains. One question
              is whether the HPC plays an important role in decision-making
              under conditions of high approach-avoidance conflict, a scenario
              that arises when a goal stimulus is simultaneously associated
              with reward and punishment. This idea has its origins in rodent
              work conducted in the 1950s and 1960s, and has recently
              experienced a resurgence of interest in the literature. In this
              review, we will first provide an overview of classic rodent
              lesion data that first suggested a role for the HPC in
              approach-avoidance conflict processing and then proceed to
              describe a wide range of more recent evidence from studies
              conducted in rodents and humans. We will demonstrate that there
              is substantial, converging cross-species evidence to support the
              idea that the HPC, in particular the ventral (in
              rodents)/anterior (in humans) portion, contributes to
              approach-avoidance conflict decision making. Furthermore, we
              suggest that the seemingly disparate functions of the HPC (e.g.
              memory, spatial cognition, conflict processing) need not be
              mutually exclusive.",
  journal  = "Behav. Brain Res.",
  volume   =  313,
  pages    = "345--357",
  month    =  oct,
  year     =  2016,
  keywords = "Approach-avoidance; Conflict; Decision-making; Functional
              neuroimaging; Hippocampus; Human; Lesion; Long axis; Memory;
              Rodent; Septotemporal axis; Spatial cognition",
  language = "en"
}

@ARTICLE{Viard2011-oi,
  title    = "Anterior hippocampus and goal-directed spatial decision making",
  author   = "Viard, Armelle and Doeller, Christian F and Hartley, Tom and
              Bird, Chris M and Burgess, Neil",
  abstract = "Planning spatial paths through our environment is an important
              part of everyday life and is supported by a neural system
              including the hippocampus and prefrontal cortex. Here we
              investigated the precise functional roles of the components of
              this system in humans by using fMRI as participants performed a
              simple goal-directed route-planning task. Participants had to
              choose the shorter of two routes to a goal in a visual scene that
              might contain a barrier blocking the most direct route, requiring
              a detour, or might be obscured by a curtain, requiring memory for
              the scene. The participant's start position was varied to
              parametrically manipulate their proximity to the goal and the
              difference in length of the two routes. Activity in medial
              prefrontal cortex, precuneus, and left posterior parietal cortex
              was associated with detour planning, regardless of difficulty,
              whereas activity in parahippocampal gyrus was associated with
              remembering the spatial layout of the visual scene. Activity in
              bilateral anterior hippocampal formation showed a strong increase
              the closer the start position was to the goal, together with
              medial prefrontal, medial and posterior parietal cortices. Our
              results are consistent with computational models in which goal
              proximity is used to guide subsequent navigation and with the
              association of anterior hippocampal areas with nonspatial
              functions such as arousal and reward expectancy. They illustrate
              how spatial and nonspatial functions combine within the anterior
              hippocampus, and how these functions interact with
              parahippocampal, parietal, and prefrontal areas in decision
              making and mnemonic function.",
  journal  = "J. Neurosci.",
  volume   =  31,
  number   =  12,
  pages    = "4613--4621",
  month    =  mar,
  year     =  2011,
  language = "en"
}

@ARTICLE{Seymour2008-vs,
  title    = "Emotion, decision making, and the amygdala",
  author   = "Seymour, Ben and Dolan, Ray",
  abstract = "Emotion plays a critical role in many contemporary accounts of
              decision making, but exactly what underlies its influence and how
              this is mediated in the brain remain far from clear. Here, we
              review behavioral studies that suggest that Pavlovian processes
              can exert an important influence over choice and may account for
              many effects that have traditionally been attributed to emotion.
              We illustrate how recent experiments cast light on the underlying
              structure of Pavlovian control and argue that generally this
              influence makes good computational sense. Corresponding
              neuroscientific data from both animals and humans implicate a
              central role for the amygdala through interactions with other
              brain areas. This yields a neurobiological account of emotion in
              which it may operate, often covertly, to optimize rather than
              corrupt economic choice.",
  journal  = "Neuron",
  volume   =  58,
  number   =  5,
  pages    = "662--671",
  month    =  jun,
  year     =  2008,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Payne1988-pk,
  title     = "Adaptive strategy selection in decision making",
  author    = "Payne, John W and Bettman, James R and Johnson, Eric J",
  abstract  = "The role of effort and accuracy in the adaptive use of decision
               processes is examined. A computer simulation using the concept
               of elementary information processes identified heuristic choice
               strategies that approximate the accuracy of normative procedures
               while saving substantial effort. However, no single heuristic
               did well across all task and context conditions. Of particular
               interest was the finding that under time constraints, several
               heuristics were more accurate than a truncated normative
               procedure. Using a process …",
  journal   = "J. Exp. Psychol. Learn. Mem. Cogn.",
  publisher = "American Psychological Association",
  volume    =  14,
  number    =  3,
  pages     = "534",
  year      =  1988
}

@ARTICLE{Dayan2012-jd,
  title    = "How to set the switches on this thing",
  author   = "Dayan, Peter",
  abstract = "Reinforcement learning (RL) has become a dominant computational
              paradigm for modeling psychological and neural aspects of
              affectively charged decision-making tasks. RL is normally
              construed in terms of the interaction between a subject and its
              environment, with the former emitting actions, and the latter
              providing stimuli, and appetitive and aversive reinforcement.
              However, there is recent emphasis on redrawing the boundary
              between the two, with the organism constructing its own notion of
              reward, punishment and state, and with internal actions, such as
              the gating of working memory, being treated on an equal footing
              with external manipulation of the environment. We review recent
              work in this area, focusing on cognitive control.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "1068--1074",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Balleine2010-es,
  title    = "Human and rodent homologies in action control: corticostriatal
              determinants of goal-directed and habitual action",
  author   = "Balleine, Bernard W and O'Doherty, John P",
  abstract = "Recent behavioral studies in both humans and rodents have found
              evidence that performance in decision-making tasks depends on two
              different learning processes; one encoding the relationship
              between actions and their consequences and a second involving the
              formation of stimulus-response associations. These learning
              processes are thought to govern goal-directed and habitual
              actions, respectively, and have been found to depend on
              homologous corticostriatal networks in these species. Thus,
              recent research using comparable behavioral tasks in both humans
              and rats has implicated homologous regions of cortex (medial
              prefrontal cortex/medial orbital cortex in humans and prelimbic
              cortex in rats) and of dorsal striatum (anterior caudate in
              humans and dorsomedial striatum in rats) in goal-directed action
              and in the control of habitual actions (posterior lateral putamen
              in humans and dorsolateral striatum in rats). These learning
              processes have been argued to be antagonistic or competing
              because their control over performance appears to be all or none.
              Nevertheless, evidence has started to accumulate suggesting that
              they may at times compete and at others cooperate in the
              selection and subsequent evaluation of actions necessary for
              normal choice performance. It appears likely that cooperation or
              competition between these sources of action control depends not
              only on local interactions in dorsal striatum but also on the
              cortico-basal ganglia network within which the striatum is
              embedded and that mediates the integration of learning with basic
              motivational and emotional processes. The neural basis of the
              integration of learning and motivation in choice and
              decision-making is still controversial and we review some recent
              hypotheses relating to this issue.",
  journal  = "Neuropsychopharmacology",
  volume   =  35,
  number   =  1,
  pages    = "48--69",
  month    =  jan,
  year     =  2010,
  language = "en"
}

@ARTICLE{Arnsten2009-ow,
  title    = "Stress signalling pathways that impair prefrontal cortex
              structure and function",
  author   = "Arnsten, Amy F T",
  abstract = "The prefrontal cortex (PFC) - the most evolved brain region -
              subserves our highest-order cognitive abilities. However, it is
              also the brain region that is most sensitive to the detrimental
              effects of stress exposure. Even quite mild acute uncontrollable
              stress can cause a rapid and dramatic loss of prefrontal
              cognitive abilities, and more prolonged stress exposure causes
              architectural changes in prefrontal dendrites. Recent research
              has begun to reveal the intracellular signalling pathways that
              mediate the effects of stress on the PFC. This research has
              provided clues as to why genetic or environmental insults that
              disinhibit stress signalling pathways can lead to symptoms of
              profound prefrontal cortical dysfunction in mental illness.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  10,
  number   =  6,
  pages    = "410--422",
  month    =  jun,
  year     =  2009,
  language = "en"
}

@ARTICLE{Schwabe2013-ka,
  title    = "Stress and multiple memory systems: from 'thinking' to 'doing'",
  author   = "Schwabe, Lars and Wolf, Oliver T",
  abstract = "Although it has been known for decades that stress influences
              memory performance, it was only recently shown that stress may
              alter the contribution of multiple, anatomically and functionally
              distinct memory systems to behavior. Here, we review recent
              animal and human studies demonstrating that stress promotes a
              shift from flexible 'cognitive' to rather rigid 'habit' memory
              systems and discuss, based on recent neuroimaging data in humans,
              the underlying brain mechanisms. We argue that, despite being
              generally adaptive, this stress-induced shift towards 'habit'
              memory may, in vulnerable individuals, be a risk factor for
              psychopathology.",
  journal  = "Trends Cogn. Sci.",
  volume   =  17,
  number   =  2,
  pages    = "60--68",
  month    =  feb,
  year     =  2013,
  language = "en"
}

@ARTICLE{Wirz2018-zd,
  title    = "Habits under stress: mechanistic insights across different types
              of learning",
  author   = "Wirz, Lisa and Bogdanov, Mario and Schwabe, Lars",
  abstract = "Learning can be controlled by reflective, `cognitive' or
              reflexive, `habitual' systems. An essential question is what
              factors determine which system governs behavior. Here we review
              recent evidence from navigation, classification, and instrumental
              learning, demonstrating that stressful events induce a shift from
              cognitive to habitual control of learning. We propose that this
              shift, mediated by noradrenaline and glucocorticoids acting
              through mineralocorticoid receptors, is orchestrated by the
              amygdala. Although generally adaptive for coping with acute
              stress, the bias toward habits comes at the cost of reduced
              flexibility of learning and may ultimately contribute to
              stress-related psychopathologies.",
  journal  = "Current Opinion in Behavioral Sciences",
  volume   =  20,
  pages    = "9--16",
  month    =  apr,
  year     =  2018
}

@ARTICLE{Corbit2018-ep,
  title    = "Understanding the balance between goal-directed and habitual
              behavioral control",
  author   = ". Corbit, Laura H",
  abstract = "Decisions can be reached in different ways. Sometimes they
              involve careful consideration of the expected outcome of our
              behavior. Other times, behavior is generated more automatically
              if a particular response has been repeatedly successful in the
              past. I review animal research into goal-directed and habit
              learning including common training paradigms and studies
              investigating the neural substrates of actions and habits.
              Further, I summarize the wide range of factors (e.g., drugs,
              stress, diet) that promote habitual control. Since habitual
              control is prevalent across a range of neuropsychiatric disorders
              it is important to be able to accurately identify when behavior
              is habitual and better understanding of the behavioral and neural
              determinants of habitual control may enable behavior change when
              needed.",
  journal  = "Current Opinion in Behavioral Sciences",
  volume   =  20,
  pages    = "161--168",
  month    =  apr,
  year     =  2018
}

@ARTICLE{Schwabe2011-ko,
  title    = "Stress-induced modulation of instrumental behavior: from
              goal-directed to habitual control of action",
  author   = "Schwabe, Lars and Wolf, Oliver T",
  abstract = "Actions that are directed at achieving pleasant or avoiding
              unpleasant states are referred to as instrumental. The
              acquisition of instrumental actions can be controlled by two
              anatomically and functionally distinct processes: a goal-directed
              process that is based on the prefrontal cortex and dorsomedial
              striatum and encodes the causal relationship between an action
              and the motivational value of the outcome and a dorsolateral
              striatum-based habit process that learns associations between
              actions and antecedent stimuli. Here, we review recent research
              showing that stress modulates the control of instrumental action
              in a manner that favors habitual over goal-directed action. At
              the neuroendocrine level, this stress-induced shift towards habit
              action requires the concerted action of glucocorticoids and
              noradrenergic arousal and is most likely accompanied by opposite
              functional changes in the corticostriatal circuits underlying
              goal-directed and habitual actions. Although generally adaptive,
              these changes in the control of instrumental action under stress
              may promote dysfunctional behaviors and the development of
              psychiatric disorders such as addiction.",
  journal  = "Behav. Brain Res.",
  volume   =  219,
  number   =  2,
  pages    = "321--328",
  month    =  jun,
  year     =  2011,
  language = "en"
}

@ARTICLE{Keinan1987-ci,
  title    = "Decision making under stress: scanning of alternatives under
              controllable and uncontrollable threats",
  author   = "Keinan, G",
  abstract = "This study tested the proposition that deficient decision making
              under stress is due, to a significant extent, to the individual's
              failure to fulfill adequately an elementary requirement of the
              decision-making process, that is, the systematic consideration of
              all relevant alternatives. One hundred one undergraduate students
              (59 women and 42 men), aged 20-40, served as subjects in this
              experiment. They were requested to solve decision problems, using
              an interactive computer paradigm, while being exposed to
              controllable stress, uncontrollable stress, or no stress at all.
              There was no time constraint for the performance of the task. The
              controllability of the stressor was found to have no effect on
              the participants' performance. However, those who were exposed to
              either controllable or uncontrollable stress showed a
              significantly stronger tendency to offer solutions before all
              available alternatives had been considered and to scan their
              alternatives in a nonsystematic fashion than did participants who
              were not exposed to stress. In addition, patterns of alternative
              scanning were found to be correlated with the correctness of
              solutions to decision problems.",
  journal  = "J. Pers. Soc. Psychol.",
  volume   =  52,
  number   =  3,
  pages    = "639--644",
  month    =  mar,
  year     =  1987,
  language = "en"
}

@ARTICLE{Boureau2015-eo,
  title    = "Deciding How To Decide: {Self-Control} and {Meta-Decision} Making",
  author   = "Boureau, Y-Lan and Sokol-Hessner, Peter and Daw, Nathaniel D",
  abstract = "Many different situations related to self control involve
              competition between two routes to decisions: default and frugal
              versus more resource-intensive. Examples include habits versus
              deliberative decisions, fatigue versus cognitive effort, and
              Pavlovian versus instrumental decision making. We propose that
              these situations are linked by a strikingly similar core dilemma,
              pitting the opportunity costs of monopolizing shared resources
              such as executive functions for some time, against the
              possibility of obtaining a better outcome. We offer a unifying
              normative perspective on this underlying rational
              meta-optimization, review how this may tie together recent
              advances in many separate areas, and connect several independent
              models. Finally, we suggest that the crucial mechanisms and
              meta-decision variables may be shared across domains.",
  journal  = "Trends Cogn. Sci.",
  volume   =  19,
  number   =  11,
  pages    = "700--710",
  month    =  nov,
  year     =  2015,
  language = "en"
}

@ARTICLE{Keramati2011-oj,
  title    = "Speed/accuracy trade-off between the habitual and the
              goal-directed processes",
  author   = "Keramati, Mehdi and Dezfouli, Amir and Piray, Payam",
  abstract = "Instrumental responses are hypothesized to be of two kinds:
              habitual and goal-directed, mediated by the sensorimotor and the
              associative cortico-basal ganglia circuits, respectively. The
              existence of the two heterogeneous associative learning
              mechanisms can be hypothesized to arise from the comparative
              advantages that they have at different stages of learning. In
              this paper, we assume that the goal-directed system is
              behaviourally flexible, but slow in choice selection. The
              habitual system, in contrast, is fast in responding, but
              inflexible in adapting its behavioural strategy to new
              conditions. Based on these assumptions and using the
              computational theory of reinforcement learning, we propose a
              normative model for arbitration between the two processes that
              makes an approximately optimal balance between search-time and
              accuracy in decision making. Behaviourally, the model can explain
              experimental evidence on behavioural sensitivity to outcome at
              the early stages of learning, but insensitivity at the later
              stages. It also explains that when two choices with equal
              incentive values are available concurrently, the behaviour
              remains outcome-sensitive, even after extensive training.
              Moreover, the model can explain choice reaction time variations
              during the course of learning, as well as the experimental
              observation that as the number of choices increases, the reaction
              time also increases. Neurobiologically, by assuming that phasic
              and tonic activities of midbrain dopamine neurons carry the
              reward prediction error and the average reward signals used by
              the model, respectively, the model predicts that whereas phasic
              dopamine indirectly affects behaviour through reinforcing
              stimulus-response associations, tonic dopamine can directly
              affect behaviour through manipulating the competition between the
              habitual and the goal-directed systems and thus, affect reaction
              time.",
  journal  = "PLoS Comput. Biol.",
  volume   =  7,
  number   =  5,
  pages    = "e1002055",
  month    =  may,
  year     =  2011,
  language = "en"
}

@ARTICLE{Yu2016-ns,
  title    = "Stress potentiates decision biases: A stress induced
              deliberation-to-intuition ({SIDI}) model",
  author   = "Yu, Rongjun",
  abstract = "Humans often make decisions in stressful situations, for example
              when the stakes are high and the potential consequences severe,
              or when the clock is ticking and the task demand is overwhelming.
              In response, a whole train of biological responses to stress has
              evolved to allow organisms to make a fight-or-flight response.
              When under stress, fast and effortless heuristics may dominate
              over slow and demanding deliberation in making decisions under
              uncertainty. Here, I review evidence from behavioral studies and
              neuroimaging research on decision making under stress and propose
              that stress elicits a switch from an analytic reasoning system to
              intuitive processes, and predict that this switch is associated
              with diminished activity in the prefrontal executive control
              regions and exaggerated activity in subcortical reactive emotion
              brain areas. Previous studies have shown that when stressed,
              individuals tend to make more habitual responses than
              goal-directed choices, be less likely to adjust their initial
              judgment, and rely more on gut feelings in social situations. It
              is possible that stress influences the arbitration between the
              emotion responses in subcortical regions and deliberative
              processes in the prefrontal cortex, so that final decisions are
              based on unexamined innate responses. Future research may further
              test this 'stress induced deliberation-to-intuition' (SIDI) model
              and examine its underlying neural mechanisms.",
  journal  = "Neurobiol Stress",
  volume   =  3,
  pages    = "83--95",
  month    =  jun,
  year     =  2016,
  keywords = "Cortisol; Decision making; Stress",
  language = "en"
}

@ARTICLE{Frank2009-nv,
  title     = "Multiple Systems in Decision Making: A Neurocomputational
               Perspective",
  author    = "Frank, Michael J and Cohen, Michael X and Sanfey, Alan G",
  abstract  = "Various psychological models posit the existence of two systems
               that contribute to decision making. The first system is
               bottom-up, automatic, intuitive, emotional, and implicit, while
               the second system is top-down, controlled, deliberative, and
               explicit. It has become increasingly evident that this dichotomy
               is both too simplistic and too vague. Here we consider insights
               gained from a different approach, one that considers the
               multiple computational demands of the decision-making system in
               the context of neural mechanisms specialized to accomplish some
               of that system's more basic functions. The use of explicit
               computational models has led to (a) identification of core
               trade-offs imposed by a single-system solution to cognitive
               problems that are solved by having multiple neural systems, and
               (b) novel predictions that can be tested empirically and that
               serve to further refine the models.",
  journal   = "Curr. Dir. Psychol. Sci.",
  publisher = "SAGE Publications Inc",
  volume    =  18,
  number    =  2,
  pages     = "73--77",
  month     =  apr,
  year      =  2009
}

@ARTICLE{Hasselmo2007-mt,
  title    = "Arc length coding by interference of theta frequency oscillations
              may underlie context-dependent hippocampal unit data and episodic
              memory function",
  author   = "Hasselmo, Michael E",
  abstract = "Many memory models focus on encoding of sequences by excitatory
              recurrent synapses in region CA3 of the hippocampus. However,
              data and modeling suggest an alternate mechanism for encoding of
              sequences in which interference between theta frequency
              oscillations encodes the position within a sequence based on
              spatial arc length or time. Arc length can be coded by an
              oscillatory interference model that accounts for many features of
              the context-dependent firing properties of hippocampal neurons
              observed during performance of spatial memory tasks. In
              continuous spatial alternation, many neurons fire selectively
              depending on the direction of prior or future response (left or
              right). In contrast, in delayed non-match to position, most
              neurons fire selectively for task phase (sample vs. choice), with
              less selectivity for left versus right. These seemingly disparate
              results are effectively simulated by the same model, based on
              mechanisms similar to a model of grid cell firing in entorhinal
              cortex. The model also simulates forward shifting of firing over
              trials. Adding effects of persistent firing with reset at reward
              locations addresses changes in context-dependent firing with
              different task designs. Arc length coding could contribute to
              episodic encoding of trajectories as sequences of states and
              actions.",
  journal  = "Learn. Mem.",
  volume   =  14,
  number   =  11,
  pages    = "782--794",
  month    =  nov,
  year     =  2007,
  language = "en"
}

@ARTICLE{Savelli2019-fx,
  title     = "Origin and role of path integration in the cognitive
               representations of the hippocampus: computational insights into
               open questions",
  author    = "Savelli, Francesco and Knierim, James J",
  abstract  = "ABSTRACT Path integration is a straightforward concept with
               varied connotations that are important to different disciplines
               concerned with navigation, such as ethology, cognitive science,
               robotics and neuroscience. In studying the hippocampal
               formation, it is fruitful to think of path integration as a
               computation that transforms a sense of motion into a sense of
               location, continuously integrated with landmark perception.
               Here, we review experimental evidence that path integration is
               intimately involved in fundamental properties of place cells and
               other spatial cells that are thought to support a cognitive
               abstraction of space in this brain system. We discuss hypotheses
               about the anatomical and computational origin of path
               integration in the well-characterized circuits of the rodent
               limbic system. We highlight how computational frameworks for
               map-building in robotics and cognitive science alike suggest an
               essential role for path integration in the creation of a new map
               in unfamiliar territory, and how this very role can help us make
               sense of differences in neurophysiological data from novel
               versus familiar and small versus large environments. Similar
               computational principles could be at work when the hippocampus
               builds certain non-spatial representations, such as time
               intervals or trajectories defined in a sensory stimulus space.",
  journal   = "J. Exp. Biol.",
  publisher = "The Company of Biologists Ltd",
  volume    =  222,
  number    = "Suppl 1",
  pages     = "jeb188912",
  month     =  feb,
  year      =  2019,
  language  = "en"
}

@UNPUBLISHED{Rubin2019-ag,
  title    = "Revealing neural correlates of behavior without behavioral
              measurements",
  author   = "Rubin, Alon and Sheintuch, Liron and Brande-Eilat, Noa and
              Pinchasof, Or and Rechavi, Yoav and Geva, Nitzan and Ziv, Yaniv",
  abstract = "Measuring neuronal tuning curves has been instrumental for many
              discoveries in neuroscience but requires a-priori assumptions
              regarding the identity of the encoded variables. We applied
              unsupervised learning to large-scale neuronal recordings in
              behaving mice from circuits involved in spatial cognition, and
              uncovered a highly-organized internal structure of ensemble
              activity patterns. This emergent structure allowed defining for
              each neuron an 9internal tuning-curve9 that characterizes its
              activity relative to the network activity, rather than relative
              to any pre-defined external variable -revealing place-tuning in
              the hippocampus and head-direction tuning in the thalamus and
              postsubiculum, without relying on measurements of place or
              head-direction. Similar investigation in prefrontal cortex
              revealed schematic representations of distances and actions, and
              exposed a previously unknown variable, the 9trajectory-phase9.
              The structure of ensemble activity patterns was conserved across
              mice, allowing using one animal9s data to decode another animal9s
              behavior. Thus, the internal structure of neuronal activity
              itself enables reconstructing internal representations and
              discovering new behavioral variables hidden within a neural code.",
  journal  = "bioRxiv",
  pages    = "540195",
  month    =  feb,
  year     =  2019,
  language = "en"
}

@ARTICLE{Rabinowitz2018-ur,
  title         = "Machine Theory of Mind",
  author        = "Rabinowitz, Neil C and Perbet, Frank and Francis Song, H and
                   Zhang, Chiyuan and Ali Eslami, S M and Botvinick, Matthew",
  abstract      = "Theory of mind (ToM; Premack \& Woodruff, 1978) broadly
                   refers to humans' ability to represent the mental states of
                   others, including their desires, beliefs, and intentions. We
                   propose to train a machine to build such models too. We
                   design a Theory of Mind neural network -- a ToMnet -- which
                   uses meta-learning to build models of the agents it
                   encounters, from observations of their behaviour alone.
                   Through this process, it acquires a strong prior model for
                   agents' behaviour, as well as the ability to bootstrap to
                   richer predictions about agents' characteristics and mental
                   states using only a small number of behavioural
                   observations. We apply the ToMnet to agents behaving in
                   simple gridworld environments, showing that it learns to
                   model random, algorithmic, and deep reinforcement learning
                   agents from varied populations, and that it passes classic
                   ToM tasks such as the ``Sally-Anne'' test (Wimmer \& Perner,
                   1983; Baron-Cohen et al., 1985) of recognising that others
                   can hold false beliefs about the world. We argue that this
                   system -- which autonomously learns how to model other
                   agents in its world -- is an important step forward for
                   developing multi-agent AI systems, for building
                   intermediating technology for machine-human interaction, and
                   for advancing the progress on interpretable AI.",
  month         =  feb,
  year          =  2018,
  archivePrefix = "arXiv",
  primaryClass  = "cs.AI",
  eprint        = "1802.07740"
}

@UNPUBLISHED{Brette2018-gj,
  title    = "Is coding a relevant metaphor for the brain?",
  author   = "Brette, Romain",
  abstract = "``Neural coding'' is a popular metaphor in neuroscience, where
              objective properties of the world are communicated to the brain
              in the form of spikes. Here I argue that this metaphor is often
              inappropriate and misleading. First, when neurons are said to
              encode experimental parameters, the neural code depends on
              experimental details that are not carried by the coding variable.
              Thus, the representational power of neural codes is much more
              limited than generally implied. Second, neural codes carry
              information only by reference to things with known meaning. In
              contrast, perceptual systems must build information from
              relations between sensory signals and actions, forming a
              structured internal model. Neural codes are inadequate for this
              purpose because they are unstructured. Third, coding variables
              are observables tied to the temporality of experiments, while
              spikes are timed actions that mediate coupling in a distributed
              dynamical system. The coding metaphor tries to fit the dynamic,
              circular and distributed causal structure of the brain into a
              linear chain of transformations between observables, but the two
              causal structures are incongruent. I conclude that the neural
              coding metaphor cannot provide a basis for theories of brain
              function, because it is incompatible with both the causal
              structure of the brain and the informational requirements of
              cognition.",
  journal  = "bioRxiv",
  pages    = "168237",
  month    =  jul,
  year     =  2018,
  language = "en"
}

@ARTICLE{Lisman2009-tn,
  title     = "Prediction, sequences and the hippocampus",
  author    = "Lisman, John and Redish, A D",
  abstract  = "Recordings of rat hippocampal place cells have provided
               information about how the hippocampus retrieves memory
               sequences. One line of evidence has to do with phase precession,
               a process organized by theta and gamma oscillations. This
               precession can be interpreted as the cued prediction of the
               sequence of upcoming positions. In support of this
               interpretation, experiments in two-dimensional environments and
               on a cue-rich linear track demonstrate that many cells represent
               a position ahead of the animal and that this position is the
               same irrespective of which direction the rat is coming from.
               Other lines of investigation have demonstrated that such
               predictive processes also occur in the non-spatial domain and
               that retrieval can be internally or externally cued. The
               mechanism of sequence retrieval and the usefulness of this
               retrieval to guide behaviour are discussed.",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "rstb.royalsocietypublishing.org",
  volume    =  364,
  number    =  1521,
  pages     = "1193--1201",
  month     =  may,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Ji2008-cy,
  title     = "Firing rate dynamics in the hippocampus induced by trajectory
               learning",
  author    = "Ji, Daoyun and Wilson, Matthew A",
  abstract  = "The hippocampus is essential for spatial navigation, which may
               involve sequential learning. However, how the hippocampus
               encodes new sequences in familiar environments is unknown. To
               study the impact of novel spatial sequences on the activity of
               hippocampal neurons, we monitored hippocampal ensembles while
               rats learned to switch from two familiar trajectories to a new
               one in a familiar environment. Here, we show that this novel
               spatial experience induces two types of changes in firing rates,
               but not locations of hippocampal place cells. First, place-cell
               firing rates on the two familiar trajectories start to change
               before the actual behavioral switch to the new trajectory.
               Second, repeated exposure on the new trajectory is associated
               with an increased dependence of place-cell firing rates on
               immediate past locations. The result suggests that sequence
               encoding in the hippocampus may involve integration of
               information about the recent past into current state.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  28,
  number    =  18,
  pages     = "4679--4689",
  month     =  apr,
  year      =  2008,
  language  = "en"
}

@ARTICLE{Eichenbaum2009-jb,
  title     = "The neurobiology of memory based predictions",
  author    = "Eichenbaum, Howard and Fortin, Norbert J",
  abstract  = "Recent findings indicate that, in humans, the hippocampal memory
               system is involved in the capacity to imagine the future as well
               as remember the past. Other studies have suggested that animals
               may also have the capacity to recall the past and plan for the
               future. Here, we will consider data that bridge between these
               sets of findings by assessing the role of the hippocampus in
               memory and prediction in rats. We will argue that animals have
               the capacity for recollection and that the hippocampus plays a
               central and selective role in binding information in the service
               of recollective memory. Then we will consider examples of
               transitive inference, a paradigm that requires the integration
               of overlapping memories and flexible use of the resulting
               relational memory networks for generating predictions in novel
               situations. Our data show that animals have the capacity for
               transitive inference and that the hippocampus plays a central
               role in the ability to predict outcomes of events that have not
               yet occurred.",
  journal   = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  publisher = "royalsocietypublishing.org",
  volume    =  364,
  number    =  1521,
  pages     = "1183--1191",
  month     =  may,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Eichenbaum2000-rr,
  title     = "A cortical--hippocampal system for declarative memory",
  author    = "Eichenbaum, Howard",
  abstract  = "Recent neurobiological studies have begun to reveal the
               cognitive and neural coding mechanisms that underlie declarative
               memory --- our ability to recollect everyday events and factual
               knowledge. These studies indicate that the critical circuitry
               involves bidirectional connections between the neocortex, the
               parahippocampal region and the hippocampus. Each of these areas
               makes a unique contribution to memory processing. Widespread
               high-order neocortical areas provide dedicated processors for
               perceptual, motor or cognitive information that is influenced by
               other components of the system. The parahippocampal region
               mediates convergence of this information and extends the
               persistence of neocortical memory representations. The
               hippocampus encodes the sequences of places and events that
               compose episodic memories, and links them together through their
               common elements. Here I describe how these mechanisms work
               together to create and re-create fully networked representations
               of previous experiences and knowledge about the world.",
  journal   = "Nat. Rev. Neurosci.",
  publisher = "Macmillan Magazines Ltd.",
  volume    =  1,
  pages     = "41",
  month     =  oct,
  year      =  2000
}

@ARTICLE{Moser2008-af,
  title     = "Place cells, grid cells, and the brain's spatial representation
               system",
  author    = "Moser, Edvard I and Kropff, Emilio and Moser, May-Britt",
  abstract  = "More than three decades of research have demonstrated a role for
               hippocampal place cells in representation of the spatial
               environment in the brain. New studies have shown that place
               cells are part of a broader circuit for dynamic representation
               of self-location. A key component of this network is the
               entorhinal grid cells, which, by virtue of their tessellating
               firing fields, may provide the elements of a path
               integration-based neural map. Here we review how place cells and
               grid cells may form the basis for quantitative spatiotemporal
               representation of places, routes, and associated experiences
               during behavior and in memory. Because these cell types have
               some of the most conspicuous behavioral correlates among neurons
               in nonsensory cortical systems, and because their spatial firing
               structure reflects computations internally in the system,
               studies of entorhinal-hippocampal representations may offer
               considerable insight into general principles of cortical network
               dynamics.",
  journal   = "Annu. Rev. Neurosci.",
  publisher = "annualreviews.org",
  volume    =  31,
  pages     = "69--89",
  year      =  2008,
  language  = "en"
}

@ARTICLE{Squire2004-hb,
  title    = "The medial temporal lobe",
  author   = "Squire, Larry R and Stark, Craig E L and Clark, Robert E",
  abstract = "The medial temporal lobe includes a system of anatomically
              related structures that are essential for declarative memory
              (conscious memory for facts and events). The system consists of
              the hippocampal region (CA fields, dentate gyrus, and subicular
              complex) and the adjacent perirhinal, entorhinal, and
              parahippocampal cortices. Here, we review findings from humans,
              monkeys, and rodents that illuminate the function of these
              structures. Our analysis draws on studies of human memory
              impairment and animal models of memory impairment, as well as
              neurophysiological and neuroimaging data, to show that this
              system (a) is principally concerned with memory, (b) operates
              with neocortex to establish and maintain long-term memory, and
              (c) ultimately, through a process of consolidation, becomes
              independent of long-term memory, though questions remain about
              the role of perirhinal and parahippocampal cortices in this
              process and about spatial memory in rodents. Data from
              neurophysiology, neuroimaging, and neuroanatomy point to a
              division of labor within the medial temporal lobe. However, the
              available data do not support simple dichotomies between the
              functions of the hippocampus and the adjacent medial temporal
              cortex, such as associative versus nonassociative memory,
              episodic versus semantic memory, and recollection versus
              familiarity.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  27,
  pages    = "279--306",
  year     =  2004,
  language = "en"
}

@ARTICLE{Kloosterman2014-ki,
  title     = "Bayesian decoding using unsorted spikes in the rat hippocampus",
  author    = "Kloosterman, Fabian and Layton, Stuart P and Chen, Zhe and
               Wilson, Matthew A",
  abstract  = "A fundamental task in neuroscience is to understand how neural
               ensembles represent information. Population decoding is a useful
               tool to extract information from neuronal populations based on
               the ensemble spiking activity. We propose a novel Bayesian
               decoding paradigm to decode unsorted spikes in the rat
               hippocampus. Our approach uses a direct mapping between spike
               waveform features and covariates of interest and avoids
               accumulation of spike sorting errors. Our decoding paradigm is
               nonparametric, encoding model-free for representing stimuli, and
               extracts information from all available spikes and their
               waveform features. We apply the proposed Bayesian decoding
               algorithm to a position reconstruction task for freely behaving
               rats based on tetrode recordings of rat hippocampal neuronal
               activity. Our detailed decoding analyses demonstrate that our
               approach is efficient and better utilizes the available
               information in the nonsortable hash than the standard
               sorting-based decoding algorithm. Our approach can be adapted to
               an online encoding/decoding framework for applications that
               require real-time decoding, such as brain-machine interfaces.",
  journal   = "J. Neurophysiol.",
  publisher = "physiology.org",
  volume    =  111,
  number    =  1,
  pages     = "217--227",
  month     =  jan,
  year      =  2014,
  keywords  = "kernel density estimation; neural decoding; population codes;
               spatial-temporal Poisson process; spike sorting",
  language  = "en"
}

@ARTICLE{Wikenheiser2015-pj,
  title     = "Hippocampal theta sequences reflect current goals",
  author    = "Wikenheiser, Andrew M and Redish, A David",
  abstract  = "Hippocampal information processing is discretized by
               oscillations, and the ensemble activity of place cells is
               organized into temporal sequences bounded by theta cycles. Theta
               sequences represent time-compressed trajectories through space.
               Their forward-directed nature makes them an intuitive candidate
               mechanism for planning future trajectories, but their connection
               to goal-directed behavior remains unclear. As rats performed a
               value-guided decision-making task, the extent to which theta
               sequences projected ahead of the animal's current location
               varied on a moment-by-moment basis depending on the rat's goals.
               Look-ahead extended farther on journeys to distant goals than on
               journeys to more proximal goals and was predictive of the
               animal's destination. On arrival at goals, however, look-ahead
               was similar regardless of where the animal began its journey
               from. Together, these results provide evidence that hippocampal
               theta sequences contain information related to goals or
               intentions, pointing toward a potential spatial basis for
               planning.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  18,
  number    =  2,
  pages     = "289--294",
  month     =  feb,
  year      =  2015,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Buckner2010-by,
  title     = "The role of the hippocampus in prediction and imagination",
  author    = "Buckner, Randy L",
  abstract  = "Traditionally, the hippocampal system has been studied in
               relation to the goal of retrieving memories about the past.
               Recent work in humans and rodents suggests that the hippocampal
               system may be better understood as a system that facilitates
               predictions about upcoming events. The hippocampus and
               associated cortical structures are active when people envision
               future events, and damage that includes the hippocampal region
               impairs this ability. In rats, hippocampal ensembles preplay and
               replay event sequences in the …",
  journal   = "Annu. Rev. Psychol.",
  publisher = "Annual Reviews",
  volume    =  61,
  pages     = "27--48",
  year      =  2010
}

@ARTICLE{Mullally2014-cr,
  title     = "Memory, Imagination, and Predicting the Future: A Common Brain
               Mechanism?",
  author    = "Mullally, Sin{\'e}ad L and Maguire, Eleanor A",
  abstract  = "On the face of it, memory, imagination, and prediction seem to
               be distinct cognitive functions. However, metacognitive,
               cognitive, neuropsychological, and neuroimaging evidence is
               emerging that they are not, suggesting intimate links in their
               underlying processes. Here, we explore these empirical findings
               and the evolving theoretical frameworks that seek to explain how
               a common neural system supports our recollection of times past,
               imagination, and our attempts to predict the future.",
  journal   = "Neuroscientist",
  publisher = "journals.sagepub.com",
  volume    =  20,
  number    =  3,
  pages     = "220--234",
  month     =  jun,
  year      =  2014,
  keywords  = "amnesia; episodic memory; fMRI; future; hippocampus;
               imagination; navigation; neuropsychology; prediction;
               prospection; scene construction; scenes; simulation",
  language  = "en"
}

@ARTICLE{Smallwood2015-wd,
  title     = "The science of mind wandering: empirically navigating the stream
               of consciousness",
  author    = "Smallwood, Jonathan and Schooler, Jonathan W",
  abstract  = "Conscious experience is fluid; it rarely remains on one topic
               for an extended period without deviation. Its dynamic nature is
               illustrated by the experience of mind wandering, in which
               attention switches from a current task to unrelated thoughts and
               feelings. Studies exploring the phenomenology of mind wandering
               highlight the importance of its content and relation to
               meta-cognition in determining its functional outcomes.
               Examination of the information-processing demands of the
               mind-wandering state suggests that it involves perceptual
               decoupling to escape the constraints of the moment, its content
               arises from episodic and affective processes, and its regulation
               relies on executive control. Mind wandering also involves a
               complex balance of costs and benefits: Its association with
               various kinds of error underlines its cost, whereas its
               relationship to creativity and future planning suggest its
               potential value. Although essential to the stream of
               consciousness, various strategies may minimize the downsides of
               mind wandering while maintaining its productive aspects.",
  journal   = "Annu. Rev. Psychol.",
  publisher = "annualreviews.org",
  volume    =  66,
  pages     = "487--518",
  month     =  jan,
  year      =  2015,
  keywords  = "default mode network; mental time travel; meta-awareness; mind
               wandering; perceptual decoupling; self-generated thought",
  language  = "en"
}

@ARTICLE{Voermans2004-ir,
  title     = "Interaction between the human hippocampus and the caudate
               nucleus during route recognition",
  author    = "Voermans, Nicol C and Petersson, Karl Magnus and Daudey, Leonie
               and Weber, Bernd and Van Spaendonck, Karel P and Kremer,
               Hubertus P H and Fern{\'a}ndez, Guill{\'e}n",
  abstract  = "Navigation through familiar environments can rely upon distinct
               neural representations that are related to different memory
               systems with either the hippocampus or the caudate nucleus at
               their core. However, it is a fundamental question whether and
               how these systems interact during route recognition. To address
               this issue, we combined a functional neuroimaging approach with
               a naturally occurring, well-controlled human model of caudate
               nucleus dysfunction (i.e., preclinical and early-stage
               Huntington's disease). Our results reveal a noncompetitive
               interaction so that the hippocampus compensates for gradual
               caudate nucleus dysfunction with a gradual activity increase,
               maintaining normal behavior. Furthermore, we revealed an
               interaction between medial temporal and caudate activity in
               healthy subjects, which was adaptively modified in Huntington
               patients to allow compensatory hippocampal processing. Thus, the
               two memory systems contribute in a noncompetitive, cooperative
               manner to route recognition, which enables the hippocampus to
               compensate seamlessly for the functional degradation of the
               caudate nucleus.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  43,
  number    =  3,
  pages     = "427--435",
  month     =  aug,
  year      =  2004,
  language  = "en"
}

@ARTICLE{Lee2011-an,
  title     = "Using hierarchical Bayesian methods to examine the tools of
               decision-making",
  author    = "Lee, Michael D and Newell, Ben R",
  abstract  = "Author(s): Lee, Michael D.; Newell, Ben R. | Abstract:
               Hierarchical Bayesian methods offer a principled and
               comprehensive way to relate psychological models to data. Here
               we use them to model the patterns of information search,
               stopping and deciding in a simulated binary comparison judgment
               task. The simulation involves 20 subjects making 100 forced
               choice comparisons about the relative magnitudes of two objects
               (which of two German cities has more inhabitants). Two
               worked-examples show how hierarchical models can be developed to
               account for and explain the diversity of both search and
               stopping rules seen across the simulated individuals. We discuss
               how the results provide insight into current debates in the
               literature on heuristic decision making and argue that they
               demonstrate the power and flexibility of hierarchical Bayesian
               methods in modeling human decision-making.",
  publisher = "escholarship.org",
  volume    =  6,
  number    =  8,
  pages     = "832--842",
  month     =  dec,
  year      =  2011,
  keywords  = "Social and Behavioral Sciences"
}

@ARTICLE{Zatka-Haas_undated-ob,
  title  = "Distinct contributions of mouse cortical areas to visual
            discrimination",
  author = "Zatka-Haas, Peter and Steinmetz, Nicholas A and Carandini, Matteo
            and Harris, Kenneth D"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Penny2012-xo,
  title     = "Bayesian models of brain and behaviour",
  author    = "Penny, William",
  abstract  = "… A readjust- ment at the next level in the hierarchy may
               increase … have multiple hidden variables, for example,
               representing different levels of abstraction in cortical
               hierarchies , and multiple … the applicability of the approach,
               but it is highly efficient for many hierarchical models [21] …",
  journal   = "ISRN Biomathematics",
  publisher = "Hindawi Publishing Corporation",
  volume    =  2012,
  year      =  2012
}

@UNPUBLISHED{Bernardi2018-ma,
  title    = "The geometry of abstraction in hippocampus and prefrontal cortex",
  author   = "Bernardi, Silvia and Benna, Marcus K and Rigotti, Mattia and
              Munuera, Jerome and Fusi, Stefano and Salzman, Daniel",
  abstract = "Abstraction can be defined as a cognitive process that identifies
              common features - abstract variables, or concepts - shared by
              many examples. Such conceptual knowledge enables subjects to
              generalize upon encountering new examples, an ability that
              supports inferential reasoning and cognitive flexibility. To
              confer the ability to generalize, the brain must represent
              variables in a particular `abstract9 format. Here we show how to
              construct neural representations that encode multiple variables
              in an abstract format simultaneously, and we characterize their
              geometry. Neural representations conforming to this geometry were
              observed in dorsolateral pre-frontal cortex, anterior cingulate
              cortex and the hippocampus in monkeys performing a serial
              reversal-learning task. Similar representations are observed in a
              simulated multi-layer neural network trained with
              back-propagation. These findings provide a novel framework for
              characterizing how different brain areas represent abstract
              variables that are critical for flexible conceptual
              generalization.",
  journal  = "bioRxiv",
  pages    = "408633",
  month    =  dec,
  year     =  2018,
  language = "en"
}

@ARTICLE{Lee2012-pe,
  title    = "Neural basis of reinforcement learning and decision making",
  author   = "Lee, Daeyeol and Seo, Hyojung and Jung, Min Whan",
  abstract = "Reinforcement learning is an adaptive process in which an animal
              utilizes its previous experience to improve the outcomes of
              future choices. Computational theories of reinforcement learning
              play a central role in the newly emerging areas of neuroeconomics
              and decision neuroscience. In this framework, actions are chosen
              according to their value functions, which describe how much
              future reward is expected from each action. Value functions can
              be adjusted not only through reward and penalty, but also by the
              animal's knowledge of its current environment. Studies have
              revealed that a large proportion of the brain is involved in
              representing and updating value functions and using them to
              choose an action. However, how the nature of a behavioral task
              affects the neural mechanisms of reinforcement learning remains
              incompletely understood. Future studies should uncover the
              principles by which different computational elements of
              reinforcement learning are dynamically coordinated across the
              entire brain.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  35,
  pages    = "287--308",
  month    =  mar,
  year     =  2012,
  language = "en"
}

@ARTICLE{Groman2018-tb,
  title    = "Neurochemical and behavioral dissections of decision-making in a
              rodent multi-stage task",
  author   = "Groman, Stephanie M and Massi, Bart and Mathias, Samuel R and
              Curry, Daniel W and Lee, Daeyeol and Taylor, Jane R",
  abstract = "Flexible decision-making in dynamic environments requires both
              retrospective appraisal of reinforced actions and prospective
              reasoning about the consequences of actions. These complementary
              reinforcement-learning systems can be characterized
              computationally with model-free and model-based algorithms, but
              how these processes interact at a neurobehavioral level in normal
              and pathological states is unknown. Here, we developed a
              translationally analogous multi-stage decision-making task to
              independently quantify model-free and model-based behavioral
              mechanisms in rats. We provide the first direct evidence that
              male rats, similar to humans, use both model-free and model-based
              learning when making value-based choices in the multi-stage
              decision-making task and provide novel analytic approaches for
              independently quantifying these reinforcement-learning
              strategies. Furthermore, we report that ex vivo dopamine tone in
              the ventral striatum and orbitofrontal cortex correlate with
              model-based, but not model-free, strategies indicating that the
              biological mechanisms mediating decision-making in the
              multi-stage task are conserved in rats and humans. This new
              multi-stage task provides a unique behavioral platform for
              conducting systems level analyses of decision-making in normal
              and pathological states.Significance statementDecision-making is
              influenced by both a retrospective ``model free'' system and a
              prospective ``model based'' system in humans, but the
              biobehavioral mechanisms mediating these learning systems in
              normal and disease states are unknown. Here, we describe a
              translationally analogous multi-stage decision-making task to
              provide a behavioral platform for conducting neuroscience studies
              of decision-making in rats. We provide the first evidence that
              choice behavior in rats is influenced by model-free and
              model-based systems and demonstrate that model-based, but not
              model-free, learning is associated with cortico-striatal dopamine
              tone. This novel behavioral paradigm has the potential to yield
              critical insights into the mechanisms mediating decision-making
              alterations in mental disorders.",
  journal  = "J. Neurosci.",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Clawson2019-kk,
  title    = "Computing Hubs in the Hippocampus and Cortex",
  author   = "Clawson, Wesley P and Vicente, Ana F and Bernard, Christophe and
              Battaglia, Demian and Quilichini, Pascale P",
  abstract = "Neural computation, which relies on the active storage and
              sharing of information, occurs within large neuron networks in
              the highly dynamic context of varying brain states. Whether such
              functions are performed by specific subsets of neurons and
              whether they occur in specific dynamical regimes remain poorly
              understood. Using high density recordings in the hippocampus,
              medial entorhinal and medial prefrontal cortex of the rat, we
              identify computing microstates, or discreet epochs, in which
              specific computing hub neurons perform well defined storage and
              sharing operations in a brain state-dependent manner. We retrieve
              a multiplicity of distinct computing microstates within each
              global brain state, such as REM and nonREM sleep. Half of
              recorded neurons act as computing hubs in at least one
              microstate, suggesting that functional roles are not firmly
              hardwired but dynamically reassigned at the second timescale. We
              identify sequences of microstates whose temporal organization is
              dynamic and stands between order and disorder. We propose that
              global brain states constrain the language of neuronal
              computations by regulating the syntactic complexity of these
              microstate sequences.",
  journal  = "bioRxiv",
  pages    = "513424",
  month    =  jan,
  year     =  2019,
  language = "en"
}

@ARTICLE{Crochet2019-lk,
  title    = "Neural Circuits for {Goal-Directed} Sensorimotor Transformations",
  author   = "Crochet, Sylvain and Lee, Seung-Hee and Petersen, Carl C H",
  abstract = "Precisely wired neuronal circuits process sensory information in
              a learning- and context-dependent manner in order to govern
              behavior. Simple sensory decision-making tasks in rodents are now
              beginning to reveal the contributions of distinct cell types and
              brain regions participating in the conversion of sensory
              information into learned goal-directed motor output. Task
              learning is accompanied by target-specific routing of sensory
              information to specific downstream cortical regions, with
              higher-order cortical regions such as the posterior parietal
              cortex, medial prefrontal cortex, and hippocampus appearing to
              play important roles in learning- and context-dependent
              processing of sensory input. An important challenge for future
              research is to connect cell-type-specific activity in these brain
              regions with motor neurons responsible for action initiation.",
  journal  = "Trends Neurosci.",
  volume   =  42,
  number   =  1,
  pages    = "66--77",
  month    =  jan,
  year     =  2019,
  keywords = "decision-making; neocortex; neuronal cell-types; sensory
              perception",
  language = "en"
}

@MISC{John_OKeefe_undated-cu,
  title    = "The hippocampus as a cognitive map",
  author   = "John O'Keefe, Lynn Nadel",
  keywords = "books;Books"
}

@ARTICLE{McNaughton2006-by,
  title    = "Path integration and the neural basis of the 'cognitive map'",
  author   = "McNaughton, Bruce L and Battaglia, Francesco P and Jensen, Ole
              and Moser, Edvard I and Moser, May-Britt",
  abstract = "The hippocampal formation can encode relative spatial location,
              without reference to external cues, by the integration of linear
              and angular self-motion (path integration). Theoretical studies,
              in conjunction with recent empirical discoveries, suggest that
              the medial entorhinal cortex (MEC) might perform some of the
              essential underlying computations by means of a unique, periodic
              synaptic matrix that could be self-organized in early development
              through a simple, symmetry-breaking operation. The scale at which
              space is represented increases systematically along the
              dorsoventral axis in both the hippocampus and the MEC, apparently
              because of systematic variation in the gain of a movement-speed
              signal. Convergence of spatially periodic input at multiple
              scales, from so-called grid cells in the entorhinal cortex, might
              result in non-periodic spatial firing patterns (place fields) in
              the hippocampus.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  7,
  number   =  8,
  pages    = "663--678",
  month    =  aug,
  year     =  2006,
  language = "en"
}

@ARTICLE{Pereira2016-eq,
  title    = "Is there anybody out there? Neural circuits of threat detection
              in vertebrates",
  author   = "Pereira, Ana G and Moita, Marta A",
  abstract = "Avoiding or escaping a predator is arguably one of the most
              important functions of a prey's brain, hence of most animals'
              brains. Studies on fear conditioning have greatly advanced our
              understanding of the circuits that regulate learned defensive
              behaviours. However, animals possess a multitude of threat
              detection mechanisms, from hardwired circuits that ensure innate
              responses to predator cues, to the use of social information.
              Surprisingly, only more recently have these circuits captured the
              attention of a wider range of researchers working on different
              species and behavioural paradigms. These have shed new light into
              the mechanisms of threat detection revealing conservation of the
              kinds of cues animals use and of its underlying detection
              circuits across vertebrates. As most of these studies focus on
              single cues, we argue for the need to study multisensory
              integration, a process that we believe is determinant for the
              prey's defence responses.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  41,
  pages    = "179--187",
  month    =  dec,
  year     =  2016,
  language = "en"
}

@ARTICLE{Stott2014-ac,
  title    = "A functional difference in information processing between
              orbitofrontal cortex and ventral striatum during decision-making
              behaviour",
  author   = "Stott, Jeffrey J and Redish, A David",
  abstract = "Both orbitofrontal cortex (OFC) and ventral striatum (vStr) have
              been identified as key structures that represent information
              about value in decision-making tasks. However, the dynamics of
              how this information is processed are not yet understood. We
              recorded ensembles of cells from OFC and vStr in rats engaged in
              the spatial adjusting delay-discounting task, a decision-making
              task that involves a trade-off between delay to and magnitude of
              reward. Ventral striatal neural activity signalled information
              about reward before the rat's decision, whereas such
              reward-related signals were absent in OFC until after the animal
              had committed to its decision. These data support models in which
              vStr is directly involved in action selection, but OFC processes
              decision-related information afterwards that can be used to
              compare the predicted and actual consequences of behaviour.",
  journal  = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  volume   =  369,
  number   =  1655,
  month    =  nov,
  year     =  2014,
  keywords = "decision-making; neuroeconomics; nucleus accumbens; orbitofrontal
              cortex; vicarious trial and error",
  language = "en"
}

@ARTICLE{Jones2005-ye,
  title    = "Theta rhythms coordinate hippocampal-prefrontal interactions in a
              spatial memory task",
  author   = "Jones, Matthew W and Wilson, Matthew A",
  abstract = "Decision-making requires the coordinated activity of diverse
              brain structures. For example, in maze-based tasks, the
              prefrontal cortex must integrate spatial information encoded in
              the hippocampus with mnemonic information concerning route and
              task rules in order to direct behavior appropriately. Using
              simultaneous tetrode recordings from CA1 of the rat hippocampus
              and medial prefrontal cortex, we show that correlated firing in
              the two structures is selectively enhanced during behavior that
              recruits spatial working memory, allowing the integration of
              hippocampal spatial information into a broader, decision-making
              network. The increased correlations are paralleled by enhanced
              coupling of the two structures in the 4- to 12-Hz theta-frequency
              range. Thus the coordination of theta rhythms may constitute a
              general mechanism through which the relative timing of disparate
              neural activities can be controlled, allowing specialized brain
              structures to both encode information independently and to
              interact selectively according to current behavioral demands.",
  journal  = "PLoS Biol.",
  volume   =  3,
  number   =  12,
  pages    = "e402",
  month    =  dec,
  year     =  2005,
  language = "en"
}

@ARTICLE{Powell2014-iy,
  title    = "Complex neural codes in rat prelimbic cortex are stable across
              days on a spatial decision task",
  author   = "Powell, Nathaniel J and Redish, A David",
  abstract = "The rodent prelimbic cortex has been shown to play an important
              role in cognitive processing, and has been implicated in encoding
              many different parameters relevant to solving decision-making
              tasks. However, it is not known how the prelimbic cortex
              represents all these disparate variables, and if they are
              simultaneously represented when the task requires it. In order to
              investigate this question, we trained rats to run the Multiple-T
              Left Right Alternate (MT-LRA) task and recorded multi-unit
              ensembles from their prelimbic regions. Significant populations
              of cells in the prelimbic cortex represented the strategy
              controlling reward receipt on a given lap, whether the animal
              chose to go right or left on a given lap, and whether the animal
              made a correct decision or an error on a given lap. These
              populations overlapped in the cells recorded, with several cells
              demonstrating differential firing to all three variables. The
              spatial and strategic firing patterns of individual prelimbic
              cells were highly conserved across several days of running this
              task, indicating that each cell encoded the same information
              across days.",
  journal  = "Front. Behav. Neurosci.",
  volume   =  8,
  pages    = "120",
  month    =  apr,
  year     =  2014,
  keywords = "animal; behavior; decision-making; neural ensemble data;
              prefrontal cortex (PFC); prelimbic cortex; rats; tetrode
              recording",
  language = "en"
}

@ARTICLE{Amemiya2016-fb,
  title    = "Manipulating Decisiveness in Decision Making: Effects of
              Clonidine on Hippocampal Search Strategies",
  author   = "Amemiya, Seiichiro and Redish, A David",
  abstract = "Decisiveness is the ability to commit to a decision quickly and
              efficiently; in contrast, indecision entails the repeated
              consideration of multiple alternative possibilities. In humans,
              the $\alpha$2-adrenergic receptor agonist clonidine increases
              decisiveness in tasks that require planning through unknown
              neural mechanisms. In rats, indecision is manifested as
              reorienting behaviors at choice points (vicarious trial and error
              [VTE]), during which hippocampal representations alternate
              between prospective options. To determine whether the increase in
              decisiveness driven by clonidine also entails changes in
              hippocampal search processes, we compared the effect of clonidine
              on spatial representations in hippocampal neural ensembles as
              rats passed through a T-shaped decision point. Consistent with
              previous experiments, hippocampal representations reflected both
              chosen and unchosen paths during VTE events under saline control
              conditions. Also, consistent with previous experiments,
              hippocampal representations reflected the chosen path more than
              the unchosen path when the animal did not show VTE at the choice
              point. Injection of clonidine suppressed the spatial
              representation of the unchosen path at the choice point on VTE
              laps and hastened the differentiation of spatial representations
              of the chosen path from the unchosen path on non-VTE laps to
              appear before reaching the choice point. These results suggest
              that the decisiveness seen under clonidine is due to limited
              exploration of potential options in hippocampus, and suggest
              novel roles for noradrenaline as a modulator of the hippocampal
              search processes. Significance statement: Clonidine, an
              $\alpha$2-adrenergic receptor agonist, which decreases the level
              of noradrenaline in vivo, has an interesting effect in humans and
              other animals: it makes them more decisive. However, the
              mechanisms by which clonidine makes them more decisive remain
              unknown. Researchers have speculated that clonidine limits the
              amount of mental search that subjects do when planning options.
              We test this hypothesis by measuring the mental search strategy
              in rats through hippocampal recordings. We find that clonidine
              limits the options searched by rats, suggesting that
              noradrenaline also plays a role in balancing exploration and
              exploitation in internally simulated behaviors, similar to its
              role in balancing exploration and exploitation in external
              behaviors.",
  journal  = "J. Neurosci.",
  volume   =  36,
  number   =  3,
  pages    = "814--827",
  month    =  jan,
  year     =  2016,
  keywords = "VTE; hippocampus; noradrenaline; norepinphrine; place field;
              vicarious trial and error",
  language = "en"
}

@ARTICLE{Schmitzer-Torbert2004-tj,
  title    = "Neuronal activity in the rodent dorsal striatum in sequential
              navigation: separation of spatial and reward responses on the
              multiple {T} task",
  author   = "Schmitzer-Torbert, Neil and Redish, A David",
  abstract = "The striatum plays an important role in ``habitual'' learning and
              memory and has been hypothesized to implement a
              reinforcement-learning algorithm to select actions to perform
              given the current sensory input. Many experimental approaches to
              striatal activity have made use of temporally structured tasks,
              which imply that the striatal representation is temporal. To test
              this assumption, we recorded neurons in the dorsal striatum of
              rats running a sequential navigation task: the multiple T maze.
              Rats navigated a sequence of four T maze turns to receive food
              rewards delivered in two locations. The responses of neurons that
              fired phasically were examined. Task-responsive phasic neurons
              were active as rats ran on the maze (maze-responsive) or during
              reward receipt (reward-responsive). Neither maze- nor
              reward-responsive neurons encoded simple motor commands:
              maze-responses were not well correlated with the shape of the
              rat's path and most reward-responsive neurons did not fire at
              similar rates at both food-delivery sites. Maze-responsive
              neurons were active at one or more locations on the maze, but
              these responses did not cluster at spatial landmarks such as
              turns. Across sessions the activity of maze-responsive neurons
              was highly correlated when rats ran the same maze. Maze-responses
              encoded the location of the rat on the maze and imply a spatial
              representation in the striatum in a task with prominent spatial
              demands. Maze-responsive and reward-responsive neurons were two
              separate populations, suggesting a divergence in striatal
              information processing of navigation and reward.",
  journal  = "J. Neurophysiol.",
  volume   =  91,
  number   =  5,
  pages    = "2259--2272",
  month    =  may,
  year     =  2004,
  language = "en"
}

@ARTICLE{Johnson2007-br,
  title    = "Neural ensembles in {CA3} transiently encode paths forward of the
              animal at a decision point",
  author   = "Johnson, Adam and Redish, A David",
  abstract = "Neural ensembles were recorded from the CA3 region of rats
              running on T-based decision tasks. Examination of neural
              representations of space at fast time scales revealed a transient
              but repeatable phenomenon as rats made a decision: the location
              reconstructed from the neural ensemble swept forward, first down
              one path and then the other. Estimated representations were
              coherent and preferentially swept ahead of the animal rather than
              behind the animal, implying it represented future possibilities
              rather than recently traveled paths. Similar phenomena occurred
              at other important decisions (such as in recovery from an error).
              Local field potentials from these sites contained pronounced
              theta and gamma frequencies, but no sharp wave frequencies.
              Forward-shifted spatial representations were influenced by task
              demands and experience. These data suggest that the hippocampus
              does not represent space as a passive computation, but rather
              that hippocampal spatial processing is an active process likely
              regulated by cognitive mechanisms.",
  journal  = "J. Neurosci.",
  volume   =  27,
  number   =  45,
  pages    = "12176--12189",
  month    =  nov,
  year     =  2007,
  language = "en"
}

@ARTICLE{Steiner2012-xp,
  title    = "The road not taken: neural correlates of decision making in
              orbitofrontal cortex",
  author   = "Steiner, Adam P and Redish, A David",
  abstract = "Empirical research links human orbitofrontal cortex (OFC) to the
              evaluation of outcomes during decision making and the
              representation of alternative (better) outcomes after failures.
              When faced with a difficult decision, rats sometimes pause and
              turn back-and-forth toward goals, until finally orienting toward
              the chosen direction. Neural representations of reward in rodent
              OFC increased immediately following each reorientation, implying
              a transient representation of the expected outcome following
              self-initiated decisions. Upon reaching reward locations and
              finding no reward (having made an error), OFC representations of
              reward decreased locally indicating a disappointment signal that
              then switched to represent the unrewarded, non-local,
              would-have-been rewarded site. These results illustrate that
              following a decision to act, neural ensembles in OFC represent
              reward, and upon the realization of an error, represent the
              reward that could have been.",
  journal  = "Front. Neurosci.",
  volume   =  6,
  pages    = "131",
  month    =  sep,
  year     =  2012,
  keywords = "counterfactual; covert representation of reward; multiple T;
              orbitofrontal cortex; regret; vicarious trial and error",
  language = "en"
}

@ARTICLE{Tolman_undated-yh,
  title  = "Cognitive Critique",
  author = "Tolman, Revisiting and Ries, His Theo"
}

@ARTICLE{Redish2016-wf,
  title    = "The Computational Complexity of Valuation and Motivational Forces
              in {Decision-Making} Processes",
  author   = "Redish, A David and Schultheiss, Nathan W and Carter, Evan C",
  abstract = "The concept of value is fundamental to most theories of
              motivation and decision making. However, value has to be measured
              experimentally. Different methods of measuring value produce
              incompatible valuation hierarchies. Taking the agent's
              perspective (rather than the experimenter's), we interpret the
              different valuation measurement methods as accessing different
              decision-making systems and show how these different systems
              depend on different information processing algorithms. This
              identifies the translation from these multiple decision-making
              systems into a single action taken by a given agent as one of the
              most important open questions in decision making today. We
              conclude by looking at how these different valuation measures
              accessing different decision-making systems can be used to
              understand and treat decision dysfunction such as in addiction.",
  journal  = "Curr. Top. Behav. Neurosci.",
  volume   =  27,
  pages    = "313--333",
  year     =  2016,
  keywords = "Decision-Making; Multiple Decision Theory; Neuroeconomonics;
              Valuation",
  language = "en"
}

@ARTICLE{Phelps2014-qu,
  title    = "Emotion and decision making: multiple modulatory neural circuits",
  author   = "Phelps, Elizabeth A and Lempert, Karolina M and Sokol-Hessner,
              Peter",
  abstract = "Although the prevalent view of emotion and decision making is
              derived from the notion that there are dual systems of emotion
              and reason, a modulatory relationship more accurately reflects
              the current research in affective neuroscience and
              neuroeconomics. Studies show two potential mechanisms for
              affect's modulation of the computation of subjective value and
              decisions. Incidental affective states may carry over to the
              assessment of subjective value and the decision, and emotional
              reactions to the choice may be incorporated into the value
              calculation. In addition, this modulatory relationship is
              reciprocal: Changing emotion can change choices. This research
              suggests that the neural mechanisms mediating the relation
              between affect and choice vary depending on which affective
              component is engaged and which decision variables are assessed.
              We suggest that a detailed and nuanced understanding of emotion
              and decision making requires characterizing the multiple
              modulatory neural circuits underlying the different means by
              which emotion and affect can influence choices.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  37,
  pages    = "263--287",
  month    =  may,
  year     =  2014,
  keywords = "amygdala; insular cortex; mood; orbitofrontal cortex; stress;
              striatum",
  language = "en"
}

@ARTICLE{Geva-Sagiv2015-cl,
  title    = "Spatial cognition in bats and rats: from sensory acquisition to
              multiscale maps and navigation",
  author   = "Geva-Sagiv, Maya and Las, Liora and Yovel, Yossi and Ulanovsky,
              Nachum",
  abstract = "Spatial orientation and navigation rely on the acquisition of
              several types of sensory information. This information is then
              transformed into a neural code for space in the hippocampal
              formation through the activity of place cells, grid cells and
              head-direction cells. These spatial representations, in turn, are
              thought to guide long-range navigation. But how the
              representations encoded by these different cell types are
              integrated in the brain to form a neural 'map and compass' is
              largely unknown. Here, we discuss this problem in the context of
              spatial navigation by bats and rats. We review the experimental
              findings and theoretical models that provide insight into the
              mechanisms that link sensory systems to spatial representations
              and to large-scale natural navigation.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  16,
  number   =  2,
  pages    = "94--108",
  month    =  feb,
  year     =  2015,
  language = "en"
}

@ARTICLE{Johnson2009-bx,
  title    = "Looking for cognition in the structure within the noise",
  author   = "Johnson, Adam and Fenton, Andr{\'e} A and Kentros, Cliff and
              Redish, A David",
  abstract = "Neural activity in the mammalian CNS is determined by both
              observable processes, such as sensory stimuli or motor output,
              and covert, internal cognitive processes that cannot be directly
              observed. We propose methods to identify these cognitive
              processes by examining the covert structure within the apparent
              'noise' in spike trains. Contemporary analyses of neural codes
              include encoding (tuning curves derived from spike trains and
              behavioral, sensory or motor variables), decoding (reconstructing
              behavioral, sensory or motor variables from spike trains and
              hypothesized tuning curves) and generative models (predicting the
              spike trains from hypothesized encoding models and decoded
              variables). We review examples of each of these processes in
              hippocampal activity, and propose a general methodology to
              examine cognitive processes via the identification of dynamic
              changes in covert variables.",
  journal  = "Trends Cogn. Sci.",
  volume   =  13,
  number   =  2,
  pages    = "55--64",
  month    =  feb,
  year     =  2009,
  language = "en"
}

@ARTICLE{Mysore2011-fr,
  title    = "The role of a midbrain network in competitive stimulus selection",
  author   = "Mysore, Shreesh P and Knudsen, Eric I",
  abstract = "A midbrain network interacts with the well-known frontoparietal
              forebrain network to select stimuli for gaze and spatial
              attention. The midbrain network, containing the superior
              colliculus (SC; optic tectum, OT, in non-mammalian vertebrates)
              and the isthmic nuclei, helps evaluate the relative priorities of
              competing stimuli and encodes them in a topographic map of space.
              Behavioral experiments in monkeys demonstrate an essential
              contribution of the SC to stimulus selection when the relative
              priorities of competing stimuli are similar. Neurophysiological
              results from the owl OT demonstrate a neural correlate of this
              essential contribution of the SC/OT. The multi-layered,
              spatiotopic organization of the midbrain network lends itself to
              the analysis and modeling of the mechanisms underlying stimulus
              selection for gaze and spatial attention.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  21,
  number   =  4,
  pages    = "653--660",
  month    =  aug,
  year     =  2011,
  language = "en"
}

@ARTICLE{Cisek2010-ke,
  title    = "Neural mechanisms for interacting with a world full of action
              choices",
  author   = "Cisek, Paul and Kalaska, John F",
  abstract = "The neural bases of behavior are often discussed in terms of
              perceptual, cognitive, and motor stages, defined within an
              information processing framework that was originally inspired by
              models of human abstract problem solving. Here, we review a
              growing body of neurophysiological data that is difficult to
              reconcile with this influential theoretical perspective. As an
              alternative foundation for interpreting neural data, we consider
              frameworks borrowed from ethology, which emphasize the kinds of
              real-time interactive behaviors that animals have engaged in for
              millions of years. In particular, we discuss an
              ethologically-inspired view of interactive behavior as
              simultaneous processes that specify potential motor actions and
              select between them. We review how recent neurophysiological data
              from diverse cortical and subcortical regions appear more
              compatible with this parallel view than with the classical view
              of serial information processing stages.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  33,
  pages    = "269--298",
  year     =  2010,
  language = "en"
}

@ARTICLE{Koene2003-ep,
  title    = "Modeling goal-directed spatial navigation in the rat based on
              physiological data from the hippocampal formation",
  author   = "Koene, Randal A and Gorchetchnikov, Anatoli and Cannon, Robert C
              and Hasselmo, Michael E",
  abstract = "We investigated the importance of hippocampal theta oscillations
              and the significance of phase differences of theta modulation in
              the cortical regions that are involved in goal-directed spatial
              navigation. Our models used representations of entorhinal cortex
              layer III (ECIII), hippocampus and prefrontal cortex (PFC) to
              guide movements of a virtual rat in a virtual environment. The
              model encoded representations of the environment through
              long-term potentiation of excitatory recurrent connections
              between sequentially spiking place cells in ECIII and CA3. This
              encoding required buffering of place cell activity, which was
              achieved by a short-term memory (STM) in EC that was regulated by
              theta modulation and allowed synchronized reactivation with
              encoding phases in ECIII and CA3. Inhibition at a specific theta
              phase deactivated the oldest item in the buffer when new input
              was presented to a full STM buffer. A 180 degrees phase
              difference separated retrieval and encoding in ECIII and CA3,
              which enabled us to simulate data on theta phase precession of
              place cells. Retrieval of known paths was elicited in ECIII by
              input at the retrieval phase from PFC working memory for goal
              location, requiring strict theta phase relationships with PFC.
              Known locations adjacent to the virtual rat were retrieved in
              CA3. Together, input from ECIII and CA3 activated predictive
              spiking in cells in CA1 for the next desired place on a shortest
              path to a goal. Consistent with data, place cell activity in CA1
              and CA3 showed smaller place fields than in ECIII.",
  journal  = "Neural Netw.",
  volume   =  16,
  number   = "5-6",
  pages    = "577--584",
  month    =  jun,
  year     =  2003,
  language = "en"
}

@ARTICLE{Van_Strien2009-yf,
  title    = "The anatomy of memory: an interactive overview of the
              parahippocampal-hippocampal network",
  author   = "van Strien, N M and Cappaert, N L M and Witter, M P",
  abstract = "Converging evidence suggests that each parahippocampal and
              hippocampal subregion contributes uniquely to the encoding,
              consolidation and retrieval of declarative memories, but their
              precise roles remain elusive. Current functional thinking does
              not fully incorporate the intricately connected networks that
              link these subregions, owing to their organizational complexity;
              however, such detailed anatomical knowledge is of pivotal
              importance for comprehending the unique functional contribution
              of each subregion. We have therefore developed an interactive
              diagram with the aim to display all of the currently known
              anatomical connections of the rat parahippocampal-hippocampal
              network. In this Review, we integrate the existing anatomical
              knowledge into a concise description of this network and discuss
              the functional implications of some relatively underexposed
              connections.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  10,
  number   =  4,
  pages    = "272--282",
  month    =  apr,
  year     =  2009,
  language = "en"
}

@ARTICLE{Oh2014-ws,
  title    = "A mesoscale connectome of the mouse brain",
  author   = "Oh, Seung Wook and Harris, Julie A and Ng, Lydia and Winslow,
              Brent and Cain, Nicholas and Mihalas, Stefan and Wang, Quanxin
              and Lau, Chris and Kuan, Leonard and Henry, Alex M and Mortrud,
              Marty T and Ouellette, Benjamin and Nguyen, Thuc Nghi and
              Sorensen, Staci A and Slaughterbeck, Clifford R and Wakeman,
              Wayne and Li, Yang and Feng, David and Ho, Anh and Nicholas, Eric
              and Hirokawa, Karla E and Bohn, Phillip and Joines, Kevin M and
              Peng, Hanchuan and Hawrylycz, Michael J and Phillips, John W and
              Hohmann, John G and Wohnoutka, Paul and Gerfen, Charles R and
              Koch, Christof and Bernard, Amy and Dang, Chinh and Jones, Allan
              R and Zeng, Hongkui",
  abstract = "Comprehensive knowledge of the brain's wiring diagram is
              fundamental for understanding how the nervous system processes
              information at both local and global scales. However, with the
              singular exception of the C. elegans microscale connectome, there
              are no complete connectivity data sets in other species. Here we
              report a brain-wide, cellular-level, mesoscale connectome for the
              mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced
              green fluorescent protein (EGFP)-expressing adeno-associated
              viral vectors to trace axonal projections from defined regions
              and cell types, and high-throughput serial two-photon tomography
              to image the EGFP-labelled axons throughout the brain. This
              systematic and standardized approach allows spatial registration
              of individual experiments into a common three dimensional (3D)
              reference space, resulting in a whole-brain connectivity matrix.
              A computational model yields insights into connectional strength
              distribution, symmetry and other network properties. Virtual
              tractography illustrates 3D topography among interconnected
              regions. Cortico-thalamic pathway analysis demonstrates
              segregation and integration of parallel pathways. The Allen Mouse
              Brain Connectivity Atlas is a freely available, foundational
              resource for structural and functional investigations into the
              neural circuits that support behavioural and cognitive processes
              in health and disease.",
  journal  = "Nature",
  volume   =  508,
  number   =  7495,
  pages    = "207--214",
  month    =  apr,
  year     =  2014,
  language = "en"
}

@ARTICLE{Sofroniew2014-mh,
  title    = "Natural whisker-guided behavior by head-fixed mice in tactile
              virtual reality",
  author   = "Sofroniew, Nicholas J and Cohen, Jeremy D and Lee, Albert K and
              Svoboda, Karel",
  abstract = "During many natural behaviors the relevant sensory stimuli and
              motor outputs are difficult to quantify. Furthermore, the high
              dimensionality of the space of possible stimuli and movements
              compounds the problem of experimental control. Head fixation
              facilitates stimulus control and movement tracking, and can be
              combined with techniques for recording and manipulating neural
              activity. However, head-fixed mouse behaviors are typically
              trained through extensive instrumental conditioning. Here we
              present a whisker-based, tactile virtual reality system for
              head-fixed mice running on a spherical treadmill. Head-fixed mice
              displayed natural movements, including running and rhythmic
              whisking at 16 Hz. Whisking was centered on a set point that
              changed in concert with running so that more protracted whisking
              was correlated with faster running. During turning, whiskers
              moved in an asymmetric manner, with more retracted whisker
              positions in the turn direction and protracted whisker movements
              on the other side. Under some conditions, whisker movements were
              phase-coupled to strides. We simulated a virtual reality tactile
              corridor, consisting of two moveable walls controlled in a
              closed-loop by running speed and direction. Mice used their
              whiskers to track the walls of the winding corridor without
              training. Whisker curvature changes, which cause forces in the
              sensory follicles at the base of the whiskers, were tightly
              coupled to distance from the walls. Our behavioral system allows
              for precise control of sensorimotor variables during natural
              tactile navigation.",
  journal  = "J. Neurosci.",
  volume   =  34,
  number   =  29,
  pages    = "9537--9550",
  month    =  jul,
  year     =  2014,
  language = "en"
}

@ARTICLE{Churchland2012-kw,
  title    = "New advances in understanding decisions among multiple
              alternatives",
  author   = "Churchland, Anne K and Ditterich, Jochen",
  abstract = "Experimental studies of decision-making have put a strong
              emphasis on choices between two alternatives. However, real-life
              decisions often involve multiple alternatives. This article
              provides an overview of theoretical frameworks that have been
              proposed to account for behavioral data from both economic and
              perceptual multialternative decision-making. We further review
              recent neurophysiological data collected in conjunction with
              decision-making behavior. These neural recordings provide
              constraints on putative models of the decision mechanism. For
              example, the time course of inhibition provides insight into how
              the competition between alternatives is mediated. Furthermore,
              whereas decision-related neural activity seems to reach a common
              threshold at the end of the decision period, the starting point
              tends to depend systematically on the number of alternatives. We
              discuss candidate mechanisms that could drive the reduction in
              firing rates on decisions among multiple alternatives.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "920--926",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Cain2012-tf,
  title    = "Computational models of decision making: integration, stability,
              and noise",
  author   = "Cain, Nicholas and Shea-Brown, Eric",
  abstract = "Decision making demands the accumulation of sensory evidence over
              time. Questions remain about how this occurs, but recent years
              have seen progress on several fronts. The first concerns when
              optimal accumulation of evidence coincides with the simplest
              method of accumulating neural activity: summation over time. The
              second involves what computations the brain might perform when
              summation is difficult due to imprecision in neural circuits or
              is suboptimal due to uncertainty or variability in how evidence
              arrives. Finally, the third concerns sources of noise in decision
              circuits. Empirical studies have better constrained the extent of
              this noise, and modeling work is helping to clarify its possible
              origins.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "1047--1053",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Wang2012-ac,
  title    = "Neural dynamics and circuit mechanisms of decision-making",
  author   = "Wang, Xiao-Jing",
  abstract = "In this review, I briefly summarize current neurobiological
              studies of decision-making that bear on two general themes. The
              first focuses on the nature of neural representation and dynamics
              in a decision circuit. Experimental and computational results
              suggest that ramping-to-threshold in the temporal domain and
              trajectory of population activity in the state space represent a
              duality of perspectives on a decision process. Moreover, a
              decision circuit can display several different dynamical regimes,
              such as the ramping mode and the jumping mode with distinct
              defining properties. The second is concerned with the
              relationship between biologically-based mechanistic models and
              normative-type models. A fruitful interplay between experiments
              and these models at different levels of abstraction have enabled
              investigators to pose increasingly refined questions and gain new
              insights into the neural basis of decision-making. In particular,
              recent work on multi-alternative decisions suggests that
              deviations from rational models of choice behavior can be
              explained by established neural mechanisms.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "1039--1046",
  month    =  dec,
  year     =  2012
}

@ARTICLE{Adams2012-mw,
  title    = "Neuroethology of decision-making",
  author   = "Adams, Geoffrey K and Watson, Karli K and Pearson, John and
              Platt, Michael L",
  abstract = "A neuroethological approach to decision-making considers the
              effect of evolutionary pressures on neural circuits mediating
              choice. In this view, decision systems are expected to enhance
              fitness with respect to the local environment, and particularly
              efficient solutions to specific problems should be conserved,
              expanded, and repurposed to solve other problems. Here, we
              discuss basic prerequisites for a variety of decision systems
              from this viewpoint. We focus on two of the best-studied and most
              widely represented decision problems. First, we examine patch
              leaving, a prototype of environmentally based switching between
              action patterns. Second, we consider social information seeking,
              a process resembling foraging with search costs. We argue that
              while the specific neural solutions to these problems sometimes
              differ across species, both the problems themselves and the
              algorithms instantiated by biological hardware are repeated
              widely throughout nature. The behavioral and mathematical study
              of ubiquitous decision processes like patch leaving and social
              information seeking thus provides a powerful new approach to
              uncovering the fundamental design structure of nervous systems.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "982--989",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Drugowitsch2012-rd,
  title    = "Probabilistic vs. non-probabilistic approaches to the
              neurobiology of perceptual decision-making",
  author   = "Drugowitsch, Jan and Pouget, Alexandre",
  abstract = "Optimal binary perceptual decision making requires accumulation
              of evidence in the form of a probability distribution that
              specifies the probability of the choices being correct given the
              evidence so far. Reward rates can then be maximized by stopping
              the accumulation when the confidence about either option reaches
              a threshold. Behavioral and neuronal evidence suggests that
              humans and animals follow such a probabilitistic decision
              strategy, although its neural implementation has yet to be fully
              characterized. Here we show that that diffusion decision models
              and attractor network models provide an approximation to the
              optimal strategy only under certain circumstances. In particular,
              neither model type is sufficiently flexible to encode the
              reliability of both the momentary and the accumulated evidence,
              which is a pre-requisite to accumulate evidence of time-varying
              reliability. Probabilistic population codes, by contrast, can
              encode these quantities and, as a consequence, have the potential
              to implement the optimal strategy accurately.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "963--969",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Dehaene2012-xq,
  title    = "From a single decision to a multi-step algorithm",
  author   = "Dehaene, Stanislas and Sigman, Mariano",
  abstract = "Humans can perform sequential and recursive computations, as when
              calculating 23$\times$74. However, this comes at a cost: flexible
              computations are slow and effortful. We argue that this
              competence involves serial chains of successive decisions, each
              based on the accumulation of evidence up to a threshold and
              forwarding the result to the subsequent step. Such serial
              'programs' require a specific neurobiological architecture,
              approximating the operation of a slow serial Turing machine. We
              review recent progress in understanding how the brain implements
              such multi-step decisions and briefly examine how they might be
              realized in models of primate cortex.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "937--945",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Cisek2012-qy,
  title    = "Making decisions through a distributed consensus",
  author   = "Cisek, Paul",
  abstract = "How does the brain decide between actions? Is it through
              comparisons of abstract representations of outcomes or through a
              competition in a sensorimotor map defining the actions
              themselves? Here, I review strengths and limitations of both of
              these proposals, and suggest that decisions emerge through a
              distributed consensus across many levels of representation.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  22,
  number   =  6,
  pages    = "927--936",
  month    =  dec,
  year     =  2012,
  language = "en"
}

@ARTICLE{Chapman2010-dv,
  title    = "Reaching for the unknown: multiple target encoding and real-time
              decision-making in a rapid reach task",
  author   = "Chapman, Craig S and Gallivan, Jason P and Wood, Daniel K and
              Milne, Jennifer L and Culham, Jody C and Goodale, Melvyn A",
  abstract = "Decision-making is central to human cognition. Fundamental to
              every decision is the ability to internally represent the
              available choices and their relative costs and benefits. The most
              basic and frequent decisions we make occur as our motor system
              chooses and executes only those actions that achieve our current
              goals. Although these interactions with the environment may
              appear effortless, this belies what must be incredibly
              sophisticated visuomotor decision-making processes. In order to
              measure how visuomotor decisions unfold in real-time, we used a
              unique reaching paradigm that forced participants to initiate
              rapid hand movements toward multiple potential targets, with only
              one being cued after reach onset. We show across three
              experiments that, in cases of target uncertainty, trajectories
              are spatially sensitive to the probabilistic distribution of
              targets within the display. Specifically, when presented with two
              or three target displays, subjects initiate their reaches toward
              an intermediary or 'averaged' location before correcting their
              trajectory in-flight to the cued target location. A control
              experiment suggests that our effect depends on the targets acting
              as potential reach locations and not as distractors. This study
              is the first to show that the 'averaging' of target-directed
              reaching movements depends not only on the spatial position of
              the targets in the display but also the probability of acting at
              each target location.",
  journal  = "Cognition",
  volume   =  116,
  number   =  2,
  pages    = "168--176",
  month    =  aug,
  year     =  2010,
  language = "en"
}

@ARTICLE{Thura2014-zb,
  title    = "Deliberation and commitment in the premotor and primary motor
              cortex during dynamic decision making",
  author   = "Thura, David and Cisek, Paul",
  abstract = "Neurophysiological studies of decision making have primarily
              focused on decisions about information that is stable over time.
              However, during natural behavior, animals make decisions in a
              constantly changing environment. To investigate the neural
              mechanisms of such dynamic choices, we recorded activity in
              dorsal premotor (PMd) and primary motor cortex (M1) while monkeys
              performed a two-choice reaching task in which sensory information
              about the correct choice was changing within each trial and the
              decision could be made at any time. During deliberation, activity
              in both areas did not integrate sensory information but instead
              tracked it and combined it with a growing urgency signal.
              Approximately 280 ms before movement onset, PMd activity tuned to
              the selected target reached a consistent peak while M1 activity
              tuned to the unselected target was suppressed. We propose that
              this reflects the resolution of a competition between the
              potential responses and constitutes the volitional commitment to
              an action choice.",
  journal  = "Neuron",
  volume   =  81,
  number   =  6,
  pages    = "1401--1416",
  month    =  mar,
  year     =  2014,
  language = "en"
}

@ARTICLE{Klaes2011-hi,
  title    = "Choosing goals, not rules: deciding among rule-based action plans",
  author   = "Klaes, Christian and Westendorff, Stephanie and Chakrabarti,
              Shubhodeep and Gail, Alexander",
  abstract = "In natural situations, movements are often directed toward
              locations different from that of the evoking sensory stimulus.
              Movement goals must then be inferred from the sensory cue based
              on rules. When there is uncertainty about the rule that applies
              for a given cue, planning a movement involves both choosing the
              relevant rule and computing the movement goal based on that rule.
              Under these conditions, it is not clear whether primates compute
              multiple movement goals based on all possible rules before
              choosing an action, or whether they first choose a rule and then
              only represent the movement goal associated with that rule.
              Supporting the former hypothesis, we show that neurons in the
              frontoparietal reach areas of monkeys simultaneously represent
              two different rule-based movement goals, which are biased by the
              monkeys' choice preferences. Apparently, primates choose between
              multiple behavioral options by weighing against each other the
              movement goals associated with each option.",
  journal  = "Neuron",
  volume   =  70,
  number   =  3,
  pages    = "536--548",
  month    =  may,
  year     =  2011,
  language = "en"
}

@ARTICLE{Busemeyer1993-qq,
  title     = "Decision field theory: a dynamic-cognitive approach to decision
               making in an uncertain environment",
  author    = "Busemeyer, J R and Townsend, J T",
  abstract  = "Decision field theory provides for a mathematical foundation
               leading to a dynamic, stochastic theory of decision behavior in
               an uncertain environment. This theory is used to explain (a)
               violations of stochastic dominance, (b) violations of strong
               stochastic transitivity, (c) violations of independence between
               alternatives, (d) serial position effects on preference, (e)
               speed-accuracy trade-off effects in decision making, (f) the
               inverse relation between choice probability and decision time,
               (g) changes in the direction of preference under time pressure,
               (h) slower decision times for avoidance as compared with
               approach conflicts, and (i) preference reversals between choice
               and selling price measures of preference. The proposed theory is
               compared with 4 other theories of decision making under
               uncertainty.",
  journal   = "Psychol. Rev.",
  publisher = "doi.apa.org",
  volume    =  100,
  number    =  3,
  pages     = "432--459",
  month     =  jul,
  year      =  1993,
  language  = "en"
}

@ARTICLE{Basso1998-ng,
  title     = "Modulation of neuronal activity in superior colliculus by
               changes in target probability",
  author    = "Basso, M A and Wurtz, R H",
  abstract  = "Complex visual scenes require that a target for an impending
               saccadic eye movement be selected from a larger number of
               possible targets. We investigated whether changing the
               probability that a visual stimulus would be selected as the
               target for a saccade altered activity of monkey superior
               colliculus (SC) neurons in two experiments. First, we changed
               the number of possible targets on each trial. Second, we kept
               the visual display constant and presented a single saccade
               target repeatedly so that target probability was established
               over time. Buildup neurons in the SC, those with delay period
               activity, showed a consistent reduction in activity as the
               probability of the saccade decreased, independent of the visual
               stimulus configuration. Other SC neurons, fixation and burst,
               were largely unaffected by the changes in saccade target
               probability. Because we had monkeys making saccades to many
               locations within the visual field, we could examine activity
               associated with saccades outside of the movement field of
               neurons. We found the activity of buildup neurons to be similar
               across the SC, before the target was identified, and reduced
               when the number of possible targets increased. The results of
               our experiments are consistent with a role for this activity in
               establishing a motor set. We found, consistent with this
               interpretation, that the activity of these neurons was
               predictive of the latency of a saccadic eye movement and not
               other saccade parameters such as end point or peak velocity.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  18,
  number    =  18,
  pages     = "7519--7534",
  month     =  sep,
  year      =  1998,
  language  = "en"
}

@ARTICLE{Leon1998-oj,
  title    = "Exploring the neurophysiology of decisions",
  author   = "Leon, M I and Shadlen, M N",
  journal  = "Neuron",
  volume   =  21,
  number   =  4,
  pages    = "669--672",
  month    =  oct,
  year     =  1998,
  language = "en"
}

@ARTICLE{Schall2001-zu,
  title    = "Neural basis of deciding, choosing and acting",
  author   = "Schall, J D",
  abstract = "The ability and opportunity to make decisions and carry out
              effective actions in pursuit of goals is central to intelligent
              life. Recent research has provided significant new insights into
              how the brain arrives at decisions, makes choices, and produces
              and evaluates the consequences of actions. In fact, by monitoring
              or manipulating specific neurons, certain choices can now be
              predicted or manipulated.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  2,
  number   =  1,
  pages    = "33--42",
  month    =  jan,
  year     =  2001,
  language = "en"
}

@ARTICLE{Evans2003-qh,
  title    = "In two minds: dual-process accounts of reasoning",
  author   = "Evans, Jonathan St B T",
  abstract = "Researchers in thinking and reasoning have proposed recently that
              there are two distinct cognitive systems underlying reasoning.
              System 1 is old in evolutionary terms and shared with other
              animals: it comprises a set of autonomous subsystems that include
              both innate input modules and domain-specific knowledge acquired
              by a domain-general learning mechanism. System 2 is
              evolutionarily recent and distinctively human: it permits
              abstract reasoning and hypothetical thinking, but is constrained
              by working memory capacity and correlated with measures of
              general intelligence. These theories essentially posit two minds
              in one brain with a range of experimental psychological evidence
              showing that the two systems compete for control of our
              inferences and actions.",
  journal  = "Trends Cogn. Sci.",
  volume   =  7,
  number   =  10,
  pages    = "454--459",
  month    =  oct,
  year     =  2003
}

@ARTICLE{Rangel2008-xe,
  title    = "A framework for studying the neurobiology of value-based decision
              making",
  author   = "Rangel, Antonio and Camerer, Colin and Montague, P Read",
  abstract = "Neuroeconomics is the study of the neurobiological and
              computational basis of value-based decision making. Its goal is
              to provide a biologically based account of human behaviour that
              can be applied in both the natural and the social sciences. This
              Review proposes a framework to investigate different aspects of
              the neurobiology of decision making. The framework allows us to
              bring together recent findings in the field, highlight some of
              the most important outstanding problems, define a common lexicon
              that bridges the different disciplines that inform
              neuroeconomics, and point the way to future applications.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  9,
  number   =  7,
  pages    = "545--556",
  month    =  jul,
  year     =  2008,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@MISC{Tamprateep2017-bd,
  title        = "Of Mice and Man",
  author       = "Tamprateep, V",
  abstract     = "… As mentioned, we considered two datasets, featuring
                  different maze environments, from Jeremy Freeman and Nicholas
                  Sofroniew at Janelia Research Campus. These two datasets
                  consisted of one maze each. To create a discrete task, these
                  mazes were discretized …",
  publisher    = "pdfs.semanticscholar.org",
  year         =  2017,
  howpublished = "\url{https://pdfs.semanticscholar.org/e3a0/b91f0dbf28afcc608ba7190e7bf941693510.pdf}",
  note         = "Accessed: 2018-11-23"
}

@UNPUBLISHED{Steinmetz2018-zx,
  title    = "Distributed correlates of visually-guided behavior across the
              mouse brain",
  author   = "Steinmetz, Nicholas and Zatka-Haas, Peter and Carandini, Matteo
              and Harris, Kenneth",
  abstract = "Behavior arises from neuronal activity, but it is not known how
              the active neurons are distributed across brain regions and how
              their activity unfolds in time. Here, we used high-density
              Neuropixels probes to record from ~30,000 neurons in mice
              performing a visual contrast discrimination task. The task
              activated 60\% of the neurons, involving nearly all 42 recorded
              brain regions, well beyond the regions activated by passive
              visual stimulation. However, neurons selective for choice (left
              vs. right) were rare, and found mostly in midbrain, striatum, and
              frontal cortex. Those in midbrain were typically activated prior
              to contralateral choices and suppressed prior to ipsilateral
              choices, consistent with a competitive midbrain circuit for
              adjudicating the subject9s choice. A brain-wide state shift
              distinguished trials in which visual stimuli led to movement.
              These results reveal concurrent representations of movement and
              choice in neurons widely distributed across the brain.",
  journal  = "bioRxiv",
  pages    = "474437",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Hok2018-di,
  title    = "A spatial code in the dorsal lateral geniculate nucleus",
  author   = "Hok, Vincent and Jacob, Pierre-Yves and Bordiga, Pierrick and
              Truchet, Bruno and Poucet, Bruno and Save, Etienne",
  abstract = "Since their discovery in the early 970s, hippocampal place cells
              have been studied in numerous animal and human spatial memory
              paradigms. These pyramidal cells, along with other spatially
              tuned types of neurons (e.g. grid cells, head direction cells),
              are thought to provide the mammalian brain a unique spatial
              signature characterizing a specific environment, and thereby a
              memory trace of the subject9s place. While grid and head
              direction cells are found in various brain regions, only few
              hippocampal-related structures showing 9place cell9-like neurons
              have been identified, thus reinforcing the central role of the
              hippocampus in spatial memory. Concurrently, it is increasingly
              suggested that visual areas play an important role in spatial
              cognition as recent studies showed a clear spatial selectivity of
              visual cortical (V1) neurons in freely moving rodents. We
              therefore thought to investigate, in the rat, such spatial
              correlates in a thalamic structure located one synapse upstream
              of V1, the dorsal Lateral Geniculate Nucleus (dLGN), and
              discovered that a substantial proportion (ca. 30\%) of neurons
              exhibits spatio-selective activity. We found that dLGN place
              cells maintain their spatial selectivity in the absence of visual
              inputs, presumably relying on odor and locomotor inputs. We also
              found that dLGN place cells maintain their place selectivity
              across sessions in a familiar environment and that contextual
              modifications yield separated representations. Our results show
              that dLGN place cells are likely to participate in spatial
              cognition processes, creating as early as the thalamic stage a
              comprehensive representation of one given environment.",
  journal  = "bioRxiv",
  pages    = "473520",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Long2018-zl,
  title    = "A novel somatosensory spatial navigation system outside the
              hippocampal formation",
  author   = "Long, Xiaoyang and Zhang, Sheng-Jia",
  abstract = "The hippocampal-parahippocampal formation has long been regarded
              as the only site for the brain9s navigational system.
              Nevertheless, studies from patients with medial temporal lobe
              (MTL) lesions suggest that the hippocampal formation is not
              essential for space memory, indicating that spatial navigation
              might be computed with another unknown representation system
              outside the MTL. Such an extra-hippocampal navigational system
              has never been identified, however. Here we report the existence,
              in the rat somatosensory cortex only, of a novel navigational
              system, which contains the full spectrum of all distinct spatial
              cell types including place, head-direction, border/boundary,
              conjunctive, speed and grid cells. All somatosensory spatial
              cells show similar firing characteristics to those detected
              previously in the hippocampal-parahippocampal structures. The
              somatosensory navigational system extends the classical theory of
              a cognitive map from two discrete hippocampal-entorhinal regions
              to only one neocortical domain, providing possible alternative
              and more sophisticated computational algorithms for spatial
              memory and cognitive mapping.",
  journal  = "bioRxiv",
  pages    = "473090",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@ARTICLE{Johnson2007-ri,
  title     = "Integrating hippocampus and striatum in decision-making",
  author    = "Johnson, Adam and van der Meer, Matthijs A A and Redish, A David",
  abstract  = "Learning and memory and navigation literatures emphasize
               interactions between multiple memory systems: a flexible,
               planning-based system and a rigid, cached-value system. This has
               profound implications for decision-making. Recent
               conceptualizations of flexible decision-making employ
               prospection and projection arising from a network involving the
               hippocampus. Recent recordings from rodent hippocampus in
               decision-making situations have found transient forward-shifted
               representations. Evaluation of that prediction and subsequent
               action-selection probably occurs downstream (e.g. in
               orbitofrontal cortex, in ventral and dorsomedial striatum).
               Classically, striatum has been identified as a crucial component
               of the less-flexible, incremental system. Current evidence,
               however, suggests that striatum is involved in both flexible and
               stimulus-response decision-making, with dorsolateral striatum
               involved in stimulus-response strategies and ventral and
               dorsomedial striatum involved in goal-directed strategies.",
  journal   = "Curr. Opin. Neurobiol.",
  publisher = "Elsevier",
  volume    =  17,
  number    =  6,
  pages     = "692--697",
  month     =  dec,
  year      =  2007,
  language  = "en"
}

@ARTICLE{Gupta2010-gx,
  title     = "Hippocampal replay is not a simple function of experience",
  author    = "Gupta, Anoopum S and van der Meer, Matthijs A A and Touretzky,
               David S and Redish, A David",
  abstract  = "Replay of behavioral sequences in the hippocampus during sharp
               wave ripple complexes (SWRs) provides a potential mechanism for
               memory consolidation and the learning of knowledge structures.
               Current hypotheses imply that replay should straightforwardly
               reflect recent experience. However, we find these hypotheses to
               be incompatible with the content of replay on a task with two
               distinct behavioral sequences (A and B). We observed forward and
               backward replay of B even when rats had been performing A for
               >10 min. Furthermore, replay of nonlocal sequence B occurred
               more often when B was infrequently experienced. Neither forward
               nor backward sequences preferentially represented highly
               experienced trajectories within a session. Additionally, we
               observed the construction of never-experienced novel-path
               sequences. These observations challenge the idea that sequence
               activation during SWRs is a simple replay of recent experience.
               Instead, replay reflected all physically available trajectories
               within the environment, suggesting a potential role in active
               learning and maintenance of the cognitive map.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  65,
  number    =  5,
  pages     = "695--705",
  month     =  mar,
  year      =  2010,
  language  = "en"
}

@ARTICLE{Wu2014-ud,
  title    = "Hippocampal replay captures the unique topological structure of a
              novel environment",
  author   = "Wu, Xiaojing and Foster, David J",
  abstract = "Hippocampal place-cell replay has been proposed as a fundamental
              mechanism of learning and memory, which might support
              navigational learning and planning. An important hypothesis of
              relevance to these proposed functions is that the information
              encoded in replay should reflect the topological structure of
              experienced environments; that is, which places in the
              environment are connected with which others. Here we report
              several attributes of replay observed in rats exploring a novel
              forked environment that support the hypothesis. First, we
              observed that overlapping replays depicting divergent
              trajectories through the fork recruited the same population of
              cells with the same firing rates to represent the common portion
              of the trajectories. Second, replay tended to be directional and
              to flip the represented direction at the fork. Third,
              replay-associated sharp-wave-ripple events in the local field
              potential exhibited substructure that mapped onto the maze
              topology. Thus, the spatial complexity of our recording
              environment was accurately captured by replay: the underlying
              neuronal activities reflected the bifurcating shape, and both
              directionality and associated ripple structure reflected the
              segmentation of the maze. Finally, we observed that replays
              occurred rapidly after small numbers of experiences. Our results
              suggest that hippocampal replay captures learned information
              about environmental topology to support a role in navigation.",
  journal  = "J. Neurosci.",
  volume   =  34,
  number   =  19,
  pages    = "6459--6469",
  month    =  may,
  year     =  2014,
  language = "en"
}

@ARTICLE{Dragoi2011-ty,
  title     = "Preplay of future place cell sequences by hippocampal cellular
               assemblies",
  author    = "Dragoi, George and Tonegawa, Susumu",
  abstract  = "During spatial exploration, hippocampal neurons show a
               sequential firing pattern in which individual neurons fire
               specifically at particular locations along the animal's
               trajectory (place cells). According to the dominant model of
               hippocampal cell assembly activity, place cell firing order is
               established for the first time during exploration, to encode the
               spatial experience, and is subsequently replayed during rest or
               slow-wave sleep for consolidation of the encoded experience.
               Here we report that temporal sequences of firing of place cells
               expressed during a novel spatial experience occurred on a
               significant number of occasions during the resting or sleeping
               period preceding the experience. This phenomenon, which is
               called preplay, occurred in disjunction with sequences of replay
               of a familiar experience. These results suggest that internal
               neuronal dynamics during resting or sleep organize hippocampal
               cellular assemblies into temporal sequences that contribute to
               the encoding of a related novel experience occurring in the
               future.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  469,
  number    =  7330,
  pages     = "397--401",
  month     =  jan,
  year      =  2011,
  language  = "en"
}

@ARTICLE{Barron2013-ho,
  title     = "Online evaluation of novel choices by simultaneous
               representation of multiple memories",
  author    = "Barron, Helen C and Dolan, Raymond J and Behrens, Timothy E J",
  abstract  = "Prior experience is critical for decision-making. It enables
               explicit representation of potential outcomes and provides
               training to valuation mechanisms. However, we can also make
               choices in the absence of prior experience by merely imagining
               the consequences of a new experience. Using functional magnetic
               resonance imaging repetition suppression in humans, we examined
               how neuronal representations of novel rewards can be constructed
               and evaluated. A likely novel experience was constructed by
               invoking multiple independent memories in hippocampus and medial
               prefrontal cortex. This construction persisted for only a short
               time period, during which new associations were observed between
               the memories for component items. Together, these findings
               suggest that, in the absence of direct experience, coactivation
               of multiple relevant memories can provide a training signal to
               the valuation system that allows the consequences of new
               experiences to be imagined and acted on.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  16,
  number    =  10,
  pages     = "1492--1498",
  month     =  oct,
  year      =  2013,
  language  = "en"
}

@ARTICLE{Olafsdottir2015-dj,
  title     = "Hippocampal place cells construct reward related sequences
               through unexplored space",
  author    = "{\'O}lafsd{\'o}ttir, H Freyja and Barry, Caswell and Saleem,
               Aman B and Hassabis, Demis and Spiers, Hugo J",
  abstract  = "Dominant theories of hippocampal function propose that place
               cell representations are formed during an animal's first
               encounter with a novel environment and are subsequently replayed
               during off-line states to support consolidation and future
               behaviour. Here we report that viewing the delivery of food to
               an unvisited portion of an environment leads to off-line
               pre-activation of place cells sequences corresponding to that
               space. Such 'preplay' was not observed for an unrewarded but
               otherwise similar portion of the environment. These results
               suggest that a hippocampal representation of a visible, yet
               unexplored environment can be formed if the environment is of
               motivational relevance to the animal. We hypothesise such
               goal-biased preplay may support preparation for future
               experiences in novel environments.",
  journal   = "Elife",
  publisher = "cdn.elifesciences.org",
  volume    =  4,
  pages     = "e06063",
  month     =  jun,
  year      =  2015,
  keywords  = "consolidation; hippocampus; neuroscience; place cells; preplay;
               rat; replay; spatial memory",
  language  = "en"
}

@ARTICLE{Foster2017-ss,
  title     = "Replay Comes of Age",
  author    = "Foster, David J",
  abstract  = "Hippocampal place cells take part in sequenced patterns of
               reactivation after behavioral experience, known as replay. Since
               replay was first reported, nearly 20 years ago, many new results
               have been found, necessitating revision of the original
               interpretations. We review some of these results with a focus on
               the phenomenology of replay.",
  journal   = "Annu. Rev. Neurosci.",
  publisher = "annualreviews.org",
  volume    =  40,
  pages     = "581--602",
  month     =  jul,
  year      =  2017,
  keywords  = "hippocampus; memory; place cell; replay",
  language  = "en"
}

@ARTICLE{Daw2005-hs,
  title     = "Uncertainty-based competition between prefrontal and
               dorsolateral striatal systems for behavioral control",
  author    = "Daw, Nathaniel D and Niv, Yael and Dayan, Peter",
  abstract  = "A broad range of neural and behavioral data suggests that the
               brain contains multiple systems for behavioral choice, including
               one associated with prefrontal cortex and another with
               dorsolateral striatum. However, such a surfeit of control raises
               an additional choice problem: how to arbitrate between the
               systems when they disagree. Here, we consider dual-action choice
               systems from a normative perspective, using the computational
               theory of reinforcement learning. We identify a key trade-off
               pitting computational simplicity against the flexible and
               statistically efficient use of experience. The trade-off is
               realized in a competition between the dorsolateral striatal and
               prefrontal systems. We suggest a Bayesian principle of
               arbitration between them according to uncertainty, so each
               controller is deployed when it should be most accurate. This
               provides a unifying account of a wealth of experimental evidence
               about the factors favoring dominance by either system.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  8,
  number    =  12,
  pages     = "1704--1711",
  month     =  dec,
  year      =  2005,
  language  = "en"
}

@ARTICLE{Redish1997-pq,
  title     = "Cognitive maps beyond the hippocampus",
  author    = "Redish, A D and Touretzky, D S",
  abstract  = "We present a conceptual framework for the role of the
               hippocampus and its afferent and efferent structures in rodent
               navigation. Our proposal is compatible with the behavioral,
               neurophysiological, anatomical, and neuropharmacological
               literature, and suggests a number of practical experiments that
               could support or refute it. We begin with a review of place
               cells and how the place code for an environment might be aligned
               with sensory cues and updated by self-motion information. The
               existence of place fields in the dark suggests that location
               information is maintained by path integration, which requires an
               internal representation of direction of motion. This leads to a
               consideration of the organization of the rodent head direction
               system, and thence into a discussion of the computational
               structure and anatomical locus of the path integrator. If the
               place code is used in navigation, there must be a mechanism for
               selecting an action based on this information. We review
               evidence that the nucleus accumbens subserves this function.
               From there, we move to interactions between the hippocampal
               system and the environment, emphasizing mechanisms for learning
               novel environments and for aligning the various subsystems upon
               re-entry into familiar environments. We conclude with a
               discussion of the relationship between navigation and
               declarative memory.",
  journal   = "Hippocampus",
  publisher = "Wiley Online Library",
  volume    =  7,
  number    =  1,
  pages     = "15--35",
  year      =  1997,
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Tolman1948-ym,
  title     = "Cognitive maps in rats and men",
  author    = "Tolman, E C",
  abstract  = "This paper is devoted to a description of experiments with rats,
               mostly at the author's laboratory, and to indicating the
               significance of these findings on rats for the clinical behavior
               of men. While all students agree as to the facts reported, they
               disagree on theory and …",
  journal   = "Psychol. Rev.",
  publisher = "psycnet.apa.org",
  volume    =  55,
  number    =  4,
  pages     = "189--208",
  month     =  jul,
  year      =  1948,
  keywords  = "CONDITIONING THERAPY",
  language  = "en"
}

@ARTICLE{Kepecs2008-ys,
  title    = "Neural correlates, computation and behavioural impact of decision
              confidence",
  author   = "Kepecs, Adam and Uchida, Naoshige and Zariwala, Hatim A and
              Mainen, Zachary F",
  abstract = "Humans and other animals must often make decisions on the basis
              of imperfect evidence. Statisticians use measures such as P
              values to assign degrees of confidence to propositions, but
              little is known about how the brain computes confidence estimates
              about decisions. We explored this issue using behavioural
              analysis and neural recordings in rats in combination with
              computational modelling. Subjects were trained to perform an
              odour categorization task that allowed decision confidence to be
              manipulated by varying the distance of the test stimulus to the
              category boundary. To understand how confidence could be computed
              along with the choice itself, using standard models of
              decision-making, we defined a simple measure that quantified the
              quality of the evidence contributing to a particular decision.
              Here we show that the firing rates of many single neurons in the
              orbitofrontal cortex match closely to the predictions of
              confidence models and cannot be readily explained by alternative
              mechanisms, such as learning stimulus-outcome associations.
              Moreover, when tested using a delayed reward version of the task,
              we found that rats' willingness to wait for rewards increased
              with confidence, as predicted by the theoretical model. These
              results indicate that confidence estimates, previously suggested
              to require 'metacognition' and conscious awareness are available
              even in the rodent brain, can be computed with relatively simple
              operations, and can drive adaptive behaviour. We suggest that
              confidence estimation may be a fundamental and ubiquitous
              component of decision-making.",
  journal  = "Nature",
  volume   =  455,
  number   =  7210,
  pages    = "227--231",
  month    =  sep,
  year     =  2008,
  language = "en"
}

@ARTICLE{Mattar2018-ro,
  title    = "Prioritized memory access explains planning and hippocampal
              replay",
  author   = "Mattar, Marcelo G and Daw, Nathaniel D",
  abstract = "To make decisions, animals must evaluate candidate choices by
              accessing memories of relevant experiences. Yet little is known
              about which experiences are considered or ignored during
              deliberation, which ultimately governs choice. We propose a
              normative theory predicting which memories should be accessed at
              each moment to optimize future decisions. Using nonlocal 'replay'
              of spatial locations in hippocampus as a window into memory
              access, we simulate a spatial navigation task in which an agent
              accesses memories of locations sequentially, ordered by utility:
              how much extra reward would be earned due to better choices. This
              prioritization balances two desiderata: the need to evaluate
              imminent choices versus the gain from propagating newly
              encountered information to preceding locations. Our theory offers
              a simple explanation for numerous findings about place cells;
              unifies seemingly disparate proposed functions of replay
              including planning, learning, and consolidation; and posits a
              mechanism whose dysfunction may underlie pathologies like
              rumination and craving.",
  journal  = "Nat. Neurosci.",
  volume   =  21,
  number   =  11,
  pages    = "1609--1617",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@ARTICLE{Daw2018-vt,
  title    = "Are we of two minds?",
  author   = "Daw, Nathaniel D",
  journal  = "Nat. Neurosci.",
  volume   =  21,
  number   =  11,
  pages    = "1497--1499",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@ARTICLE{Vander_Weele2018-qt,
  title    = "Dopamine enhances signal-to-noise ratio in cortical-brainstem
              encoding of aversive stimuli",
  author   = "Vander Weele, Caitlin M and Siciliano, Cody A and Matthews,
              Gillian A and Namburi, Praneeth and Izadmehr, Ehsan M and
              Espinel, Isabella C and Nieh, Edward H and Schut, Evelien H S and
              Padilla-Coreano, Nancy and Burgos-Robles, Anthony and Chang,
              Chia-Jung and Kimchi, Eyal Y and Beyeler, Anna and Wichmann, Romy
              and Wildes, Craig P and Tye, Kay M",
  abstract = "Dopamine modulates medial prefrontal cortex (mPFC) activity to
              mediate diverse behavioural functions1,2; however, the precise
              circuit computations remain unknown. One potentially unifying
              model by which dopamine may underlie a diversity of functions is
              by modulating the signal-to-noise ratio in subpopulations of mPFC
              neurons3-6, where neural activity conveying sensory information
              (signal) is amplified relative to spontaneous firing (noise).
              Here we demonstrate that dopamine increases the signal-to-noise
              ratio of responses to aversive stimuli in mPFC neurons projecting
              to the dorsal periaqueductal grey (dPAG). Using an
              electrochemical approach, we reveal the precise time course of
              pinch-evoked dopamine release in the mPFC, and show that mPFC
              dopamine biases behavioural responses to aversive stimuli.
              Activation of mPFC-dPAG neurons is sufficient to drive place
              avoidance and defensive behaviours. mPFC-dPAG neurons display
              robust shock-induced excitations, as visualized by single-cell,
              projection-defined microendoscopic calcium imaging. Finally,
              photostimulation of dopamine terminals in the mPFC reveals an
              increase in the signal-to-noise ratio in mPFC-dPAG responses to
              aversive stimuli. Together, these data highlight how dopamine in
              the mPFC can selectively route sensory information to specific
              downstream circuits, representing a potential circuit mechanism
              for valence processing.",
  journal  = "Nature",
  volume   =  563,
  number   =  7731,
  pages    = "397--401",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Bagur2018-lr,
  title    = "Dissociation of fear initiation and maintenance by
              breathing-driven prefrontal oscillations",
  author   = "Bagur, Sophie and Lefort, Julie M and Lacroix, Marie M and de
              Lavilleon, Gaetan and Herry, Cyril and Billand, Clara and
              Geoffroy, Helene and Benchenane, Karim",
  abstract = "Does the body play an active role in emotions? Since the original
              James/Cannon controversy this debate has mainly been fueled by
              introspective accounts of human experience. Here, we use the
              animal model to demonstrate a physiological mechanism for bodily
              feedback and its causal role in the stabilization of emotional
              states. We report that during fear-related freezing mice breathe
              at 4Hz and show, using probabilistic modelling, that optogenetic
              perturbation of this feedback specifically reduces freezing
              maintenance without impacting its initiation. This rhythm is
              transmitted by the olfactory bulb to the prefrontal cortex where
              it organizes neural firing and optogenetic probing of the circuit
              demonstrates frequency-specific tuning that maximizes prefrontal
              cortex responsivity at 4Hz, the breathing frequency during
              freezing. These results point to a brain-body-brain loop in which
              the initiation of emotional behavior engenders somatic changes
              which then feedback to the cortex to directly participate in
              sustaining emotional states.",
  journal  = "bioRxiv",
  pages    = "468264",
  month    =  nov,
  year     =  2018,
  language = "en"
}

@ARTICLE{Webb2001-kg,
  title    = "Can robots make good models of biological behaviour?",
  author   = "Webb, B",
  abstract = "UNLABELLED: How should biological behaviour be modelled? A
              relatively new approach is to investigate problems in
              neuroethology by building physical robot models of biological
              sensorimotor systems. The explication and justification of this
              approach are here placed within a framework for describing and
              comparing models in the behavioural and biological sciences.
              First, simulation models--the representation of a hypothesis
              about a target system--are distinguished from several other
              relationships also termed ``modelling'' in discussions of
              scientific explanation. Seven dimensions on which simulation
              models can differ are defined and distinctions between them
              discussed: 1. RELEVANCE: whether the model tests and generates
              hypotheses applicable to biology. 2. Level: the elemental units
              of the model in the hierarchy from atoms to societies. 3.
              Generality: the range of biological systems the model can
              represent. 4. Abstraction: the complexity, relative to the
              target, or amount of detail included in the model. 5. Structural
              accuracy: how well the model represents the actual mechanisms
              underlying the behaviour. 6. Performance match: to what extent
              the model behaviour matches the target behaviour. 7. Medium: the
              physical basis by which the model is implemented. No specific
              position in the space of models thus defined is the only correct
              one, but a good modelling methodology should be explicit about
              its position and the justification for that position. It is
              argued that in building robot models biological relevance is more
              effective than loose biological inspiration; multiple levels can
              be integrated; that generality cannot be assumed but might emerge
              from studying specific instances; abstraction is better done by
              simplification than idealisation; accuracy can be approached
              through iterations of complete systems; that the model should be
              able to match and predict target behaviour; and that a physical
              medium can have significant advantages. These arguments reflect
              the view that biological behaviour needs to be studied and
              modelled in context, that is, in terms of the real problems faced
              by real animals in real environments.",
  journal  = "Behav. Brain Sci.",
  volume   =  24,
  number   =  6,
  pages    = "1033--50; discussion 1050--94",
  month    =  dec,
  year     =  2001,
  language = "en"
}

@ARTICLE{Webb2009-nq,
  title     = "Animals Versus Animats: Or Why Not Model the Real Iguana?",
  author    = "Webb, Barbara",
  abstract  = "The overlapping fields of adaptive behavior and artificial life
               are often described as novel approaches to biology. They focus
               attention on bottom-up explanations and how lifelike phenomena
               can result from relatively simple systems interacting
               dynamically with their environments. They are also characterized
               by the use of synthetic methodologies, that is, building
               artificial systems as a means of exploring these ideas. Two
               differing approaches can be distinguished: building models of
               specific animal systems and assessing them within complete
               behavior?environment loops; and exploring the behavior of
               invented artificial animals, often called animats, under similar
               conditions. An obvious question about the latter approach is,
               how can we learn about real biology from simulation of
               non-existent animals? In this article I will argue, first, that
               animat research, to the extent that it is relevant to biology,
               should also be considered as model building. Animat simulations
               do, implicitly, represent hypotheses about, and should be
               evaluated by comparison to, animals. Casting this research in
               terms of invented agents serves only to limit the ability to
               draw useful conclusions from it by deflecting or deferring any
               serious comparisons of the model mechanisms and results with
               real biological systems. Claims that animat models are meant to
               be existence proofs, idealizations, or represent general
               problems in biology do not make these models qualitatively
               different from more conventional models of specific animals, nor
               undermine the ultimate requirement to justify this work by
               making concrete comparisons with empirical data. It is thus
               suggested that we will learn more by choosing real, and not
               made-up, targets for our models.",
  journal   = "Adapt. Behav.",
  publisher = "SAGE Publications Ltd STM",
  volume    =  17,
  number    =  4,
  pages     = "269--286",
  month     =  aug,
  year      =  2009
}

@ARTICLE{Yan2017-hj,
  title    = "Network control principles predict neuron function in the
              Caenorhabditis elegans connectome",
  author   = "Yan, Gang and V{\'e}rtes, Petra E and Towlson, Emma K and Chew,
              Yee Lian and Walker, Denise S and Schafer, William R and
              Barab{\'a}si, Albert-L{\'a}szl{\'o}",
  abstract = "Recent studies on the controllability of complex systems offer a
              powerful mathematical framework to systematically explore the
              structure-function relationship in biological, social, and
              technological networks. Despite theoretical advances, we lack
              direct experimental proof of the validity of these widely used
              control principles. Here we fill this gap by applying a control
              framework to the connectome of the nematode Caenorhabditis
              elegans, allowing us to predict the involvement of each C.
              elegans neuron in locomotor behaviours. We predict that control
              of the muscles or motor neurons requires 12 neuronal classes,
              which include neuronal groups previously implicated in locomotion
              by laser ablation, as well as one previously uncharacterized
              neuron, PDB. We validate this prediction experimentally, finding
              that the ablation of PDB leads to a significant loss of
              dorsoventral polarity in large body bends. Importantly, control
              principles also allow us to investigate the involvement of
              individual neurons within each neuronal class. For example, we
              predict that, within the class of DD motor neurons, only three
              (DD04, DD05, or DD06) should affect locomotion when ablated
              individually. This prediction is also confirmed; single cell
              ablations of DD04 or DD05 specifically affect posterior body
              movements, whereas ablations of DD02 or DD03 do not. Our
              predictions are robust to deletions of weak connections, missing
              connections, and rewired connections in the current connectome,
              indicating the potential applicability of this analytical
              framework to larger and less well-characterized connectomes.",
  journal  = "Nature",
  volume   =  550,
  number   =  7677,
  pages    = "519--523",
  month    =  oct,
  year     =  2017,
  language = "en"
}

@ARTICLE{Najafi2018-vk,
  title     = "Perceptual {Decision-Making}: A Field in the Midst of a
               Transformation",
  author    = "Najafi, Farzaneh and Churchland, Anne K",
  abstract  = "Major changes are underway in the field of perceptual
               decision-making. Single-neuron studies have given way to
               population recordings with identified cell types, traditional
               analyses have been extended to accommodate these large and
               diverse collections of neurons, and novel methods of neural
               disruption have provided insights about causal circuits.
               Further, the field has expanded to include multiple new species:
               rodents and invertebrates, for example, have been instrumental
               in demonstrating the importance of internal state on neural
               responses. Finally, a renewed interest in ethological stimuli
               prompted development of new behaviors, frequently analyzed by
               new, automated movement tracking methods. Taken together, these
               advances constitute a seismic shift in both our approach and
               understanding of how incoming sensory signals are used to guide
               decisions.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  100,
  number    =  2,
  pages     = "453--462",
  month     =  oct,
  year      =  2018,
  keywords  = "decision-making; cognition; mice; imaging; neural data analysis;
               computational models",
  language  = "en"
}

@ARTICLE{Lee2017-fw,
  title    = "Flexibility to contingency changes distinguishes habitual and
              goal-directed strategies in humans",
  author   = "Lee, Julie J and Keramati, Mehdi",
  abstract = "Decision-making in the real world presents the challenge of
              requiring flexible yet prompt behavior, a balance that has been
              characterized in terms of a trade-off between a slower,
              prospective goal-directed model-based (MB) strategy and a fast,
              retrospective habitual model-free (MF) strategy. Theory predicts
              that flexibility to changes in both reward values and transition
              contingencies can determine the relative influence of the two
              systems in reinforcement learning, but few studies have
              manipulated the latter. Therefore, we developed a novel two-level
              contingency change task in which transition contingencies between
              states change every few trials; MB and MF control predict
              different responses following these contingency changes, allowing
              their relative influence to be inferred. Additionally, we
              manipulated the rate of contingency changes in order to determine
              whether contingency change volatility would play a role in
              shifting subjects between a MB and MF strategy. We found that
              human subjects employed a hybrid MB/MF strategy on the task,
              corroborating the parallel contribution of MB and MF systems in
              reinforcement learning. Further, subjects did not remain at one
              level of MB/MF behaviour but rather displayed a shift towards
              more MB behavior over the first two blocks that was not
              attributable to the rate of contingency changes but rather to the
              extent of training. We demonstrate that flexibility to
              contingency changes can distinguish MB and MF strategies, with
              human subjects utilizing a hybrid strategy that shifts towards
              more MB behavior over blocks, consequently corresponding to a
              higher payoff.",
  journal  = "PLoS Comput. Biol.",
  volume   =  13,
  number   =  9,
  pages    = "e1005753",
  month    =  sep,
  year     =  2017,
  language = "en"
}

@ARTICLE{Reiter2018-gu,
  title    = "Elucidating the control and development of skin patterning in
              cuttlefish",
  author   = "Reiter, Sam and H{\"u}lsdunk, Philipp and Woo, Theodosia and
              Lauterbach, Marcel A and Eberle, Jessica S and Akay, Leyla Anne
              and Longo, Amber and Meier-Credo, Jakob and Kretschmer, Friedrich
              and Langer, Julian D and Kaschube, Matthias and Laurent, Gilles",
  abstract = "Few animals provide a readout that is as objective of their
              perceptual state as camouflaging cephalopods. Their skin display
              system includes an extensive array of pigment cells
              (chromatophores), each expandable by radial muscles controlled by
              motor neurons. If one could track the individual expansion states
              of the chromatophores, one would obtain a quantitative
              description-and potentially even a neural description by proxy-of
              the perceptual state of the animal in real time. Here we present
              the use of computational and analytical methods to achieve this
              in behaving animals, quantifying the states of tens of thousands
              of chromatophores at sixty frames per second, at single-cell
              resolution, and over weeks. We infer a statistical hierarchy of
              motor control, reveal an underlying low-dimensional structure to
              pattern dynamics and uncover rules that govern the development of
              skin patterns. This approach provides an objective description of
              complex perceptual behaviour, and a powerful means to uncover the
              organizational principles that underlie the function, dynamics
              and morphogenesis of neural systems.",
  journal  = "Nature",
  volume   =  562,
  number   =  7727,
  pages    = "361--366",
  month    =  oct,
  year     =  2018,
  language = "en"
}

@MISC{noauthor_undated-bu,
  institution = "bioRxiv"
}

@TECHREPORT{Kahneman1977-iq,
  title     = "Prospect Theory. An Analysis of Decision Making Under Risk",
  author    = "Kahneman, Daniel and Tversky, Amos",
  publisher = "Defense Technical Information Center",
  month     =  apr,
  year      =  1977
}

@MISC{noauthor_undated-zp,
  institution = "bioRxiv"
}

@ARTICLE{Dhawale2017-yp,
  title    = "Automated long-term recording and analysis of neural activity in
              behaving animals",
  author   = "Dhawale, Ashesh K and Poddar, Rajesh and Wolff, Steffen Be and
              Normand, Valentin A and Kopelowitz, Evi and {\"O}lveczky, Bence P",
  abstract = "Addressing how neural circuits underlie behavior is routinely
              done by measuring electrical activity from single neurons in
              experimental sessions. While such recordings yield snapshots of
              neural dynamics during specified tasks, they are ill-suited for
              tracking single-unit activity over longer timescales relevant for
              most developmental and learning processes, or for capturing
              neural dynamics across different behavioral states. Here we
              describe an automated platform for continuous long-term
              recordings of neural activity and behavior in freely moving
              rodents. An unsupervised algorithm identifies and tracks the
              activity of single units over weeks of recording, dramatically
              simplifying the analysis of large datasets. Months-long
              recordings from motor cortex and striatum made and analyzed with
              our system revealed remarkable stability in basic neuronal
              properties, such as firing rates and inter-spike interval
              distributions. Interneuronal correlations and the representation
              of different movements and behaviors were similarly stable. This
              establishes the feasibility of high-throughput long-term
              extracellular recordings in behaving animals.",
  journal  = "Elife",
  volume   =  6,
  month    =  sep,
  year     =  2017,
  keywords = "behavior; neural recordings; neuroscience; rat; systems
              neuroscience",
  language = "en"
}

@ARTICLE{Wolff2018-ir,
  title    = "The promise and perils of causal circuit manipulations",
  author   = "Wolff, Steffen Be and {\"O}lveczky, Bence P",
  abstract = "The development of increasingly sophisticated methods for
              recording and manipulating neural activity is revolutionizing
              neuroscience. By probing how activity patterns in different types
              of neurons and circuits contribute to behavior, these tools can
              help inform mechanistic models of brain function and explain the
              roles of distinct circuit elements. However, in systems where
              functions are distributed over large networks, interpreting
              causality experiments can be challenging. Here we review common
              assumptions underlying circuit manipulations in behaving animals
              and discuss the strengths and limitations of different
              approaches.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  49,
  pages    = "84--94",
  month    =  apr,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Low2018-gr,
  title    = "Probing variability in a cognitive map using manifold inference
              from neural dynamics",
  author   = "Low, Ryan J and Lewallen, Sam and Aronov, Dmitriy and Nevers,
              Rhino and Tank, David W",
  abstract = "Hippocampal neurons fire selectively in local behavioral contexts
              such as the position in an environment or phase of a task, and
              are thought to form a cognitive map of task-relevant variables.
              However, their activity varies over repeated behavioral
              conditions, such as different runs through the same position or
              repeated trials. Although widely observed across the brain, such
              variability is not well understood, and could reflect noise or
              structure, such as the encoding of additional cognitive
              information. Here, we introduce a conceptual model to explain
              variability in terms of underlying, population-level structure in
              single-trial neural activity. To test this model, we developed a
              novel unsupervised learning algorithm incorporating temporal
              dynamics, in order to characterize population activity as a
              trajectory on a nonlinear manifold--a space of possible network
              states. The manifold9s structure captures correlations between
              neurons and temporal relationships between states, constraints
              arising from underlying network architecture and inputs. Using
              measurements of activity over time but no information about
              exogenous behavioral variables, we recovered hippocampal activity
              manifolds during spatial and non-spatial cognitive tasks in rats.
              Manifolds were low dimensional and smoothly encoded task-related
              variables, but contained an extra dimension reflecting
              information beyond the measured behavioral variables. Consistent
              with our model, neurons fired as a function of overall network
              state, and fluctuations in their activity across trials
              corresponded to variation in the underlying trajectory on the
              manifold. In particular, the extra dimension allowed the system
              to take different trajectories despite repeated behavioral
              conditions. Furthermore, the trajectory could temporarily
              decouple from current behavioral conditions and traverse
              neighboring manifold points corresponding to past, future, or
              nearby behavioral states. Our results suggest that trial-to-trial
              variability in the hippocampus is structured, and may reflect the
              operation of internal cognitive processes. The manifold structure
              of population activity is well-suited for organizing information
              to support memory, planning, and reinforcement learning. In
              general, our approach could find broader use in probing the
              organization and computational role of circuit dynamics in other
              brain regions.",
  journal  = "bioRxiv",
  pages    = "418939",
  month    =  sep,
  year     =  2018,
  language = "en"
}

@ARTICLE{Pandarinath2018-mm,
  title    = "Inferring single-trial neural population dynamics using
              sequential auto-encoders",
  author   = "Pandarinath, Chethan and O'Shea, Daniel J and Collins, Jasmine
              and Jozefowicz, Rafal and Stavisky, Sergey D and Kao, Jonathan C
              and Trautmann, Eric M and Kaufman, Matthew T and Ryu, Stephen I
              and Hochberg, Leigh R and Henderson, Jaimie M and Shenoy, Krishna
              V and Abbott, L F and Sussillo, David",
  abstract = "Neuroscience is experiencing a revolution in which simultaneous
              recording of thousands of neurons is revealing population
              dynamics that are not apparent from single-neuron responses. This
              structure is typically extracted from data averaged across many
              trials, but deeper understanding requires studying phenomena
              detected in single trials, which is challenging due to incomplete
              sampling of the neural population, trial-to-trial variability,
              and fluctuations in action potential timing. We introduce latent
              factor analysis via dynamical systems, a deep learning method to
              infer latent dynamics from single-trial neural spiking data. When
              applied to a variety of macaque and human motor cortical
              datasets, latent factor analysis via dynamical systems accurately
              predicts observed behavioral variables, extracts precise firing
              rate estimates of neural dynamics on single trials, infers
              perturbations to those dynamics that correlate with behavioral
              choices, and combines data from non-overlapping recording
              sessions spanning months to improve inference of underlying
              dynamics.",
  journal  = "Nat. Methods",
  month    =  sep,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Ahilan2018-qy,
  title    = "Forgetful inference in a sophisticated world model",
  author   = "Ahilan, Sanjeevan and Solomon, Rebecca B and Breton,
              Yannick-Andr{\'e} and Conover, Kent and Niyogi, Ritwik K and
              Shizgal, Peter and Dayan, Peter",
  abstract = "Humans and other animals are able to discover underlying
              statistical structure in their environments and exploit it to
              achieve efficient and effective performance. However, such
              structure is often difficult to learn and use because it is
              obscure, involving long-range temporal dependencies. Here, we
              analysed behavioural data from an extended experiment with rats,
              showing that the subjects learned the underlying statistical
              structure, albeit suffering at times from immediate inferential
              imperfections as to their current state within it. We accounted
              for their behaviour using a Hidden Markov Model, in which recent
              observations are integrated with the recollections of an
              imperfect memory. We found that over the course of training,
              subjects came to track their progress through the task more
              accurately, a change that our model largely attributed to
              decreased forgetting. This 9learning to remember9 decreased
              reliance on recent observations, which may be misleading, in
              favour of a longer-term memory.",
  journal  = "bioRxiv",
  pages    = "419317",
  month    =  sep,
  year     =  2018,
  language = "en"
}

@ARTICLE{Han2018-vj,
  title    = "A Neural Circuit for {Gut-Induced} Reward",
  author   = "Han, Wenfei and Tellez, Luis A and Perkins, Matthew H and Perez,
              Isaac O and Qu, Taoran and Ferreira, Jozelia and Ferreira,
              Tatiana L and Quinn, Daniele and Liu, Zhong-Wu and Gao, Xiao-Bing
              and Kaelberer, Melanie M and Boh{\'o}rquez, Diego V and
              Shammah-Lagnado, Sara J and de Lartigue, Guillaume and de Araujo,
              Ivan E",
  abstract = "The gut is now recognized as a major regulator of motivational
              and emotional states. However, the relevant gut-brain neuronal
              circuitry remains unknown. We show that optical activation of
              gut-innervating vagal sensory neurons recapitulates the hallmark
              effects of stimulating brain reward neurons. Specifically, right,
              but not left, vagal sensory ganglion activation sustained
              self-stimulation behavior, conditioned both flavor and place
              preferences, and induced dopamine release from Substantia nigra.
              Cell-specific transneuronal tracing revealed asymmetric ascending
              pathways of vagal origin throughout the CNS. In particular,
              transneuronal labeling identified the glutamatergic neurons of
              the dorsolateral parabrachial region as the obligatory relay
              linking the right vagal sensory ganglion to dopamine cells in
              Substantia nigra. Consistently, optical activation of
              parabrachio-nigral projections replicated the rewarding effects
              of right vagus excitation. Our findings establish the vagal
              gut-to-brain axis as an integral component of the neuronal reward
              pathway. They also suggest novel vagal stimulation approaches to
              affective disorders.",
  journal  = "Cell",
  month    =  sep,
  year     =  2018,
  keywords = "dopamine; gut-brain axis; reward; vagus nerve",
  language = "en"
}

@UNPUBLISHED{Grundemann2018-yn,
  title    = "Amygdala neuronal ensembles dynamically encode behavioral states",
  author   = "Gr{\"u}ndemann, Jan and Bitterman, Yael and Lu, Tingjia and
              Krabbe, Sabine and Grewe, Benjamin F and Schnitzer, Mark J and
              L{\"u}thi, Andreas",
  abstract = "Internal states, including affective or homeostatic states, are
              important behavioral motivators. The amygdala is a key brain
              region involved in the regulation of motivated behaviors, yet how
              distinct internal states are represented in amygdala circuits is
              not known. Here, by imaging somatic neural calcium dynamics in
              freely moving mice, we demonstrate that changes in the relative
              activity levels of two major, non-overlapping populations of
              principal neurons in the basal nucleus of the amygdala (BA)
              predict switches between exploratory and anxiety-like or
              defensive behavioral states across different environments.
              Moreover, we found that the amygdala widely broadcasts internal
              state information via several output pathways to larger brain
              networks, and that sensory responses in the BA were not
              correlated with behavioral states. Our data indicate that the
              brain processes external stimuli and internal states in an
              orthogonal manner, which may facilitate rapid and flexible
              selection of appropriate, state-dependent behavioral responses.",
  journal  = "bioRxiv",
  pages    = "425736",
  month    =  sep,
  year     =  2018,
  language = "en"
}

@ARTICLE{Buzsaki2018-je,
  title    = "Space and Time: The Hippocampus as a Sequence Generator",
  author   = "Buzs{\'a}ki, Gy{\"o}rgy and Tingley, David",
  abstract = "Neural computations are often compared to instrument-measured
              distance or duration, and such relationships are interpreted by a
              human observer. However, neural circuits do not depend on
              human-made instruments but perform computations relative to an
              internally defined rate-of-change. While neuronal correlations
              with external measures, such as distance or duration, can be
              observed in spike rates or other measures of neuronal activity,
              what matters for the brain is how such activity patterns are
              utilized by downstream neural observers. We suggest that
              hippocampal operations can be described by the sequential
              activity of neuronal assemblies and their internally defined rate
              of change without resorting to the concept of space or time.",
  journal  = "Trends Cogn. Sci.",
  volume   =  22,
  number   =  10,
  pages    = "853--869",
  month    =  oct,
  year     =  2018,
  keywords = "place cells; time cells; theta oscillation; phase coding; lateral
              septum"
}

@ARTICLE{Moita2004-fi,
  title     = "Putting fear in its place: remapping of hippocampal place cells
               during fear conditioning",
  author    = "Moita, Marta A P and Rosis, Svetlana and Zhou, Yu and LeDoux,
               Joseph E and Blair, Hugh T",
  abstract  = "We recorded hippocampal place cells in two spatial environments:
               a training environment in which rats underwent fear conditioning
               and a neutral control environment. Fear conditioning caused many
               place cells to alter (or remap) their preferred firing locations
               in the training environment, whereas most cells remained stable
               in the control environment. This finding indicates that aversive
               reinforcement can induce place cell remapping even when the
               environment itself remains unchanged. Furthermore, contextual
               fear conditioning caused significantly more remapping of place
               cells than auditory fear conditioning, suggesting that place
               cell remapping was related to the rat's learned fear of the
               environment. These results suggest that one possible function of
               place cell remapping may be to generate new spatial
               representations of a single environment, which could help the
               animal to discriminate among different motivational contexts
               within that environment.",
  journal   = "J. Neurosci.",
  publisher = "Soc Neuroscience",
  volume    =  24,
  number    =  31,
  pages     = "7015--7023",
  month     =  aug,
  year      =  2004,
  language  = "en"
}

@ARTICLE{Nusbaum2017-sy,
  title    = "Functional consequences of neuropeptide and small-molecule
              co-transmission",
  author   = "Nusbaum, Michael P and Blitz, Dawn M and Marder, Eve",
  abstract = "Colocalization of small-molecule and neuropeptide transmitters is
              common throughout the nervous system of all animals. The
              resulting co-transmission, which provides conjoint ionotropic
              ('classical') and metabotropic ('modulatory') actions, includes
              neuropeptide- specific aspects that are qualitatively different
              from those that result from metabotropic actions of
              small-molecule transmitter release. Here, we focus on the
              flexibility afforded to microcircuits by such co-transmission,
              using examples from various nervous systems. Insights from such
              studies indicate that co-transmission mediated even by a single
              neuron can configure microcircuit activity via an array of
              contributing mechanisms, operating on multiple timescales, to
              enhance both behavioural flexibility and robustness.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  18,
  number   =  7,
  pages    = "389--403",
  month    =  jul,
  year     =  2017,
  keywords = "synapses",
  language = "en"
}

@ARTICLE{Ryan2009-qm,
  title    = "The origin and evolution of synapses",
  author   = "Ryan, Tom{\'a}s J and Grant, Seth G N",
  abstract = "Understanding the evolutionary origins of behaviour is a central
              aim in the study of biology and may lead to insights into human
              disorders. Synaptic transmission is observed in a wide range of
              invertebrate and vertebrate organisms and underlies their
              behaviour. Proteomic studies of the molecular components of the
              highly complex mammalian postsynaptic machinery point to an
              ancestral molecular machinery in unicellular organisms--the
              protosynapse--that existed before the evolution of metazoans and
              neurons, and hence challenges existing views on the origins of
              the brain. The phylogeny of the molecular components of the
              synapse provides a new model for studying synapse diversity and
              complexity, and their implications for brain evolution.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  10,
  number   =  10,
  pages    = "701--712",
  month    =  oct,
  year     =  2009,
  keywords = "synapses",
  language = "en"
}

@ARTICLE{Masi2015-wb,
  title    = "Electrical spiking in bacterial biofilms",
  author   = "Masi, Elisa and Ciszak, Marzena and Santopolo, Luisa and
              Frascella, Arcangela and Giovannetti, Luciana and Marchi,
              Emmanuela and Viti, Carlo and Mancuso, Stefano",
  abstract = "In nature, biofilms are the most common form of bacterial growth.
              In biofilms, bacteria display coordinated behaviour to perform
              specific functions. Here, we investigated electrical signalling
              as a possible driver in biofilm sociobiology. Using a
              multi-electrode array system that enables high spatio-temporal
              resolution, we studied the electrical activity in two
              biofilm-forming strains and one non-biofilm-forming strain. The
              action potential rates monitored during biofilm-forming bacterial
              growth exhibited a one-peak maximum with a long tail,
              corresponding to the highest biofilm development. This peak was
              not observed for the non-biofilm-forming strain, demonstrating
              that the intensity of the electrical activity was not linearly
              related to the bacterial density, but was instead correlated with
              biofilm formation. Results obtained indicate that the analysis of
              the spatio-temporal electrical activity of bacteria during
              biofilm formation can open a new frontier in the study of the
              emergence of collective microbial behaviour.",
  journal  = "J. R. Soc. Interface",
  volume   =  12,
  number   =  102,
  pages    = "20141036",
  month    =  jan,
  year     =  2015,
  keywords = "bacteria; biofilm; electrical spiking; multi-electrode array;
              sociobiology;synapses",
  language = "en"
}

@ARTICLE{Emes2012-ea,
  title    = "Evolution of synapse complexity and diversity",
  author   = "Emes, Richard D and Grant, Seth G N",
  abstract = "Proteomic studies of the composition of mammalian synapses have
              revealed a high degree of complexity. The postsynaptic and
              presynaptic terminals are molecular systems with highly organized
              protein networks producing emergent physiological and behavioral
              properties. The major classes of synapse proteins and their
              respective functions in intercellular communication and adaptive
              responses evolved in prokaryotes and eukaryotes prior to the
              origins of neurons in metazoa. In eukaryotes, the organization of
              individual proteins into multiprotein complexes comprising
              scaffold proteins, receptors, and signaling enzymes formed the
              precursor to the core adaptive machinery of the metazoan
              postsynaptic terminal. Multiplicative increases in the complexity
              of this protosynapse machinery secondary to genome duplications
              drove synaptic, neuronal, and behavioral novelty in vertebrates.
              Natural selection has constrained diversification in mammalian
              postsynaptic mechanisms and the repertoire of adaptive and innate
              behaviors. The evolution and organization of synapse proteomes
              underlie the origins and complexity of nervous systems and
              behavior.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  35,
  pages    = "111--131",
  year     =  2012,
  keywords = "synapses",
  language = "en"
}

@ARTICLE{Burkhardt2017-rp,
  title    = "Evolutionary origin of synapses and neurons - Bridging the gap",
  author   = "Burkhardt, Pawel and Sprecher, Simon G",
  abstract = "The evolutionary origin of synapses and neurons is an enigmatic
              subject that inspires much debate. Non-bilaterian metazoans, both
              with and without neurons and their closest relatives already
              contain many components of the molecular toolkits for synapse
              functions. The origin of these components and their assembly into
              ancient synaptic signaling machineries are particularly important
              in light of recent findings on the phylogeny of non-bilaterian
              metazoans. The evolution of synapses and neurons are often
              discussed only from a metazoan perspective leaving a considerable
              gap in our understanding. By taking an integrative approach we
              highlight the need to consider different, but extremely relevant
              phyla and to include the closest unicellular relatives of
              metazoans, the ichthyosporeans, filastereans and
              choanoflagellates, to fully understand the evolutionary origin of
              synapses and neurons. This approach allows for a detailed
              understanding of when and how the first pre- and postsynaptic
              signaling machineries evolved.",
  journal  = "Bioessays",
  volume   =  39,
  number   =  10,
  month    =  oct,
  year     =  2017,
  keywords = "evolution; neuron; origin; protein-protein interactions;
              synapse;synapses",
  language = "en"
}

@ARTICLE{Brunet2016-lp,
  title    = "From damage response to action potentials: early evolution of
              neural and contractile modules in stem eukaryotes",
  author   = "Brunet, Thibaut and Arendt, Detlev",
  abstract = "Eukaryotic cells convert external stimuli into membrane
              depolarization, which in turn triggers effector responses such as
              secretion and contraction. Here, we put forward an evolutionary
              hypothesis for the origin of the
              depolarization-contraction-secretion (DCS) coupling, the
              functional core of animal neuromuscular circuits. We propose that
              DCS coupling evolved in unicellular stem eukaryotes as part of an
              'emergency response' to calcium influx upon membrane rupture. We
              detail how this initial response was subsequently modified into
              an ancient mechanosensory-effector arc, present in the last
              eukaryotic common ancestor, which enabled contractile amoeboid
              movement that is widespread in extant eukaryotes. Elaborating on
              calcium-triggered membrane depolarization, we reason that the
              first action potentials evolved alongside the membrane of
              sensory-motile cilia, with the first voltage-sensitive
              sodium/calcium channels (Nav/Cav) enabling a fast and coordinated
              response of the entire cilium to mechanosensory stimuli. From the
              cilium, action potentials then spread across the entire cell,
              enabling global cellular responses such as concerted contraction
              in several independent eukaryote lineages. In animals, this
              process led to the invention of mechanosensory contractile cells.
              These gave rise to mechanosensory receptor cells, neurons and
              muscle cells by division of labour and can be regarded as the
              founder cell type of the nervous system.",
  journal  = "Philos. Trans. R. Soc. Lond. B Biol. Sci.",
  volume   =  371,
  number   =  1685,
  pages    = "20150043",
  month    =  jan,
  year     =  2016,
  keywords = "action potentials; electrophysiology; evo-devo; evolution;
              musculature; nervous systems;synapses",
  language = "en"
}

@ARTICLE{Brette_undated-lb,
  title    = "Theory of action potentials",
  author   = "Brette, Romain",
  keywords = "synapses"
}

@MISC{noauthor_undated-oe,
  title    = "418228.full.pdf",
  keywords = "synapses"
}

@ARTICLE{Cox2000-ax,
  title    = "Action potentials reliably invade axonal arbors of rat
              neocortical neurons",
  author   = "Cox, C L and Denk, W and Tank, D W and Svoboda, K",
  abstract = "Neocortical pyramidal neurons have extensive axonal arborizations
              that make thousands of synapses. Action potentials can invade
              these arbors and cause calcium influx that is required for
              neurotransmitter release and excitation of postsynaptic targets.
              Thus, the regulation of action potential invasion in axonal
              branches might shape the spread of excitation in cortical neural
              networks. To measure the reliability and extent of action
              potential invasion into axonal arbors, we have used two-photon
              excitation laser scanning microscopy to directly image
              action-potential-mediated calcium influx in single varicosities
              of layer 2/3 pyramidal neurons in acute brain slices. Our data
              show that single action potentials or bursts of action potentials
              reliably invade axonal arbors over a range of developmental ages
              (postnatal 10-24 days) and temperatures (24 degrees C-30 degrees
              C). Hyperpolarizing current steps preceding action potential
              initiation, protocols that had previously been observed to
              produce failures of action potential propagation in cultured
              preparations, were ineffective in modulating the spread of action
              potentials in acute slices. Our data show that action potentials
              reliably invade the axonal arbors of neocortical pyramidal
              neurons. Failures in synaptic transmission must therefore
              originate downstream of action potential invasion. We also
              explored the function of modulators that inhibit presynaptic
              calcium influx. Consistent with previous studies, we find that
              adenosine reduces action-potential-mediated calcium influx in
              presynaptic terminals. This reduction was observed in all
              terminals tested, suggesting that some modulatory systems are
              expressed homogeneously in most terminals of the same neuron.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  97,
  number   =  17,
  pages    = "9724--9728",
  month    =  aug,
  year     =  2000,
  keywords = "synapses",
  language = "en"
}

@ARTICLE{Huguenard2000-qu,
  title    = "Reliability of axonal propagation: the spike doesn't stop here",
  author   = "Huguenard, J R",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  97,
  number   =  17,
  pages    = "9349--9350",
  month    =  aug,
  year     =  2000,
  language = "en"
}

@ARTICLE{Tao2014-bv,
  title    = "Flexible stop and double-cascaded stop to improve shock
              reliability of {MEMS} accelerometer",
  author   = "Tao, Yong-Kang and Liu, Yun-Feng and Dong, Jing-Xin",
  abstract = "Flexible stop could provide shock protection for MEMS
              accelerometer. By modeling and simulation, the paper studied the
              response of a closed-loop MEMS accelerometer with stop under
              shock of different amplitudes and pulse width. Contact force
              plays an important role and the shock response shows strong
              nonlinearity due to the contact mechanism. A kind of
              double-cascaded stop is proposed to mitigate high-frequency shock
              failure. MEMS accelerometers with flexible stop and with
              double-cascaded stop are both designed and fabricated based on
              SOG (silicon on glass) technology. Compared with shock tests of
              accelerometers with hard cylinder stop, flexible stop could
              withstand more than 1e4g shock with about 100$\mu$s pulse width.
              Double-cascaded stop is more robust to high frequency shock.",
  journal  = "Microelectron. Reliab.",
  volume   =  54,
  number   =  6,
  pages    = "1328--1337",
  month    =  jun,
  year     =  2014
}

@ARTICLE{Pfeiffer2013-un,
  title    = "Hippocampal place-cell sequences depict future paths to
              remembered goals",
  author   = "Pfeiffer, Brad E and Foster, David J",
  abstract = "Effective navigation requires planning extended routes to
              remembered goal locations. Hippocampal place cells have been
              proposed to have a role in navigational planning, but direct
              evidence has been lacking. Here we show that before goal-directed
              navigation in an open arena, the rat hippocampus generates brief
              sequences encoding spatial trajectories strongly biased to
              progress from the subject's current location to a known goal
              location. These sequences predict immediate future behaviour,
              even in cases in which the specific combination of start and goal
              locations is novel. These results indicate that hippocampal
              sequence events characterized previously in linearly constrained
              environments as 'replay' are also capable of supporting a
              goal-directed, trajectory-finding mechanism, which identifies
              important places and relevant behavioural paths, at specific
              times when memory retrieval is required, and in a manner that
              could be used to control subsequent navigational behaviour.",
  journal  = "Nature",
  volume   =  497,
  number   =  7447,
  pages    = "74--79",
  month    =  may,
  year     =  2013,
  language = "en"
}

@ARTICLE{Lin2007-yy,
  title    = "Neural encoding of the concept of nest in the mouse brain",
  author   = "Lin, Longnian and Chen, Guifen and Kuang, Hui and Wang, Dong and
              Tsien, Joe Z",
  abstract = "As important as memory is to our daily functions, the ability to
              extract fundamental features and commonalities from various
              episodic experiences and to then generalize them into abstract
              concepts is even more crucial for both humans and animals to
              adapt to novel and complex situations. Here, we report the neural
              correlates of the abstract concept of nests or beds in mice.
              Specifically, we find hippocampal neurons that selectively fire
              or cease to fire when the mouse perceives nests or beds,
              regardless of their locations and environments. Parametric
              analyses show that responses of nest cells remain invariant over
              changes in the nests' physical shape, style, color, odor, or
              construction materials; rather, their responses are driven by
              conscious awareness and physical determination of the categorical
              features that would functionally define nests. Such
              functionality-based abstraction and generalization of conceptual
              knowledge, emerging from episodic experiences, suggests that the
              hippocampus is an intrinsic part of the hierarchical structure
              for generating concepts and knowledge in the brain.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  104,
  number   =  14,
  pages    = "6066--6071",
  month    =  apr,
  year     =  2007,
  language = "en"
}

@ARTICLE{Yoo2018-fd,
  title    = "Economic Choice as an Untangling of Options into Actions",
  author   = "Yoo, Seng Bum Michael and Hayden, Benjamin Yost",
  abstract = "We propose that economic choice can be understood as a gradual
              transformation from a domain of options to one of the actions. We
              draw an analogy with the idea of untangling information in the
              form vision system and propose that form vision and economic
              choice may be two aspects of a larger process that sculpts
              actions based on sensory inputs. From this viewpoint, choice
              results from the accumulated effect of repetitions of simple
              computations. These may consist primarily of relative valuations
              (evaluations relative to the value of rejection, perhaps in a
              manner akin to divisive normalization) applied to individual
              offers. With regard to economic choice, cortical brain regions
              differ primarily in their position and in what information they
              prioritize, and do not-with a few exceptions-have categorically
              distinct roles. Each region's specific contribution is determined
              largely by its inputs; thus, understanding connectivity is
              crucial for understanding choice. This view suggests that there
              is no single site of choice, that there is no meaningful
              distinction between pre- and post-decisionality, and that there
              is no explicit representation of value in the brain.",
  journal  = "Neuron",
  volume   =  99,
  number   =  3,
  pages    = "434--447",
  month    =  aug,
  year     =  2018,
  keywords = "Untangling; affordance competition; economic choice; functional
              neuroanatomy; value",
  language = "en"
}

@ARTICLE{Huk2018-ng,
  title    = "Beyond {Trial-Based} Paradigms: Continuous Behavior, Ongoing
              Neural Activity, and Natural Stimuli",
  author   = "Huk, Alexander and Bonnen, Kathryn and He, Biyu J",
  abstract = "The vast majority of experiments examining perception and
              behavior are conducted using experimental paradigms that adhere
              to a rigid trial structure: each trial consists of a brief and
              discrete series of events and is regarded as independent from all
              other trials. The assumptions underlying this structure ignore
              the reality that natural behavior is rarely discrete, brain
              activity follows multiple time courses that do not necessarily
              conform to the trial structure, and the natural environment has
              statistical structure and dynamics that exhibit long-range
              temporal correlation. Modern advances in statistical modeling and
              analysis offer tools that make it feasible for experiments to
              move beyond rigid independent and identically distributed trial
              structures. Here we review literature that serves as evidence for
              the feasibility and advantages of moving beyond trial-based
              paradigms to understand the neural basis of perception and
              cognition. Furthermore, we propose a synthesis of these efforts,
              integrating the characterization of natural stimulus properties
              with measurements of continuous neural activity and behavioral
              outputs within the framework of sensory-cognitive-motor loops.
              Such a framework provides a basis for the study of natural
              statistics, naturalistic tasks, and/or slow fluctuations in brain
              activity, which should provide starting points for important
              generalizations of analytical tools in neuroscience and
              subsequent progress in understanding the neural basis of
              perception and cognition.",
  journal  = "J. Neurosci.",
  volume   =  38,
  number   =  35,
  pages    = "7551--7558",
  month    =  aug,
  year     =  2018,
  language = "en"
}

@ARTICLE{Bicanski2018-jz,
  title    = "A neural-level model of spatial memory and imagery",
  author   = "Bicanski, Andrej and Burgess, Neil",
  abstract = "We present a model of how neural representations of egocentric
              spatial experiences in parietal cortex interface with
              viewpoint-independent representations in medial temporal areas,
              via retrosplenial cortex, to enable many key aspects of spatial
              cognition. This account shows how previously reported neural
              responses (place, head-direction and grid cells, allocentric
              boundary- and object-vector cells, gain-field neurons) can map
              onto higher cognitive function in a modular way, and predicts new
              cell types (egocentric and head-direction-modulated boundary- and
              object-vector cells). The model predicts how these neural
              populations should interact across multiple brain regions to
              support spatial memory, scene construction, novelty-detection,
              'trace cells', and mental navigation. Simulated behavior and
              firing rate maps are compared to experimental data, for example
              showing how object-vector cells allow items to be remembered
              within a contextual representation based on environmental
              boundaries, and how grid cells could update the viewpoint in
              imagery during planning and short-cutting by driving sequential
              place cell activity.",
  journal  = "Elife",
  volume   =  7,
  month    =  sep,
  year     =  2018,
  keywords = "computational model; episodic memory; neuroscience; none; scene
              construction; spatial cognition; spatially selective cells; trace
              cells",
  language = "en"
}

@UNPUBLISHED{Zhang2018-tv,
  title    = "Modeling {Sensory-Motor} Decisions in Natural Behavior",
  author   = "Zhang, Ruohan and Zhang, Shun and Tong, Matthew H and Cui, Yuchen
              and Rothkopf, Constantin A and Ballard, Dana H and Hayhoe, Mary M",
  abstract = "Although a standard reinforcement learning model can capture many
              aspects of reward-seeking behaviors, it may not be practical for
              modeling human natural behaviors because of the richness of
              dynamic environments and limitations in cognitive resources. We
              propose a modular reinforcement learning model that addresses
              these factors. Based on this model, a modular inverse
              reinforcement learning algorithm is developed to estimate both
              the rewards and discount factors from human behavioral data,
              which allows predictions of human navigation behaviors in virtual
              reality with high accuracy across different subjects and with
              different tasks. Complex human navigation trajectories in novel
              environments can be reproduced by an artificial agent that is
              based on the modular model. This model provides a strategy for
              estimating the subjective value of actions and how they influence
              sensory-motor decisions in natural behavior.",
  journal  = "bioRxiv",
  pages    = "412155",
  month    =  sep,
  year     =  2018,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Swanson2000-yg,
  title     = "Cerebral hemisphere regulation of motivated behavior",
  author    = "Swanson, Larry W",
  abstract  = "The goals of this article are to suggest a basic wiring diagram
               for the motor neural network that controls motivated behavior,
               and to provide a model for the organization of cerebral
               hemisphere inputs to this network. Cerebral projections mediate
               voluntary regulation of a …",
  journal   = "Brain Res.",
  publisher = "Elsevier",
  volume    =  886,
  number    = "1-2",
  pages     = "113--164",
  year      =  2000
}

@ARTICLE{Garrett2018-np,
  title     = "Updating Beliefs Under Perceived Threat",
  author    = "Garrett, Neil and Gonz{\'a}lez-Garz{\'o}n, Ana Mar{\'\i}a and
               Foulkes, Lucy and Levita, Liat and Sharot, Tali",
  abstract  = "Humans are better at integrating desirable information into
               their beliefs than undesirable. This asymmetry poses an
               evolutionary puzzle, as it can lead to an underestimation of
               risk and thus failure to take precautionary action. Here, we
               suggest a mechanism that can speak to this conundrum. In
               particular, we show that the bias vanishes in response to
               perceived threat in the environment. We report that an
               improvement in participants' tendency to incorporate bad news
               into their beliefs is associated with physiological arousal in
               response to threat indexed by galvanic skin response and
               self-reported anxiety. This pattern of results was observed in a
               controlled laboratory setting (Experiment I), where perceived
               threat was manipulated, and in firefighters on duty (Experiment
               II), where it naturally varied. Such flexibility in how
               individuals integrate information may enhance the likelihood of
               responding to warnings with caution in environments rife with
               threat, while maintaining a positivity bias otherwise, a
               strategy that can increase well-being.SIGNIFICANCE STATEMENTThe
               human tendency to be overly optimistic has mystified scholars
               and lay people for decades: how could biased beliefs have been
               selected for over unbiased beliefs? Scholars have suggested that
               while the optimism bias can lead to negative outcomes, including
               financial collapse and war, it can also facilitate health and
               productivity. Here, we demonstrate that a mechanism generating
               the optimism bias, namely asymmetric information integration,
               evaporates under threat. Such flexibility could result in
               enhanced caution in dangerous environments while supporting an
               optimism bias otherwise, potentially increasing well-being.",
  journal   = "J. Neurosci.",
  publisher = "papers.ssrn.com",
  month     =  aug,
  year      =  2018,
  language  = "en"
}

@ARTICLE{Papale2012-xl,
  title     = "Interactions between deliberation and delay-discounting in rats",
  author    = "Papale, Andrew E and Stott, Jeffrey J and Powell, Nathaniel J
               and Regier, Paul S and Redish, A David",
  abstract  = "When faced with decisions, rats sometimes pause and look back
               and forth between possible alternatives, a phenomenon termed
               vicarious trial and error (VTE). When it was first observed in
               the 1930s, VTE was theorized to be a mechanism for exploration.
               Later theories suggested that VTE aided the resolution of
               sensory or neuroeconomic conflict. In contrast, recent
               neurophysiological data suggest that VTE reflects a dynamic
               search and evaluation process. These theories make unique
               predictions about the timing of VTE on behavioral tasks. We
               tested these theories of VTE on a T-maze with return rails,
               where rats were given a choice between a smaller reward
               available after one delay or a larger reward available after an
               adjustable delay. Rats showed three clear phases of behavior on
               this task: investigation, characterized by discovery of task
               parameters; titration, characterized by iterative adjustment of
               the delay to a preferred interval; and exploitation,
               characterized by alternation to hold the delay at the preferred
               interval. We found that VTE events occurred during adjustment
               laps more often than during alternation laps. Results were
               incompatible with theories of VTE as an exploratory behavior, as
               reflecting sensory conflict, or as a simple neuroeconomic
               valuation process. Instead, our results were most consistent
               with VTE as reflecting a search process during deliberative
               decision making. This pattern of VTE that we observed is
               reminiscent of current navigational theories proposing a
               transition from a deliberative to a habitual decision-making
               mechanism.",
  journal   = "Cogn. Affect. Behav. Neurosci.",
  publisher = "Springer",
  volume    =  12,
  number    =  3,
  pages     = "513--526",
  month     =  sep,
  year      =  2012,
  language  = "en"
}

@ARTICLE{Gallivan2018-rt,
  title    = "Decision-making in sensorimotor control",
  author   = "Gallivan, Jason P and Chapman, Craig S and Wolpert, Daniel M and
              Flanagan, J Randall",
  abstract = "Skilled sensorimotor interactions with the world result from a
              series of decision-making processes that determine, on the basis
              of information extracted during the unfolding sequence of events,
              which movements to make and when and how to make them. Despite
              this inherent link between decision-making and sensorimotor
              control, research into each of these two areas has largely
              evolved in isolation, and it is only fairly recently that
              researchers have begun investigating how they interact and,
              together, influence behaviour. Here, we review recent
              behavioural, neurophysiological and computational research that
              highlights the role of decision-making processes in the
              selection, planning and control of goal-directed movements in
              humans and nonhuman primates.",
  journal  = "Nat. Rev. Neurosci.",
  month    =  aug,
  year     =  2018,
  language = "en"
}

@ARTICLE{Gilad2018-cq,
  title    = "Behavioral Strategy Determines Frontal or Posterior Location of
              {Short-Term} Memory in Neocortex",
  author   = "Gilad, Ariel and Gallero-Salas, Yasir and Groos, Dominik and
              Helmchen, Fritjof",
  abstract = "The location of short-term memory in mammalian neocortex remains
              elusive. Here we show that distinct neocortical areas maintain
              short-term memory depending on behavioral strategy. Using
              wide-field and single-cell calcium imaging, we measured layer 2/3
              neuronal activity in mice performing a whisker-based texture
              discrimination task with delayed response. Mice either deployed
              an active strategy-engaging their body toward the approaching
              texture-or passively awaited the touch. Independent of strategy,
              whisker-related posterior areas encoded choice early after touch.
              During the delay, in contrast, persistent cortical activity was
              located medio-frontally in active trials but in a lateral
              posterior area in passive trials. Perturbing these areas impaired
              performance for the associated strategy and also provoked
              strategy switches. Frontally maintained information related to
              future action, whereas activity in the posterior cortex reflected
              past stimulus identity. Thus, depending on behavioral strategy,
              cortical activity is routed differentially to hold information
              either frontally or posteriorly before converging to similar
              action.",
  journal  = "Neuron",
  month    =  jul,
  year     =  2018,
  keywords = "barrel cortex; calcium imaging; fronto-posterior interactions;
              motor cortex; optogenetics; posterolateral cortex; secondary
              motor cortex; whisker; wide-field imaging; working memory",
  language = "en"
}

@UNPUBLISHED{Karalis2018-wn,
  title    = "Breathing coordinates limbic network dynamics underlying memory
              consolidation",
  author   = "Karalis, Nikolaos and Sirota, Anton",
  abstract = "The coordinated activity between remote brain regions underlies
              cognition and memory function. Although neuronal oscillations
              have been proposed as a mechanistic substrate for the
              coordination of information transfer and memory consolidation
              during sleep, little is known about the mechanisms that support
              the widespread synchronization of brain regions and the
              relationship of neuronal dynamics with other bodily rhythms, such
              as breathing. Here we address this question using large-scale
              recordings from a number of structures, including the medial
              prefrontal cortex, hippocampus, thalamus, amygdala and nucleus
              accumbens in mice. We identify a dual mechanism of respiratory
              entrainment, in the form of an intracerebral corollary discharge
              that acts jointly with an olfactory reafference to coordinate
              limbic network dynamics, such as hippocampal ripples and cortical
              UP and DOWN states, involved in memory consolidation. These
              results highlight breathing, a perennial rhythmic input to the
              brain, as an oscillatory scaffold for the functional coordination
              of the limbic circuit, enabling the segregation and integration
              of information flow across neuronal networks.",
  journal  = "bioRxiv",
  pages    = "392530",
  month    =  aug,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Carrillo-Reid2018-tp,
  title    = "Triggering visually-guided behavior by holographic activation of
              pattern completion neurons in cortical ensembles",
  author   = "Carrillo-Reid, Luis and Han, Shuting and Yang, Weijian and
              Akrouh, Alejandro and Yuste, Rafael",
  abstract = "Neuronal ensembles are building blocks of cortical activity yet
              it is unclear if they have any causal role in behavior. Here we
              tested if the precise activation of neuronal ensembles with
              two-photon holographic optogenetics in mouse primary visual
              cortex alters behavioral performance in a visual task. Disruption
              of behaviorally relevant cortical ensembles by activation of
              non-selective neurons decreased behavioral performance whereas
              optogenetic targeting of as few as two neurons with pattern
              completion capability from behaviorally relevant ensembles
              improved task performance by reliably recalling the whole
              ensemble. Moreover, in some cases, activation of two pattern
              completion neurons, in the absence of visual stimulus, triggered
              correct behavioral responses. Our results demonstrate a causal
              role of neuronal ensembles in a visually guided behavior and
              suggest that ensembles could represent perceptual states.",
  journal  = "bioRxiv",
  pages    = "394999",
  month    =  aug,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Kim2018-uq,
  title    = "Task complexity interacts with state-space uncertainty in the
              arbitration process between model-based and model-free
              reinforcement-learning at both behavioral and neural levels",
  author   = "Kim, Dongjae and Park, Geon Yeong and O'Doherty, John P and Lee,
              Sang Wan",
  abstract = "A major open question concerns how the brain governs the
              allocation of control between two distinct strategies for
              learning from reinforcement: model-based and model-free
              reinforcement learning. While there is evidence to suggest that
              the reliability of the predictions of the two systems is a key
              variable responsible for the arbitration process, another key
              variable has remained relatively unexplored: the role of task
              complexity. By using a combination of novel task design,
              computational modeling, and model-based fMRI analysis, we
              examined the role of task complexity alongside state-space
              uncertainty in the arbitration process between model-based and
              model-free RL. We found evidence to suggest that task complexity
              plays a role in influencing the arbitration process alongside
              state-space uncertainty. Participants tended to increase
              model-based RL control in response to increasing task complexity.
              However, they resorted to model-free RL when both uncertainty and
              task complexity were high, suggesting that these two variables
              interact during the arbitration process. Computational fMRI
              revealed that task complexity interacts with neural
              representations of the reliability of the two systems in the
              inferior prefrontal cortex bilaterally. These findings provide
              insight into how the inferior prefrontal cortex negotiates the
              trade-off between model-based and model-free RL in the presence
              of uncertainty and complexity, and more generally, illustrates
              how the brain resolves uncertainty and complexity in dynamically
              changing environment.",
  journal  = "bioRxiv",
  pages    = "393983",
  month    =  aug,
  year     =  2018,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Niv2006-yu,
  title     = "A normative perspective on motivation",
  author    = "Niv, Y and Joel, D and Dayan, P",
  abstract  = "Understanding the effects of motivation on instrumental action
               selection, and specifically on its two main forms, goal-directed
               and habitual control, is fundamental to the study of decision
               making. Motivational states have been shown to
               'direct'goal-directed behavior rather straightforwardly towards
               more valuable outcomes. However, how motivational states can
               influence outcome-insensitive habitual behavior is more
               mysterious. We adopt a normative perspective, assuming that
               animals seek to maximize the utilities they achieve, and viewing
               …",
  journal   = "Trends Cogn. Sci.",
  publisher = "Elsevier",
  year      =  2006
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Van_der_Meer2012-lh,
  title     = "Information processing in decision-making systems",
  author    = "van der Meer, M and Kurth-Nelson, Z and {others}",
  abstract  = "Decisions result from an interaction between multiple functional
               systems acting in parallel to process information in very
               different ways, each with strengths and weaknesses. In this
               review, the authors address three action-selection components of
               decision-making: The Pavlovian system releases an action from a
               limited repertoire of potential actions, such as approaching
               learned stimuli. Like the Pavlovian system, the habit system is
               computationally fast but, unlike the Pavlovian system permits
               arbitrary stimulus-action pairings. These …",
  journal   = "The",
  publisher = "journals.sagepub.com",
  year      =  2012
}

@ARTICLE{Gardner2013-bg,
  title    = "A secondary working memory challenge preserves primary place
              strategies despite overtraining",
  author   = "Gardner, Robert S and Uttaro, Michael R and Fleming, Samantha E
              and Suarez, Daniel F and Ascoli, Giorgio A and Dumas, Theodore C",
  abstract = "Learning by repetition engages distinct cognitive strategies
              whose contributions are adjusted with experience. Early in
              learning, performance relies upon flexible, attentive strategies.
              With extended practice, inflexible, automatic strategies emerge.
              This transition is thought fundamental to habit formation and
              applies to human and animal cognition. In the context of spatial
              navigation, place strategies are flexible, typically employed
              early in training, and rely on the spatial arrangement of
              landmarks to locate a goal. Response strategies are inflexible,
              become dominant after overtraining, and utilize fixed motor
              sequences. Although these strategies can operate independently,
              they have also been shown to interact. However, since previous
              work has focused on single-choice learning, if and how these
              strategies interact across sequential choices remains unclear. To
              test strategy interactions across sequential choices, we utilized
              various two-choice spatial navigation tasks administered on the
              Opposing Ts maze, an apparatus for rodents that permits
              experimental control over strategy recruitment. We found that
              when a second choice required spatial working memory, the
              transition to response navigation on the first choice was
              blocked. Control experiments specified this effect to the
              cognitive aspects of the secondary task. In addition, response
              navigation, once established on a single choice, was not reversed
              by subsequent introduction of a secondary choice reliant on
              spatial working memory. These results demonstrate that
              performance strategies interact across choices, highlighting the
              sensitivity of strategy use to the cognitive demands of
              subsequent actions, an influence from which overtrained rigid
              actions may be protected.",
  journal  = "Learn. Mem.",
  volume   =  20,
  number   =  11,
  pages    = "648--656",
  month    =  oct,
  year     =  2013,
  language = "en"
}

@ARTICLE{Hasz2018-hy,
  title    = "Deliberation and Procedural Automation on a {Two-Step} Task for
              Rats",
  author   = "Hasz, Brendan M and Redish, A David",
  abstract = "Current theories suggest that decision-making arises from
              multiple systems. Human studies dissociate model-based and
              model-free systems, while rodent studies dissociate deliberation
              and habit. However, the relationship between these constructs
              remains unresolved. We adapted for rats a two-step task which has
              been used to dissociate model based from model-free decisions in
              humans. We found that an uncertainty-based algorithm predicted
              rats' choices on the maze better than an algorithm with a
              constant weighting between systems, supporting theoretical work
              suggesting decision-making systems are more likely to be used
              when their valuation is less uncertain. We also found that path
              stereotypy, a measure of behavioral consistency associated with
              procedural learning, was correlated with model-free certainty,
              while vicarious trial and error, a deliberative behavior, was
              increased during model-free uncertainty.",
  journal  = "Front. Integr. Neurosci.",
  volume   =  12,
  pages    = "30",
  year     =  2018
}

@ARTICLE{McNaughton2018-bc,
  title    = "Survival circuits and risk assessment",
  author   = "McNaughton, Neil and Corr, Philip J",
  abstract = "Risk assessment (RA) behaviour is unusual in the context of
              survival circuits. An external object elicits eating, mating or
              fleeing; but conflict between internal approach and withdrawal
              tendencies elicits RA-specific behaviour that scans the
              environment for new information to bring closure. Recently rodent
              and human threat responses have been compared using `predators'
              that can be real (e.g. a tarantula), robot, virtual, or symbolic
              (with the last three rendered predatory by the use of shock).
              `Quick and dirty' survival circuits in the periaqueductal grey,
              hypothalamus, and amygdala control external RA behaviour. These
              subcortical circuits activate, and are partially inhibited by,
              higher-order internal RA processes (anxiety, memory scanning,
              evaluation and sometimes---maladaptive rumination) in the ventral
              hippocampus and medial prefrontal cortex.",
  journal  = "Current Opinion in Behavioral Sciences",
  volume   =  24,
  pages    = "14--20",
  month    =  dec,
  year     =  2018
}

@UNPUBLISHED{Javer2018-js,
  title    = "Powerful and interpretable behavioural features for quantitative
              phenotyping of C. elegans",
  author   = "Javer, Avelino and Ripoll-Sanchez, Lidia and Brown, Andr{\'e} E X",
  abstract = "Behaviour is a sensitive and integrative readout of nervous
              system function and therefore an attractive measure for assessing
              the effects of mutation or drug treatment on animals. Video data
              provides a rich but high-dimensional representation of behaviour
              and so the first step of analysis is often some form of tracking
              and feature extraction to reduce dimensionality while maintaining
              relevant information. Modern machine learning methods are
              powerful but notoriously difficult to interpret, while
              handcrafted features are interpretable but do not always perform
              as well. Here we report a new set of handcrafted features to
              compactly quantify C. elegans behaviour. The features are
              designed to be interpretable but to capture as much of the
              phenotypic differences between worms as possible. We show that
              the full feature set is more powerful than a previously defined
              feature set in classifying mutant strains. We then use a
              combination of automated and manual feature selection to define a
              core set of interpretable features that still provides sufficient
              power to detect behavioural differences between mutant strains
              and the wild type. Finally, we apply the new features to detect
              time- resolved behavioural differences in a series of optogenetic
              experiments targeting different neural subsets.",
  journal  = "bioRxiv",
  pages    = "389023",
  month    =  aug,
  year     =  2018,
  language = "en"
}

@ARTICLE{Laubach2018-sh,
  title     = "What, if anything, is rodent prefrontal cortex?",
  author    = "Laubach, Mark and Amarante, Linda and Swanson, Kyra and White,
               Samantha R",
  publisher = "PsyArXiv",
  year      =  2018
}

@ARTICLE{Stern2015-kb,
  title    = "Analyzing animal behavior via classifying each video frame using
              convolutional neural networks",
  author   = "Stern, Ulrich and He, Ruo and Yang, Chung-Hui",
  abstract = "High-throughput analysis of animal behavior requires software to
              analyze videos. Such software analyzes each frame individually,
              detecting animals' body parts. But the image analysis rarely
              attempts to recognize ``behavioral states''-e.g., actions or
              facial expressions-directly from the image instead of using the
              detected body parts. Here, we show that convolutional neural
              networks (CNNs)-a machine learning approach that recently became
              the leading technique for object recognition, human pose
              estimation, and human action recognition-were able to recognize
              directly from images whether Drosophila were ``on'' (standing or
              walking) or ``off'' (not in physical contact with) egg-laying
              substrates for each frame of our videos. We used multiple nets
              and image transformations to optimize accuracy for our
              classification task, achieving a surprisingly low error rate of
              just 0.072\%. Classifying one of our 8 h videos took less than 3
              h using a fast GPU. The approach enabled uncovering a novel
              egg-laying-induced behavior modification in Drosophila.
              Furthermore, it should be readily applicable to other behavior
              analysis tasks.",
  journal  = "Sci. Rep.",
  volume   =  5,
  pages    = "14351",
  month    =  sep,
  year     =  2015,
  keywords = "Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Felsen2012-ng,
  title    = "Midbrain contributions to sensorimotor decision making",
  author   = "Felsen, Gidon and Mainen, Zachary F",
  abstract = "Making decisions about future actions is a fundamental function
              of the nervous system. Classical theories hold that separate sets
              of brain regions are responsible for selecting and implementing
              an action. Traditionally, action selection has been considered
              the domain of high-level regions, such as the prefrontal cortex,
              whereas action generation is thought to be carried out by
              dedicated cortical and subcortical motor regions. However,
              increasing evidence suggests that the activity of individual
              neurons in cortical motor structures reflects abstract properties
              of ``decision variables'' rather than conveying simple motor
              commands. Less is known, though, about the role of subcortical
              structures in decision making. In particular, the superior
              colliculus (SC) is critical for planning and initiating visually
              guided, gaze-displacing movements and selecting visual targets,
              but whether and how it contributes more generally to sensorimotor
              decisions are unclear. Here, we show that the SC is intimately
              involved in orienting decisions based on odor cues, even though
              the SC does not explicitly process olfactory stimuli. Neurons
              were recorded from the intermediate and deep SC layers in rats
              trained to perform a delayed-response, odor-cued spatial choice
              task. SC neurons commonly fired well in advance of movement
              initiation, predicting the chosen direction nearly 1 s before
              movement. Moreover, under conditions of sensory uncertainty, SC
              activity varied with task difficulty and reward outcome,
              reflecting the influence of decision variables on the
              intercollicular competition thought to underlie orienting
              movements. These results indicate that the SC plays a more
              general role in decisions than previously appreciated, extending
              beyond visuomotor functions.",
  journal  = "J. Neurophysiol.",
  volume   =  108,
  number   =  1,
  pages    = "135--147",
  month    =  jul,
  year     =  2012,
  language = "en"
}

@ARTICLE{Anderson2014-hr,
  title    = "Toward a science of computational ethology",
  author   = "Anderson, David J and Perona, Pietro",
  abstract = "The new field of ``Computational Ethology'' is made possible by
              advances in technology, mathematics, and engineering that allow
              scientists to automate the measurement and the analysis of animal
              behavior. We explore the opportunities and long-term directions
              of research in this area.",
  journal  = "Neuron",
  volume   =  84,
  number   =  1,
  pages    = "18--31",
  month    =  oct,
  year     =  2014,
  language = "en"
}

@ARTICLE{Kastner2013-gi,
  title    = "When can a Computer Simulation act as Substitute for an
              Experiment? A {Case-Study} from Chemisty",
  author   = "K{\"a}stner, Johannes and Arnold, Eckhart",
  year     =  2013,
  keywords = "Theoretical"
}

@INCOLLECTION{Peschard2013-ga,
  title     = "Modeling and experimenting",
  booktitle = "Models, simulations, and representations",
  author    = "Peschard, Isabelle",
  publisher = "Routledge",
  pages     = "60--79",
  year      =  2013,
  keywords  = "Theoretical"
}

@ARTICLE{Peschard2011-sz,
  title    = "Is Simulation an Epistemic Substitute for Experimentation?",
  author   = "Peschard, Isabelle",
  abstract = "It is sometimes said that simulation can serve as epistemic
              substitute for experimentation. Such a claim might be suggested
              by the fast-spreading use of computer simulation to investigate
              phenomena not accessible to experimentation (in astrophysics,
              ecology, economics, climatology, etc.). But what does that mean?
              The paper starts with a clarification of the terms of the issue
              and then focuses on two powerful arguments for the view that
              simulation and experimentation are `epistemically on a par'. One
              is based on the claim that, in experimentation, no less than in
              simulation, it is not the system under study that is manipulated
              but a system that `stands-in' for it. The other one highlights
              the pervasive use of models in experimentation. It will be argued
              that these arguments, as compelling as they might seem, are each
              based on a mistaken interpretation of experimentation and that,
              far from simulation and experimentation being epistemically on a
              par, they do not have the same epistemic function, do not produce
              the same kind of epistemic results.",
  month    =  aug,
  year     =  2011,
  keywords = "simulation, experiment, experimentation, substitute, modeling,
              target system, surrogate.;Theoretical",
  language = "en"
}

@INCOLLECTION{Guala2002-ap,
  title     = "Models, Simulations, and Experiments",
  booktitle = "{Model-Based} Reasoning: Science, Technology, Values",
  author    = "Guala, Francesco",
  editor    = "Magnani, Lorenzo and Nersessian, Nancy J",
  abstract  = "I discuss the difference between models, simulations, and
               experiments from an epistemological and an ontological
               perspective. I first distinguish between ``static'' models (like
               a map) and ``dynamic'' models endowed with the capacity to
               generate processes. Only the latter can be used to simulate. I
               then criticize the view according to which the difference
               between models/simulations and experiments is fundamentally
               epistemic in character. Following Herbert Simon, I argue that
               the difference is ontological. Simulations merely require the
               existence of an abstract correspondence between the simulating
               and the simulated system. In experiments, in contrast, the
               causal relations governing the experimental and the target
               systems are grounded in the same material. Simulations can
               produce new knowledge just as experiments do, but the prior
               knowledge needed to run a good simulation is not the same as
               that needed to run a good experiment. I conclude by discussing
               ``hybrid'' cases of ``experimental simulations'' or ``simulating
               experiments''.",
  publisher = "Springer US",
  pages     = "59--74",
  year      =  2002,
  address   = "Boston, MA",
  keywords  = "Theoretical"
}

@ARTICLE{Frigg2009-bp,
  title     = "The philosophy of simulation: hot new issues or same old stew?",
  author    = "Frigg, Roman and Reiss, Julian",
  abstract  = "Computer simulations are an exciting tool that plays important
               roles in many scientific disciplines. This has attracted the
               attention of a number of philosophers of science. The main tenor
               in this literature is that computer simulations not only
               constitute interesting and powerful new science, but that they
               also raise a host of new philosophical issues. The protagonists
               in this debate claim no less than that simulations call into
               question our philosophical understanding of scientific ontology,
               the epistemology and semantics of models and theories, and the
               relation between experimentation and theorising, and submit that
               simulations demand a fundamentally new philosophy of science in
               many respects. The aim of this paper is to critically evaluate
               these claims. Our conclusion will be sober. We argue that these
               claims are overblown and that simulations, far from demanding a
               new metaphysics, epistemology, semantics and methodology, raise
               few if any new philosophical problems. The philosophical
               problems that do come up in connection with simulations are not
               specific to simulations and most of them are variants of
               problems that have been discussed in other contexts before.",
  journal   = "Synthese",
  publisher = "Springer Netherlands",
  volume    =  169,
  number    =  3,
  pages     = "593--613",
  month     =  aug,
  year      =  2009,
  keywords  = "Theoretical",
  language  = "en"
}

@ARTICLE{Huxter2003-tz,
  title    = "Independent rate and temporal coding in hippocampal pyramidal
              cells",
  author   = "Huxter, John and Burgess, Neil and O'Keefe, John",
  abstract = "In the brain, hippocampal pyramidal cells use temporal as well as
              rate coding to signal spatial aspects of the animal's environment
              or behaviour. The temporal code takes the form of a phase
              relationship to the concurrent cycle of the hippocampal
              electroencephalogram theta rhythm. These two codes could each
              represent a different variable. However, this requires the rate
              and phase to vary independently, in contrast to recent
              suggestions that they are tightly coupled, both reflecting the
              amplitude of the cell's input. Here we show that the time of
              firing and firing rate are dissociable, and can represent two
              independent variables: respectively the animal's location within
              the place field, and its speed of movement through the field.
              Independent encoding of location together with actions and
              stimuli occurring there may help to explain the dual roles of the
              hippocampus in spatial and episodic memory, or may indicate a
              more general role of the hippocampus in relational/declarative
              memory.",
  journal  = "Nature",
  volume   =  425,
  number   =  6960,
  pages    = "828--832",
  month    =  oct,
  year     =  2003,
  language = "en"
}

@ARTICLE{Jazayeri2017-on,
  title    = "Navigating the Neural Space in Search of the Neural Code",
  author   = "Jazayeri, Mehrdad and Afraz, Arash",
  abstract = "The advent of powerful perturbation tools, such as optogenetics,
              has created new frontiers for probing causal dependencies in
              neural and behavioral states. These approaches have significantly
              enhanced the ability to characterize the contribution of
              different cells and circuits to neural function in health and
              disease. They have shifted the emphasis of research toward causal
              interrogations and increased the demand for more precise and
              powerful tools to control and manipulate neural activity. Here,
              we clarify the conditions under which measurements and
              perturbations support causal inferences. We note that the brain
              functions at multiple scales and that causal dependencies may be
              best inferred with perturbation tools that interface with the
              system at the appropriate scale. Finally, we develop a geometric
              framework to facilitate the interpretation of causal experiments
              when brain perturbations do or do not respect the intrinsic
              patterns of brain activity. We describe the challenges and
              opportunities of applying perturbations in the presence of
              dynamics, and we close with a general perspective on navigating
              the activity space of neurons in the search for neural codes.",
  journal  = "Neuron",
  volume   =  93,
  number   =  5,
  pages    = "1003--1014",
  month    =  mar,
  year     =  2017,
  keywords = "behavior; causation; correlation; neural code; neural manifold;
              perturbation;Theoretical",
  language = "en"
}

@UNPUBLISHED{Slezak2018-ix,
  title    = "Astrocytes integrate local sensory and brain-wide neuromodulatory
              signals",
  author   = "Slezak, Michal and Kandler, Steffen and Van Veldhoven, Paul P and
              Bonin, Vincent and Holt, Matthew G",
  abstract = "Astrocytes play multiple functions in the central nervous system,
              from control of blood flow through to modulation of synaptic
              activity. Transient increases in intracellular Ca2+ are thought
              to control these activities. The prevailing concept is that these
              Ca2+ transients are triggered by distinct pathways, with little
              mechanistic and functional overlap. Here we demonstrate that
              astrocytes in visual cortex of mice encode local visual signals
              in conjunction with arousal state, functioning as multi-modal
              integrators. Such activity adds an additional layer of complexity
              to astrocyte function and may enable astrocytes to specifically
              and subtly regulate local network activity and plasticity.",
  journal  = "bioRxiv",
  pages    = "381434",
  month    =  jul,
  year     =  2018,
  language = "en"
}

@ARTICLE{Kaplan2011-vm,
  title     = "Explanation and description in computational neuroscience",
  author    = "Kaplan, David Michael",
  abstract  = "The central aim of this paper is to shed light on the nature of
               explanation in computational neuroscience. I argue that
               computational models in this domain possess explanatory force to
               the extent that they describe the mechanisms responsible for
               producing a given phenomenon---paralleling how other mechanistic
               models explain. Conceiving computational explanation as a
               species of mechanistic explanation affords an important
               distinction between computational models that play genuine
               explanatory roles and those that merely provide accurate
               descriptions or predictions of phenomena. It also serves to
               clarify the pattern of model refinement and elaboration
               undertaken by computational neuroscientists.",
  journal   = "Synthese",
  publisher = "Springer Netherlands",
  volume    =  183,
  number    =  3,
  pages     = "339",
  month     =  dec,
  year      =  2011,
  keywords  = "Theoretical",
  language  = "en"
}

@UNPUBLISHED{George2018-aw,
  title    = "Cortical Microcircuits from a Generative Vision Model",
  author   = "George, Dileep and Lavin, Alexander and Swaroop Guntupalli, J and
              Mely, David and Hay, Nick and Lazaro-Gredilla, Miguel",
  abstract = "Understanding the information processing roles of cortical
              circuits is an outstanding problem in neuroscience and artificial
              intelligence. The theoretical setting of Bayesian inference has
              been suggested as a framework for understanding cortical
              computation. Based on a recently published generative model for
              visual inference (George et al., 2017), we derive a family of
              anatomically instantiated and functional cortical circuit models.
              In contrast to simplistic models of Bayesian inference, the
              underlying generative model9s representational choices are
              validated with real-world tasks that required efficient inference
              and strong generalization. The cortical circuit model is derived
              by systematically comparing the computational requirements of
              this model with known anatomical constraints. The derived model
              suggests precise functional roles for the feedforward, feedback
              and lateral connections observed in different laminae and
              columns, and assigns a computational role for the path through
              the thalamus.",
  journal  = "bioRxiv",
  pages    = "379313",
  month    =  aug,
  year     =  2018,
  language = "en"
}

@UNPUBLISHED{Genewsky2018-bj,
  title    = "How much fear is in anxiety?",
  author   = "Genewsky, Andreas and Albrecht, Nina and Bura, Simona A and
              Kaplick, Paul M and Heinz, Daniel E and Nu{\ss}baumer, Markus and
              Engel, Mareen and Gr{\"u}necker, Barbara and Kaltwasser,
              Sebastian F and Riebe, Caitlin J and Bedenk, Benedikt T and
              Czisch, Michael and Wotjak, Carsten T",
  abstract = "The selective breeding for extreme behavior on the elevated
              plus-maze (EPM) resulted in two mouse lines namely high-anxiety
              behaving (HAB) and low-anxiety behaving (LAB) mice. Using novel
              behavioral tests we demonstrate that HAB animals additionally
              exhibit maladaptive escape behavior and defensive vocalizations,
              whereas LAB mice show profound deficits in escaping from
              approaching threats which partially results from sensory
              deficits. We could relate these behavioral distortions to tonic
              changes in brain activity within the periaqueductal gray (PAG) in
              HAB mice and the superior colliculus (SC) in LAB mice, using in
              vivo manganese-enhanced MRI (MEMRI) followed by pharmacological
              or chemogenetic interventions. Therefore, midbrain-tectal
              structures govern the expression of both anxiety-like behavior
              and defensive responses. Our results challenge the uncritical use
              of the anthropomorphic terms anxiety or anxiety-like for the
              description of mouse behavior, as they imply higher cognitive
              processes, which are not necessarily in place.",
  journal  = "bioRxiv",
  pages    = "385823",
  month    =  aug,
  year     =  2018,
  keywords = "Threat response",
  language = "en"
}

@ARTICLE{Juavinett2018-al,
  title    = "Decision-making behaviors: weighing ethology, complexity, and
              sensorimotor compatibility",
  author   = "Juavinett, Ashley L and Erlich, Jeffrey C and Churchland, Anne K",
  abstract = "Rodent decision-making research aims to uncover the neural
              circuitry underlying the ability to evaluate alternatives and
              select appropriate actions. Designing behavioral paradigms that
              provide a solid foundation to ask questions about decision-making
              computations and mechanisms is a difficult and often
              underestimated challenge. Here, we propose three dimensions on
              which we can consider rodent decision-making tasks: ethological
              validity, task complexity, and stimulus-response compatibility.
              We review recent research through this lens, and provide
              practical guidance for researchers in the decision-making field.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  49,
  pages    = "42--50",
  month    =  apr,
  year     =  2018,
  keywords = "Decision Making",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Meyer2018-ex,
  title     = "An ultralight head-mounted camera system integrates detailed
               behavioral monitoring with multichannel electrophysiology in
               freely moving mice",
  author    = "Meyer, A F and Poort, J and O'Keefe, J and Sahani, M and Linden,
               J F",
  abstract  = "Breakthroughs in understanding the neural basis of natural
               behavior require neural recording and intervention to be paired
               with high-fidelity multimodal behavioral monitoring. An
               extensive genetic toolkit for neural circuit dissection, and
               well-developed neural recording technology, make the mouse a
               powerful model organism for systems neuroscience. However,
               methods for high-bandwidth acquisition of behavioral signals in
               mice remain limited to fixed-position cameras and other
               off-animal devices, complicating the …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2018,
  keywords  = "Analysis/Modelling [Behaviour]"
}

@ARTICLE{Sejnowski2014-rn,
  title     = "Putting big data to good use in neuroscience",
  author    = "Sejnowski, Terrence J and Churchland, Patricia S and Movshon, J
               Anthony",
  abstract  = "Big data has transformed fields such as physics and genomics.
               Neuroscience is set to collect its own big data sets, but to
               exploit its full potential, there need to be ways to
               standardize, integrate and synthesize diverse types of data from
               different levels of analysis and across species. This will
               require a cultural shift in sharing data across labs, as well as
               to a central role for theorists in neuroscience research.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  17,
  number    =  11,
  pages     = "1440--1441",
  month     =  nov,
  year      =  2014,
  keywords  = "Theoretical",
  language  = "en"
}

@ARTICLE{Carandini2013-hh,
  title     = "Probing perceptual decisions in rodents",
  author    = "Carandini, Matteo and Churchland, Anne K",
  abstract  = "The study of perceptual decision-making offers insight into how
               the brain uses complex, sometimes ambiguous information to guide
               actions. Understanding the underlying processes and their neural
               bases requires that one pair recordings and manipulations of
               neural activity with rigorous psychophysics. Though this
               research has been traditionally performed in primates, it seems
               increasingly promising to pursue it at least partly in mice and
               rats. However, rigorous psychophysical methods are not yet as
               developed for these rodents as they are for primates. Here we
               give a brief overview of the sensory capabilities of rodents and
               of their cortical areas devoted to sensation and decision. We
               then review methods of psychophysics, focusing on the technical
               issues that arise in their implementation in rodents. These
               methods represent a rich set of challenges and opportunities.",
  journal   = "Nat. Neurosci.",
  publisher = "nature.com",
  volume    =  16,
  number    =  7,
  pages     = "824--831",
  month     =  jul,
  year      =  2013,
  keywords  = "Decision Making",
  language  = "en"
}

@ARTICLE{Shadlen2013-hz,
  title     = "Decision making as a window on cognition",
  author    = "Shadlen, Michael N and Kiani, Roozbeh",
  abstract  = "A decision is a commitment to a proposition or plan of action
               based on information and values associated with the possible
               outcomes. The process operates in a flexible timeframe that is
               free from the immediacy of evidence acquisition and the real
               time demands of action itself. Thus, it involves deliberation,
               planning, and strategizing. This Perspective focuses on
               perceptual decision making in nonhuman primates and the
               discovery of neural mechanisms that support accuracy, speed, and
               confidence in a decision. We suggest that these mechanisms
               expose principles of cognitive function in general, and we
               speculate about the challenges and directions before the field.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  80,
  number    =  3,
  pages     = "791--806",
  month     =  oct,
  year      =  2013,
  keywords  = "Decision Making",
  language  = "en"
}

@ARTICLE{DeCharms2000-ng,
  title     = "Neural representation and the cortical code",
  author    = "deCharms, R C and Zador, A",
  abstract  = "The principle function of the central nervous system is to
               represent and transform information and thereby mediate
               appropriate decisions and behaviors. The cerebral cortex is one
               of the primary seats of the internal representations maintained
               and used in perception, memory, decision making, motor control,
               and subjective experience, but the basic coding scheme by which
               this information is carried and transformed by neurons is not
               yet fully understood. This article defines and reviews how
               information is represented in the firing rates and temporal
               patterns of populations of cortical neurons, with a particular
               emphasis on how this information mediates behavior and
               experience.",
  journal   = "Annu. Rev. Neurosci.",
  publisher = "annualreviews.org",
  volume    =  23,
  pages     = "613--647",
  year      =  2000,
  keywords  = "Theoretical",
  language  = "en"
}

@ARTICLE{Bastos2012-fc,
  title    = "Canonical microcircuits for predictive coding",
  author   = "Bastos, Andre M and Usrey, W Martin and Adams, Rick A and Mangun,
              George R and Fries, Pascal and Friston, Karl J",
  abstract = "This Perspective considers the influential notion of a canonical
              (cortical) microcircuit in light of recent theories about
              neuronal processing. Specifically, we conciliate quantitative
              studies of microcircuitry and the functional logic of neuronal
              computations. We revisit the established idea that message
              passing among hierarchical cortical areas implements a form of
              Bayesian inference-paying careful attention to the implications
              for intrinsic connections among neuronal populations. By deriving
              canonical forms for these computations, one can associate
              specific neuronal populations with specific computational roles.
              This analysis discloses a remarkable correspondence between the
              microcircuitry of the cortical column and the connectivity
              implied by predictive coding. Furthermore, it provides some
              intuitive insights into the functional asymmetries between
              feedforward and feedback connections and the characteristic
              frequencies over which they operate.",
  journal  = "Neuron",
  volume   =  76,
  number   =  4,
  pages    = "695--711",
  month    =  nov,
  year     =  2012,
  keywords = "Theoretical",
  language = "en"
}

@ARTICLE{Spratling2017-te,
  title    = "A review of predictive coding algorithms",
  author   = "Spratling, M W",
  abstract = "Predictive coding is a leading theory of how the brain performs
              probabilistic inference. However, there are a number of distinct
              algorithms which are described by the term ``predictive coding''.
              This article provides a concise review of these different
              predictive coding algorithms, highlighting their similarities and
              differences. Five algorithms are covered: linear predictive
              coding which has a long and influential history in the signal
              processing literature; the first neuroscience-related application
              of predictive coding to explaining the function of the retina;
              and three versions of predictive coding that have been proposed
              to model cortical function. While all these algorithms aim to fit
              a generative model to sensory data, they differ in the type of
              generative model they employ, in the process used to optimise the
              fit between the model and sensory data, and in the way that they
              are related to neurobiology.",
  journal  = "Brain Cogn.",
  volume   =  112,
  pages    = "92--97",
  month    =  mar,
  year     =  2017,
  keywords = "Cortex; Free energy; Neural networks; Predictive coding; Retina;
              Signal processing;Theoretical",
  language = "en"
}

@UNPUBLISHED{Gomez-Marin2014-qb,
  title    = "Big Behavioral Data: Psychology, Ethology and the Foundations of
              Neuroscience",
  author   = "Gomez-Marin, Alex and Paton, Joseph J and Kampff, Adam R and
              Costa, Rui M and Mainen, Zachary M",
  abstract = "Behavior is a unifying organismal process where genes, neural
              function, anatomy and environment converge and interrelate. Here
              we review the current state and discuss the future impact of
              accelerating advances in technology for behavioral studies,
              focusing on rodents as an exemplar. We frame our perspective in
              three dimensions: degree of experimental constraint,
              dimensionality of data, and level of description. We argue that
              ``big behavioral data'' presents challenges proportionate to its
              promise and describe how these challenges might be met through
              opportunities afforded by the two rival conceptual legacies of
              20th century behavioral science, ethology and psychology. We
              conclude that although ``more is not necessarily better'',
              copious, quantitative and open behavioral data has the potential
              to transform and unify these two disciplines and to solidify the
              foundations of others, including neuroscience, but only if the
              development of novel theoretical frameworks and improved
              experimental designs matches the technological progress.",
  journal  = "bioRxiv",
  pages    = "006809",
  month    =  jul,
  year     =  2014,
  keywords = "Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Dudman2016-gy,
  title    = "The basal ganglia: from motor commands to the control of vigor",
  author   = "Dudman, Joshua T and Krakauer, John W",
  abstract = "Vertebrates are remarkable for their ability to select and
              execute goal-directed actions: motor skills critical for thriving
              in complex, competitive environments. A key aspect of a motor
              skill is the ability to execute its component movements over a
              range of speeds, amplitudes and frequencies (vigor). Recent work
              has indicated that a subcortical circuit, the basal ganglia, is a
              critical determinant of movement vigor in rodents and primates.
              We propose that the basal ganglia evolved from a circuit that in
              lower vertebrates and some mammals is sufficient to directly
              command simple or stereotyped movements to one that indirectly
              controls the vigor of goal-directed movements. The implications
              of a dual role of the basal ganglia in the control of vigor and
              response to reward are also discussed.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  37,
  pages    = "158--166",
  month    =  apr,
  year     =  2016,
  language = "en"
}

@ARTICLE{Brody2016-ud,
  title    = "Neural underpinnings of the evidence accumulator",
  author   = "Brody, Carlos D and Hanks, Timothy D",
  abstract = "Gradual accumulation of evidence favoring one or another choice
              is considered a core component of many different types of
              decisions, and has been the subject of many neurophysiological
              studies in non-human primates. But its neural circuit mechanisms
              remain mysterious. Investigating it in rodents has recently
              become possible, facilitating perturbation experiments to
              delineate the relevant causal circuit, as well as the application
              of other tools more readily available in rodents. In addition,
              advances in stimulus design and analysis have aided studying the
              relevant neural encoding. In complement to ongoing non-human
              primate studies, these newly available model systems and tools
              place the field at an exciting time that suggests that the
              dynamical circuit mechanisms underlying accumulation of evidence
              could soon be revealed.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  37,
  pages    = "149--157",
  month    =  apr,
  year     =  2016,
  language = "en"
}

@ARTICLE{Fetsch2016-zu,
  title    = "The importance of task design and behavioral control for
              understanding the neural basis of cognitive functions",
  author   = "Fetsch, Christopher R",
  abstract = "The success of systems neuroscience depends on the ability to
              forge quantitative links between neural activity and behavior.
              Traditionally, this process has benefited from the rigorous
              development and testing of hypotheses using tools derived from
              classical psychophysics and computational motor control. As our
              capacity for measuring neural activity improves, accompanied by
              powerful new analysis strategies, it seems prudent to remember
              what these traditional approaches have to offer. Here I present a
              perspective on the merits of principled task design and tight
              behavioral control, along with some words of caution about
              interpretation in unguided, large-scale neural recording studies.
              I argue that a judicious combination of new and old approaches is
              the best way to advance our understanding of higher brain
              function in health and disease.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  37,
  pages    = "16--22",
  month    =  apr,
  year     =  2016,
  keywords = "Theoretical",
  language = "en"
}

@ARTICLE{Jovanic2016-ok,
  title    = "Competitive Disinhibition Mediates Behavioral Choice and
              Sequences in Drosophila",
  author   = "Jovanic, Tihana and Schneider-Mizell, Casey Martin and Shao, Mei
              and Masson, Jean-Baptiste and Denisov, Gennady and Fetter,
              Richard Doty and Mensh, Brett Daren and Truman, James William and
              Cardona, Albert and Zlatic, Marta",
  abstract = "Even a simple sensory stimulus can elicit distinct innate
              behaviors and sequences. During sensorimotor decisions,
              competitive interactions among neurons that promote distinct
              behaviors must ensure the selection and maintenance of one
              behavior, while suppressing others. The circuit implementation of
              these competitive interactions is still an open question. By
              combining comprehensive electron microscopy reconstruction of
              inhibitory interneuron networks, modeling, electrophysiology, and
              behavioral studies, we determined the circuit mechanisms that
              contribute to the Drosophila larval sensorimotor decision to
              startle, explore, or perform a sequence of the two in response to
              a mechanosensory stimulus. Together, these studies reveal that,
              early in sensory processing, (1) reciprocally connected
              feedforward inhibitory interneurons implement behavioral choice,
              (2) local feedback disinhibition provides positive feedback that
              consolidates and maintains the chosen behavior, and (3) lateral
              disinhibition promotes sequence transitions. The combination of
              these interconnected circuit motifs can implement both behavior
              selection and the serial organization of behaviors into a
              sequence.",
  journal  = "Cell",
  volume   =  167,
  number   =  3,
  pages    = "858--870.e19",
  month    =  oct,
  year     =  2016,
  keywords = "Drosophila; EM connectome; behavioral choice; behavioral
              sequences; disinihibition; recurrent inhibition; sensory
              processing",
  language = "en"
}

@ARTICLE{Stephens2011-ce,
  title    = "Searching for simplicity in the analysis of neurons and behavior",
  author   = "Stephens, Greg J and Osborne, Leslie C and Bialek, William",
  abstract = "What fascinates us about animal behavior is its richness and
              complexity, but understanding behavior and its neural basis
              requires a simpler description. Traditionally, simplification has
              been imposed by training animals to engage in a limited set of
              behaviors, by hand scoring behaviors into discrete classes, or by
              limiting the sensory experience of the organism. An alternative
              is to ask whether we can search through the dynamics of natural
              behaviors to find explicit evidence that these behaviors are
              simpler than they might have been. We review two mathematical
              approaches to simplification, dimensionality reduction and the
              maximum entropy method, and we draw on examples from different
              levels of biological organization, from the crawling behavior of
              Caenorhabditis elegans to the control of smooth pursuit eye
              movements in primates, and from the coding of natural scenes by
              networks of neurons in the retina to the rules of English
              spelling. In each case, we argue that the explicit search for
              simplicity uncovers new and unexpected features of the biological
              system and that the evidence for simplification gives us a
              language with which to phrase new questions for the next
              generation of experiments. The fact that similar mathematical
              structures succeed in taming the complexity of very different
              biological systems hints that there is something more general to
              be discovered.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   = "108 Suppl 3",
  pages    = "15565--15571",
  month    =  sep,
  year     =  2011,
  keywords = "Analysis/Modelling [Behaviour];Theoretical",
  language = "en"
}

@ARTICLE{Stephens2008-vt,
  title    = "Dimensionality and dynamics in the behavior of C. elegans",
  author   = "Stephens, Greg J and Johnson-Kerner, Bethany and Bialek, William
              and Ryu, William S",
  abstract = "A major challenge in analyzing animal behavior is to discover
              some underlying simplicity in complex motor actions. Here, we
              show that the space of shapes adopted by the nematode
              Caenorhabditis elegans is low dimensional, with just four
              dimensions accounting for 95\% of the shape variance. These
              dimensions provide a quantitative description of worm behavior,
              and we partially reconstruct ``equations of motion'' for the
              dynamics in this space. These dynamics have multiple attractors,
              and we find that the worm visits these in a rapid and almost
              completely deterministic response to weak thermal stimuli.
              Stimulus-dependent correlations among the different modes suggest
              that one can generate more reliable behaviors by synchronizing
              stimuli to the state of the worm in shape space. We confirm this
              prediction, effectively ``steering'' the worm in real time.",
  journal  = "PLoS Comput. Biol.",
  volume   =  4,
  number   =  4,
  pages    = "e1000028",
  month    =  apr,
  year     =  2008,
  keywords = "Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Poehlmann2018-yj,
  title    = "A unifying model to predict multiple object orienting behaviors
              in tethered flies",
  author   = "Poehlmann, A and Soselisa, S and Fenk, L and Straw, A",
  journal  = "BiorXiv",
  year     =  2018,
  keywords = "Analysis/Modelling [Behaviour]"
}

@ARTICLE{Todd2017-xy,
  title    = "Systematic exploration of unsupervised methods for mapping
              behavior",
  author   = "Todd, Jeremy G and Kain, Jamey S and de Bivort, Benjamin L",
  abstract = "To fully understand the mechanisms giving rise to behavior, we
              need to be able to precisely measure it. When coupled with large
              behavioral data sets, unsupervised clustering methods offer the
              potential of unbiased mapping of behavioral spaces. However,
              unsupervised techniques to map behavioral spaces are in their
              infancy, and there have been few systematic considerations of all
              the methodological options. We compared the performance of seven
              distinct mapping methods in clustering a wavelet-transformed data
              set consisting of the x- and y-positions of the six legs of
              individual flies. Legs were automatically tracked by small pieces
              of fluorescent dye, while the fly was tethered and walking on an
              air-suspended ball. We find that there is considerable variation
              in the performance of these mapping methods, and that better
              performance is attained when clustering is done in higher
              dimensional spaces (which are otherwise less preferable because
              they are hard to visualize). High dimensionality means that some
              algorithms, including the non-parametric watershed cluster
              assignment algorithm, cannot be used. We developed an alternative
              watershed algorithm which can be used in high-dimensional spaces
              when a probability density estimate can be computed directly.
              With these tools in hand, we examined the behavioral space of fly
              leg postural dynamics and locomotion. We find a striking division
              of behavior into modes involving the fore legs and modes
              involving the hind legs, with few direct transitions between
              them. By computing behavioral clusters using the data from all
              flies simultaneously, we show that this division appears to be
              common to all flies. We also identify individual-to-individual
              differences in behavior and behavioral transitions. Lastly, we
              suggest a computational pipeline that can achieve satisfactory
              levels of performance without the taxing computational demands of
              a systematic combinatorial approach.",
  journal  = "Phys. Biol.",
  volume   =  14,
  number   =  1,
  pages    = "015002",
  month    =  feb,
  year     =  2017,
  keywords = "Analysis/Modelling [Behaviour]",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Miller2018-vn,
  title     = "Retrosplenial cortical representations of space and future goal
               locations develop with learning",
  author    = "Miller, A M P and Mau, W and Smith, D M",
  abstract  = "The retrosplenial cortex (RSC) is important for long-term
               contextual memory and spatial navigation, but little is known
               about how RSC neural representations develop with experience. We
               recorded neuronal activity in the RSC of rats as they learned a
               continuous spatial alternation task and found that the RSC
               slowly developed a population-level representation of the rat9s
               spatial location and current trajectory to the goal. After the
               rats reached peak performance, RSC firing patterns became
               predictive of navigation accuracy …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2018,
  keywords  = "Spatial Navigation"
}

@ARTICLE{Krakauer2017-va,
  title    = "Neuroscience Needs Behavior: Correcting a Reductionist Bias",
  author   = "Krakauer, John W and Ghazanfar, Asif A and Gomez-Marin, Alex and
              MacIver, Malcolm A and Poeppel, David",
  abstract = "There are ever more compelling tools available for neuroscience
              research, ranging from selective genetic targeting to optogenetic
              circuit control to mapping whole connectomes. These approaches
              are coupled with a deep-seated, often tacit, belief in the
              reductionist program for understanding the link between the brain
              and behavior. The aim of this program is causal explanation
              through neural manipulations that allow testing of necessity and
              sufficiency claims. We argue, however, that another equally
              important approach seeks an alternative form of understanding
              through careful theoretical and experimental decomposition of
              behavior. Specifically, the detailed analysis of tasks and of the
              behavior they elicit is best suited for discovering component
              processes and their underlying algorithms. In most cases, we
              argue that study of the neural implementation of behavior is best
              investigated after such behavioral work. Thus, we advocate a more
              pluralistic notion of neuroscience when it comes to the
              brain-behavior relationship: behavioral work provides
              understanding, whereas neural interventions test causality.",
  journal  = "Neuron",
  volume   =  93,
  number   =  3,
  pages    = "480--490",
  month    =  feb,
  year     =  2017,
  keywords = "Theoretical",
  language = "en"
}

@ARTICLE{Egnor2016-ix,
  title    = "Computational Analysis of Behavior",
  author   = "Egnor, S E Roian and Branson, Kristin",
  abstract = "In this review, we discuss the emerging field of computational
              behavioral analysis-the use of modern methods from computer
              science and engineering to quantitatively measure animal
              behavior. We discuss aspects of experiment design important to
              both obtaining biologically relevant behavioral data and enabling
              the use of machine vision and learning techniques for automation.
              These two goals are often in conflict. Restraining or restricting
              the environment of the animal can simplify automatic behavior
              quantification, but it can also degrade the quality or alter
              important aspects of behavior. To enable biologists to design
              experiments to obtain better behavioral measurements, and
              computer scientists to pinpoint fruitful directions for algorithm
              improvement, we review known effects of artificial manipulation
              of the animal on behavior. We also review machine vision and
              learning techniques for tracking, feature extraction, automated
              behavior classification, and automated behavior discovery, the
              assumptions they make, and the types of data they work best with.",
  journal  = "Annu. Rev. Neurosci.",
  volume   =  39,
  pages    = "217--236",
  month    =  jul,
  year     =  2016,
  keywords = "animal behavior; automated behavioral analysis; computer vision;
              machine learning; tracking;Analysis/Modelling [Behaviour]",
  language = "en"
}

@UNPUBLISHED{Goode2018-px,
  title    = "Bed nucleus of the stria terminalis mediates fear to ambiguous
              threat signals",
  author   = "Goode, Travis D and Ressler, Reed L and Acca, Gillian M and
              Maren, Stephen",
  abstract = "The bed nucleus of the stria terminalis (BNST) has been
              implicated in fear and anxiety, but the specific factors that
              engage the BNST in defensive behavior are unclear. Here we
              explore the possibility that ambiguous threats recruit the BNST
              during Pavlovian fear conditioning in rats. We arranged a
              conditioned stimulus (CS) to either precede or follow an aversive
              unconditioned stimulus (US), a procedure that established
              reliable (forward) or ambiguous (backward) signals for US onset.
              After conditioning, reversible inactivation of the BNST
              selectively reduced freezing to the backward CS; BNST
              inactivation did not affect freezing to the forward CS even when
              that CS predicted a variable magnitude US. Backward CSs increased
              Fos in the ventral BNST and in BNST-projecting neurons in the
              infralimbic cortex, but not the hippocampus or amygdala. These
              data reveal that BNST circuits process ambiguous threat signals
              central to the etiology and expression of anxiety.",
  journal  = "bioRxiv",
  pages    = "376228",
  month    =  jul,
  year     =  2018,
  keywords = "Threat response",
  language = "en"
}

@ARTICLE{Atiya_undated-kw,
  title    = "Neural Circuit Mechanism of Decision Uncertainty and
              {Change-of-Mind}",
  author   = "Atiya, N and Ra{\~n}{\'o}, I and Prasad, G and Wong-Lin, K",
  journal  = "BiorXiv",
  keywords = "Decision Making;Theoretical"
}

@ARTICLE{Clark_undated-jz,
  title    = "Identifying the cognitive processes underpinning
              hippocampal-dependent tasks",
  author   = "Clark, I and Hotchin, V and Monk, A and Pizzamiglio, G and
              Liefgreen, A and Maguire, E",
  keywords = "Spatial Navigation"
}

@ARTICLE{Tingley2018-yq,
  title    = "Transformation of a Spatial Map across the {Hippocampal-Lateral}
              Septal Circuit",
  author   = "Tingley, David and Buzs{\'a}ki, Gy{\"o}rgy",
  abstract = "The hippocampus constructs a map of the environment. How this
              ``cognitive map'' is utilized by other brain regions to guide
              behavior remains unexplored. To examine how neuronal firing
              patterns in the hippocampus are transmitted and transformed, we
              recorded neurons in its principal subcortical target, the lateral
              septum (LS). We observed that LS neurons carry reliable spatial
              information in the phase of action potentials, relative to
              hippocampal theta oscillations, while the firing rates of LS
              neurons remained uninformative. Furthermore, this spatial phase
              code had an anatomical microstructure within the LS and was bound
              to the hippocampal spatial code by synchronous gamma frequency
              cell assemblies. Using a data-driven model, we show that
              rate-independent spatial tuning arises through the dynamic
              weighting of CA1 and CA3 cell assemblies. Our findings
              demonstrate that transformation of the hippocampal spatial map
              depends on higher-order theta-dependent neuronal sequences. VIDEO
              ABSTRACT.",
  journal  = "Neuron",
  volume   =  98,
  number   =  6,
  pages    = "1229--1242.e5",
  month    =  jun,
  year     =  2018,
  keywords = "cell assemblies; dynamic weighting; hippocampus; information
              transfer; lateral septum; phase coding; rate coding; theta
              sequences; transformation;Spatial Navigation",
  language = "en"
}

@ARTICLE{Akam2015-tt,
  title    = "Simple Plans or Sophisticated Habits? State, Transition and
              Learning Interactions in the {Two-Step} Task",
  author   = "Akam, Thomas and Costa, Rui and Dayan, Peter",
  abstract = "The recently developed 'two-step' behavioural task promises to
              differentiate model-based from model-free reinforcement learning,
              while generating neurophysiologically-friendly decision datasets
              with parametric variation of decision variables. These desirable
              features have prompted its widespread adoption. Here, we analyse
              the interactions between a range of different strategies and the
              structure of transitions and outcomes in order to examine
              constraints on what can be learned from behavioural performance.
              The task involves a trade-off between the need for stochasticity,
              to allow strategies to be discriminated, and a need for
              determinism, so that it is worth subjects' investment of effort
              to exploit the contingencies optimally. We show through
              simulation that under certain conditions model-free strategies
              can masquerade as being model-based. We first show that seemingly
              innocuous modifications to the task structure can induce
              correlations between action values at the start of the trial and
              the subsequent trial events in such a way that analysis based on
              comparing successive trials can lead to erroneous conclusions. We
              confirm the power of a suggested correction to the analysis that
              can alleviate this problem. We then consider model-free
              reinforcement learning strategies that exploit correlations
              between where rewards are obtained and which actions have high
              expected value. These generate behaviour that appears model-based
              under these, and also more sophisticated, analyses. Exploiting
              the full potential of the two-step task as a tool for behavioural
              neuroscience requires an understanding of these issues.",
  journal  = "PLoS Comput. Biol.",
  volume   =  11,
  number   =  12,
  pages    = "e1004648",
  month    =  dec,
  year     =  2015,
  language = "en"
}


@ARTICLE{Markowitz2018-fk,
  title    = "The Striatum Organizes {3D} Behavior via {Moment-to-Moment}
              Action Selection",
  author   = "Markowitz, Jeffrey E and Gillis, Winthrop F and Beron, Celia C
              and Neufeld, Shay Q and Robertson, Keiramarie and Bhagat, Neha D
              and Peterson, Ralph E and Peterson, Emalee and Hyun, Minsuk and
              Linderman, Scott W and Sabatini, Bernardo L and Datta, Sandeep
              Robert",
  abstract = "Many naturalistic behaviors are built from modular components
              that are expressed sequentially. Although striatal circuits have
              been implicated in action selection and implementation, the
              neural mechanisms that compose behavior in unrestrained animals
              are not well understood. Here, we record bulk and cellular neural
              activity in the direct and indirect pathways of dorsolateral
              striatum (DLS) as mice spontaneously express action sequences.
              These experiments reveal that DLS neurons systematically encode
              information about the identity and ordering of sub-second 3D
              behavioral motifs; this encoding is facilitated by fast-timescale
              decorrelations between the direct and indirect pathways.
              Furthermore, lesioning the DLS prevents appropriate sequence
              assembly during exploratory or odor-evoked behaviors. By
              characterizing naturalistic behavior at neural timescales, these
              experiments identify a code for elemental 3D pose dynamics built
              from complementary pathway dynamics, support a role for DLS in
              constructing meaningful behavioral sequences, and suggest models
              for how actions are sculpted over time.",
  journal  = "Cell",
  volume   =  174,
  number   =  1,
  pages    = "44--58.e17",
  month    =  jun,
  year     =  2018,
  keywords = "basal ganglia; behavior; coding; direct pathway; ethology;
              indirect pathway; machine learning; mouse; photometry; striatum",
  language = "en"
}

@ARTICLE{Wiltschko2015-wd,
  title     = "Mapping {Sub-Second} Structure in Mouse Behavior",
  author    = "Wiltschko, Alexander B and Johnson, Matthew J and Iurilli,
               Giuliano and Peterson, Ralph E and Katon, Jesse M and
               Pashkovski, Stan L and Abraira, Victoria E and Adams, Ryan P and
               Datta, Sandeep Robert",
  abstract  = "Complex animal behaviors are likely built from simpler modules,
               but their systematic identification in mammals remains a
               significant challenge. Here we use depth imaging to show that 3D
               mouse pose dynamics are structured at the sub-second timescale.
               Computational modeling of these fast dynamics effectively
               describes mouse behavior as a series of reused and stereotyped
               modules with defined transition probabilities. We demonstrate
               this combined 3D imaging and machine learning method can be used
               to unmask potential strategies employed by the brain to adapt to
               the environment, to capture both predicted and previously hidden
               phenotypes caused by genetic or neural manipulations, and to
               systematically expose the global structure of behavior within an
               experiment. This work reveals that mouse body language is built
               from identifiable components and is organized in a predictable
               fashion; deciphering this language establishes an objective
               framework for characterizing the influence of environmental
               cues, genes and neural activity on behavior.",
  journal   = "Neuron",
  publisher = "Elsevier",
  volume    =  88,
  number    =  6,
  pages     = "1121--1135",
  month     =  dec,
  year      =  2015,
  language  = "en"
}

@ARTICLE{Friston2018-lp,
  title    = "Does predictive coding have a future?",
  author   = "Friston, Karl",
  journal  = "Nat. Neurosci.",
  month    =  jul,
  year     =  2018,
  keywords = "Threat response",
  language = "en"
}

@ARTICLE{Campbell2018-tx,
  title    = "Principles governing the integration of landmark and self-motion
              cues in entorhinal cortical codes for navigation",
  author   = "Campbell, Malcolm G and Ocko, Samuel A and Mallory, Caitlin S and
              Low, Isabel I C and Ganguli, Surya and Giocomo, Lisa M",
  abstract = "To guide navigation, the nervous system integrates multisensory
              self-motion and landmark information. We dissected how these
              inputs generate spatial representations by recording entorhinal
              grid, border and speed cells in mice navigating virtual
              environments. Manipulating the gain between the animal's
              locomotion and the visual scene revealed that border cells
              responded to landmark cues while grid and speed cells responded
              to combinations of locomotion, optic flow and landmark cues in a
              context-dependent manner, with optic flow becoming more
              influential when it was faster than expected. A network model
              explained these results by revealing a phase transition between
              two regimes in which grid cells remain coherent with or break
              away from the landmark reference frame. Moreover, during
              path-integration-based navigation, mice estimated their position
              following principles predicted by our recordings. Together, these
              results provide a theoretical framework for understanding how
              landmark and self-motion cues combine during navigation to
              generate spatial representations and guide behavior.",
  journal  = "Nat. Neurosci.",
  month    =  jul,
  year     =  2018,
  keywords = "Spatial Navigation",
  language = "en"
}

@ARTICLE{Branco2009-gn,
  title     = "The probability of neurotransmitter release: variability and
               feedback control at single synapses",
  author    = "Branco, Tiago and Staras, Kevin",
  abstract  = "Information transfer at chemical synapses occurs when vesicles
               fuse with the plasma membrane and release neurotransmitter. This
               process is stochastic and its likelihood of occurrence is a
               crucial factor in the regulation of signal propagation in
               neuronal networks. The reliability of neurotransmitter release
               can be highly variable: experimental data from
               electrophysiological, molecular and imaging studies have
               demonstrated that synaptic terminals can individually set their
               neurotransmitter release probability dynamically through local
               feedback regulation. This local tuning of transmission has
               important implications for current models of single-neuron
               computation.",
  journal   = "Nat. Rev. Neurosci.",
  publisher = "nature.com",
  volume    =  10,
  number    =  5,
  pages     = "373--383",
  month     =  may,
  year      =  2009,
  language  = "en"
}

@ARTICLE{Wood2018-fu,
  title     = "The honeycomb maze provides a novel test to study
               hippocampal-dependent spatial navigation",
  author    = "Wood, Ruth A and Bauza, Marius and Krupic, Julija and Burton,
               Stephen and Delekate, Andrea and Chan, Dennis and O'Keefe, John",
  abstract  = "Here we describe the honeycomb maze, a behavioural paradigm for
               the study of spatial navigation in rats. The maze consists of 37
               platforms that can be raised or lowered independently. Place
               navigation requires an animal to go to a goal platform from any
               of several start platforms via a series of sequential choices.
               For each, the animal is confined to a raised platform and
               allowed to choose between two of the six adjacent platforms, the
               correct one being the platform with the smallest angle to the
               goal-heading direction. Rats learn rapidly and their choices are
               influenced by three factors: the angle between the two choice
               platforms, the distance from the goal, and the angle between the
               correct platform and the direction of the goal. Rats with
               hippocampal damage are impaired in learning and their
               performance is affected by all three factors. The honeycomb maze
               represents a marked improvement over current spatial navigation
               tests, such as the Morris water maze, because it controls the
               choices of the animal at each point in the maze, provides the
               ability to assess knowledge of the goal direction from any
               location, enables the identification of factors influencing task
               performance and provides the possibility for concomitant
               single-cell recording.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  554,
  number    =  7690,
  pages     = "102--105",
  month     =  feb,
  year      =  2018,
  keywords  = "Spatial Navigation",
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Tolman1939-vg,
  title     = "Prediction of vicarious trial and error by means of the
               schematic sowbug",
  author    = "Tolman, Edward Chace",
  abstract  = "An experiment is described in white-black and white-gray
               discrimination by rats, in which considerable``
               looking-back-and-forth'' or vicarious trial -and- error
               (Muenzinger's terminology), hereafter called VTE behavior,
               occurred. 3 groups of 10 rats each were used …",
  journal   = "Psychol. Rev.",
  publisher = "American Psychological Association",
  volume    =  46,
  number    =  4,
  pages     = "318",
  year      =  1939,
  keywords  = "Decision Making"
}

@ARTICLE{Schmidt2013-bd,
  title     = "Conflict between place and response navigation strategies:
               effects on vicarious trial and error ({VTE}) behaviors",
  author    = "Schmidt, Brandy and Papale, Andrew and Redish, A David and
               Markus, Etan J",
  abstract  = "Navigation can be accomplished through multiple decision-making
               strategies, using different information-processing computations.
               A well-studied dichotomy in these decision-making strategies
               compares hippocampal-dependent ``place'' and dorsal-lateral
               striatal-dependent ``response'' strategies. A place strategy
               depends on the ability to flexibly respond to environmental
               cues, while a response strategy depends on the ability to
               quickly recognize and react to situations with well-learned
               action-outcome relationships. When rats reach decision points,
               they sometimes pause and orient toward the potential routes of
               travel, a process termed vicarious trial and error (VTE). VTE
               co-occurs with neurophysiological information processing,
               including sweeps of representation ahead of the animal in the
               hippocampus and transient representations of reward in the
               ventral striatum and orbitofrontal cortex. To examine the
               relationship between VTE and the place/response strategy
               dichotomy, we analyzed data in which rats were cued to switch
               between place and response strategies on a plus maze. The
               configuration of the maze allowed for place and response
               strategies to work competitively or cooperatively. Animals
               showed increased VTE on trials entailing competition between
               navigational systems, linking VTE with deliberative
               decision-making. Even in a well-learned task, VTE was
               preferentially exhibited when a spatial selection was required,
               further linking VTE behavior with decision-making associated
               with hippocampal processing.",
  journal   = "Learn. Mem.",
  publisher = "learnmem.cshlp.org",
  volume    =  20,
  number    =  3,
  pages     = "130--138",
  month     =  feb,
  year      =  2013,
  keywords  = "Decision Making",
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Goss1956-dh,
  title     = "Vicarious trial and error and related behavior",
  author    = "Goss, A E and Wischner, G J",
  abstract  = "Empirical material relating to`` vicarious trial -and- error
               ''(VTE) is summarized and evaluated critically in terms of
               criteria for VTE, of antecedents to and response correlates of
               VTE, and of VTE and learning efficiency. It is proposed that the
               criterion for scoring VTE behavior should …",
  journal   = "Psychol. Bull.",
  publisher = "psycnet.apa.org",
  volume    =  53,
  number    =  1,
  pages     = "35--54",
  month     =  jan,
  year      =  1956,
  keywords  = "LEARNING;Decision Making",
  language  = "en"
}

@ARTICLE{Redish2016-id,
  title     = "Vicarious trial and error",
  author    = "Redish, A David",
  abstract  = "When rats come to a decision point, they sometimes pause and
               look back and forth as if deliberating over the choice; at other
               times, they proceed as if they have already made their decision.
               In the 1930s, this pause-and-look behaviour was termed
               'vicarious trial and error' (VTE), with the implication that the
               rat was 'thinking about the future'. The discovery in 2007 that
               the firing of hippocampal place cells gives rise to alternating
               representations of each of the potential path options in a
               serial manner during VTE suggested a possible neural mechanism
               that could underlie the representations of future outcomes.
               More-recent experiments examining VTE in rats suggest that there
               are direct parallels to human processes of deliberative decision
               making, working memory and mental time travel.",
  journal   = "Nat. Rev. Neurosci.",
  publisher = "nature.com",
  volume    =  17,
  number    =  3,
  pages     = "147--159",
  month     =  mar,
  year      =  2016,
  keywords  = "Decision Making",
  language  = "en"
}

@ARTICLE{Amsel1993-qk,
  title     = "Hippocampal function in the rat: cognitive mapping or vicarious
               trial and error?",
  author    = "Amsel, A",
  abstract  = "The most prominent hypothesis of hippocampal function likens the
               hippocampus to a ``cognitive map,'' a term used by a famous
               learning theorist, E. C. Tolman, to explain maze learning. The
               usual application of this concept of cognitive map, as it
               applies to the hippocampus, is to what is called spatial
               learning, mainly in the radial-arm maze of Olton and the Morris
               water maze. In a recent Hippocampus Forum, evidence for the
               cognitive map hypothesis was reviewed in a lead article by
               Nadel, followed by a series of commentaries by leading
               investigators of hippocampal function. This speculative
               commentary offers an alternative not represented in the
               forum--that the function of the hippocampus in spatial learning
               is not as a cognitive map, but that it subserves another
               function proposed by Tolman in his work on simple discrimination
               learning, vicarious trial and error, based on incipient,
               conflicting dispositions to approach and avoid.",
  journal   = "Hippocampus",
  publisher = "Wiley Online Library",
  volume    =  3,
  number    =  3,
  pages     = "251--256",
  month     =  jul,
  year      =  1993,
  keywords  = "Decision Making",
  language  = "en"
}

@ARTICLE{Hu1995-ip,
  title     = "A simple test of the vicarious trial-and-error hypothesis of
               hippocampal function",
  author    = "Hu, D and Amsel, A",
  abstract  = "Vicarious trial-and-error (VTE) is a term that Muenzinger and
               Tolman used to describe the rat's conflict-like behavior before
               responding to choice. Recently, VTE was proposed as a mechanism
               alternative to the concept of ``cognitive map'' in accounts of
               hippocampal function. That is, many phenomena of impaired
               learning and memory related to hippocampal interventions may be
               explained by behavioral first principles: reduced conflicting,
               incipient, pre-choice tendencies to approach and avoid. The
               nonspatial black-white discrimination learning and VTE behavior
               of the rat were investigated. Hippocampal-lesioned and
               sham-lesioned animals were trained for 25 days (20 trials per
               day) starting at 60 days of age. Each movement of the head from
               one discriminative stimulus to the other was counted as a VTE
               instance. Lesioned rats had fewer VTEs than sham controls, and
               the former learned much more slowly or never learned. After
               learning, VTE frequency declined. Male and female rats showed no
               significant differences in VTE behavior or discrimination
               learning.",
  journal   = "Proc. Natl. Acad. Sci. U. S. A.",
  publisher = "National Acad Sciences",
  volume    =  92,
  number    =  12,
  pages     = "5506--5509",
  month     =  jun,
  year      =  1995,
  keywords  = "Decision Making",
  language  = "en"
}

@ARTICLE{Muenzinger1938-ex,
  title     = "Vicarious Trial and Error at a Point of Choice: I. A General
               Survey of its Relation to Learning Efficiency",
  author    = "Muenzinger, Karl F",
  abstract  = "* Received in the Editorial Office on December 7, 1937.",
  journal   = "The Pedagogical Seminary and Journal of Genetic Psychology",
  publisher = "Routledge",
  volume    =  53,
  number    =  1,
  pages     = "75--86",
  month     =  sep,
  year      =  1938,
  keywords  = "Decision Making"
}

@ARTICLE{De_Franceschi2016-vo,
  title     = "Vision Guides Selection of Freeze or Flight Defense Strategies
               in Mice",
  author    = "De Franceschi, Gioia and Vivattanasarn, Tipok and Saleem, Aman B
               and Solomon, Samuel G",
  abstract  = "In prey species such as mice, avoidance of predators is key to
               survival and drives instinctual behaviors like freeze or flight
               [1, 2]. Sensory signals guide the selection of appropriate
               behavior [3], and for aerial predators only vision provides
               useful information. Surprisingly, there is no evidence that
               vision can guide the selection of escape strategies. Fleeing
               behavior can be readily triggered by a rapidly looming overhead
               stimulus [4]. Freezing behavior, however, has previously been
               induced by real predators or their odors [5]. Here, we discover
               that a small moving disk, simulating the sweep of a predator
               cruising overhead, is sufficient to induce freezing response in
               mice. Looming and sweeping therefore provide visual triggers for
               opposing flight and freeze behaviors and provide evidence that
               mice innately make behavioral choices based on vision alone.
               VIDEO ABSTRACT.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  26,
  number    =  16,
  pages     = "2150--2154",
  month     =  aug,
  year      =  2016,
  keywords  = "innate behavior; mouse; predator and prey; visual pathways",
  language  = "en"
}

@ARTICLE{Vale2017-cv,
  title     = "Rapid Spatial Learning Controls Instinctive Defensive Behavior
               in Mice",
  author    = "Vale, Ruben and Evans, Dominic A and Branco, Tiago",
  abstract  = "Instinctive defensive behaviors are essential for animal
               survival. Across the animal kingdom, there are sensory stimuli
               that innately represent threat and trigger stereotyped behaviors
               such as escape or freezing [1-4]. While innate behaviors are
               considered to be hard-wired stimulus-responses [5], they act
               within dynamic environments, and factors such as the properties
               of the threat [6-9] and its perceived intensity [1, 10, 11],
               access to food sources [12-14], and expectations from past
               experience [15, 16] have been shown to influence defensive
               behaviors, suggesting that their expression can be modulated.
               However, despite recent work [2, 4, 17-21], little is known
               about how flexible mouse innate defensive behaviors are and how
               quickly they can be modified by experience. To address this, we
               have investigated the dependence of escape behavior on learned
               knowledge about the spatial environment and how the behavior is
               updated when the environment changes acutely. Using behavioral
               assays with innately threatening visual and auditory stimuli, we
               show that the primary goal of escape in mice is to reach a
               previously memorized shelter location. Memory of the escape
               target can be formed in a single shelter visit lasting less than
               20 s, and changes in the spatial environment lead to a rapid
               update of the defensive action, including changing the defensive
               strategy from escape to freezing. Our results show that although
               there are innate links between specific sensory features and
               defensive behavior, instinctive defensive actions are
               surprisingly flexible and can be rapidly updated by experience
               to adapt to changing spatial environments.",
  journal   = "Curr. Biol.",
  publisher = "Elsevier",
  volume    =  27,
  number    =  9,
  pages     = "1342--1349",
  month     =  may,
  year      =  2017,
  keywords  = "defensive behavior; escape; freezing; innate behavior; mouse;
               shelter; spatial learning; spatial memory",
  language  = "en"
}

@ARTICLE{Evans2018-rs,
  title     = "A synaptic threshold mechanism for computing escape decisions",
  author    = "Evans, Dominic A and Stempel, A Vanessa and Vale, Ruben and
               Ruehle, Sabine and Lefler, Yaara and Branco, Tiago",
  abstract  = "Escaping from imminent danger is an instinctive behaviour that
               is fundamental for survival, and requires the classification of
               sensory stimuli as harmless or threatening. The absence of
               threat enables animals to forage for essential resources, but as
               the level of threat and potential for harm increases, they have
               to decide whether or not to seek safety 1 . Despite previous
               work on instinctive defensive behaviours in rodents2-11, little
               is known about how the brain computes the threat level for
               initiating escape. Here we show that the probability and vigour
               of escape in mice scale with the saliency of innate threats, and
               are well described by a model that computes the distance between
               the threat level and an escape threshold. Calcium imaging and
               optogenetics in the midbrain of freely behaving mice show that
               the activity of excitatory neurons in the deep layers of the
               medial superior colliculus (mSC) represents the saliency of the
               threat stimulus and is predictive of escape, whereas
               glutamatergic neurons of the dorsal periaqueductal grey (dPAG)
               encode exclusively the choice to escape and control escape
               vigour. We demonstrate a feed-forward monosynaptic excitatory
               connection from mSC to dPAG neurons, which is weak and
               unreliable-yet required for escape behaviour-and provides a
               synaptic threshold for dPAG activation and the initiation of
               escape. This threshold can be overcome by high mSC network
               activity because of short-term synaptic facilitation and
               recurrent excitation within the mSC, which amplifies and
               sustains synaptic drive to the dPAG. Therefore, dPAG
               glutamatergic neurons compute escape decisions and escape vigour
               using a synaptic mechanism to threshold threat information
               received from the mSC, and provide a biophysical model of how
               the brain performs a critical behavioural computation.",
  journal   = "Nature",
  publisher = "nature.com",
  volume    =  558,
  number    =  7711,
  pages     = "590--594",
  month     =  jun,
  year      =  2018,
  language  = "en"
}

@ARTICLE{Branco2010-cb,
  title     = "Dendritic discrimination of temporal input sequences in cortical
               neurons",
  author    = "Branco, Tiago and Clark, Beverley A and H{\"a}usser, Michael",
  abstract  = "The detection and discrimination of temporal sequences is
               fundamental to brain function and underlies perception,
               cognition, and motor output. By applying patterned, two-photon
               glutamate uncaging, we found that single dendrites of cortical
               pyramidal neurons exhibit sensitivity to the sequence of
               synaptic activation. This sensitivity is encoded by both local
               dendritic calcium signals and somatic depolarization, leading to
               sequence-selective spike output. The mechanism involves
               dendritic impedance gradients and nonlinear synaptic
               N-methyl-D-aspartate receptor activation and is generalizable to
               dendrites in different neuronal types. This enables
               discrimination of patterns delivered to a single dendrite, as
               well as patterns distributed randomly across the dendritic tree.
               Pyramidal cell dendrites can thus act as processing compartments
               for the detection of synaptic sequences, thereby implementing a
               fundamental cortical computation.",
  journal   = "Science",
  publisher = "science.sciencemag.org",
  volume    =  329,
  number    =  5999,
  pages     = "1671--1675",
  month     =  sep,
  year      =  2010,
  language  = "en"
}

@UNPUBLISHED{Brown2018-bm,
  title    = "Ethology as a physical science",
  author   = "Brown, Andre E X and de Bivort, Benjamin",
  abstract = "Behaviour is the ultimate output of an animal9s nervous system
              and choosing the right action at the right time can be critical
              for survival. The study of the organisation of behaviour in its
              natural context, ethology, has historically been a primarily
              qualitative science. A quantitative theory of behaviour would
              advance research in neuroscience as well as ecology and
              evolution. However, animal posture typically has many degrees of
              freedom and behavioural dynamics vary on timescales ranging from
              milliseconds to years, presenting both technical and conceptual
              challenges. Here we review 1) advances in imaging and computer
              vision that are making it possible to capture increasingly
              complete records of animal motion and 2) new approaches to
              understanding the resulting behavioural data sets. With the right
              analytical approaches, these data are allowing researchers to
              revisit longstanding questions about the structure and
              organisation of animal behaviour and to put unifying principles
              on a quantitative footing. Contributions from both
              experimentalists and theorists are leading to the emergence of a
              physics of behaviour and the prospect of discovering laws and
              developing theories with broad applicability. We believe that
              there now exists an opportunity to develop theories of behaviour
              which can be tested using these data sets leading to a deeper
              understanding of how and why animals behave.",
  journal  = "bioRxiv",
  pages    = "220855",
  month    =  feb,
  year     =  2018,
  keywords = "Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Mathis2018-uu,
  title         = "Markerless tracking of user-defined features with deep
                   learning",
  author        = "Mathis, Alexander and Mamidanna, Pranav and Abe, Taiga and
                   Cury, Kevin M and Murthy, Venkatesh N and Mathis, Mackenzie
                   W and Bethge, Matthias",
  abstract      = "Quantifying behavior is crucial for many applications in
                   neuroscience. Videography provides easy methods for the
                   observation and recording of animal behavior in diverse
                   settings, yet extracting particular aspects of a behavior
                   for further analysis can be highly time consuming. In motor
                   control studies, humans or other animals are often marked
                   with reflective markers to assist with computer-based
                   tracking, yet markers are intrusive (especially for smaller
                   animals), and the number and location of the markers must be
                   determined a priori. Here, we present a highly efficient
                   method for markerless tracking based on transfer learning
                   with deep neural networks that achieves excellent results
                   with minimal training data. We demonstrate the versatility
                   of this framework by tracking various body parts in a broad
                   collection of experimental settings: mice odor
                   trail-tracking, egg-laying behavior in drosophila, and mouse
                   hand articulation in a skilled forelimb task. For example,
                   during the skilled reaching behavior, individual joints can
                   be automatically tracked (and a confidence score is
                   reported). Remarkably, even when a small number of frames
                   are labeled ($\approx 200$), the algorithm achieves
                   excellent tracking performance on test frames that is
                   comparable to human accuracy.",
  month         =  apr,
  year          =  2018,
  keywords      = "Analysis/Modelling [Behaviour]",
  archivePrefix = "arXiv",
  primaryClass  = "cs.CV",
  eprint        = "1804.03142"
}

@ARTICLE{Ainge2007-ue,
  title    = "Hippocampal {CA1} place cells encode intended destination on a
              maze with multiple choice points",
  author   = "Ainge, James A and Tamosiunaite, Minija and Woergoetter,
              Florentin and Dudchenko, Paul A",
  abstract = "The hippocampus encodes both spatial and nonspatial aspects of a
              rat's ongoing behavior at the single-cell level. In this study,
              we examined the encoding of intended destination by hippocampal
              (CA1) place cells during performance of a serial reversal task on
              a double Y-maze. On the maze, rats had to make two choices to
              access one of four possible goal locations, two of which
              contained reward. Reward locations were kept constant within
              blocks of 10 trials but changed between blocks, and the session
              of each day comprised three or more trial blocks. A
              disproportionate number of place fields were observed in the
              start box and beginning stem of the maze, relative to other
              locations on the maze. Forty-six percent of these place fields
              had different firing rates on journeys to different goal boxes.
              Another group of cells had place fields before the second choice
              point, and, of these, 44\% differentiated between journeys to
              specific goal boxes. In a second experiment, we observed that
              rats with hippocampal damage made significantly more errors than
              control rats on the Y-maze when reward locations were reversed.
              Together, these results suggest that, at the start of the maze,
              the hippocampus encodes both current location and the intended
              destination of the rat, and this encoding is necessary for the
              flexible response to changes in reinforcement contingencies.",
  journal  = "J. Neurosci.",
  volume   =  27,
  number   =  36,
  pages    = "9769--9779",
  month    =  sep,
  year     =  2007,
  keywords = "Spatial Navigation;Decision Making",
  language = "en"
}

@ARTICLE{Grieves2017-ay,
  title     = "The representation of space in the brain",
  author    = "Grieves, Roddy M and Jeffery, Kate J",
  journal   = "Behav. Processes",
  publisher = "Elsevier",
  volume    =  135,
  pages     = "113--131",
  year      =  2017,
  keywords  = "Spatial Navigation"
}

@ARTICLE{Gauthier2018-db,
  title    = "A Dedicated Population for Reward Coding in the Hippocampus",
  author   = "Gauthier, Jeffrey L and Tank, David W",
  abstract = "The hippocampus plays a critical role in goal-directed
              navigation. Across different environments, however, hippocampal
              maps are randomized, making it unclear how goal locations could
              be encoded consistently. To address this question, we developed a
              virtual reality task with shifting reward contingencies to
              distinguish place versus reward encoding. In mice performing the
              task, large-scale recordings in CA1 and subiculum revealed a
              small, specialized cell population that was only active near
              reward yet whose activity could not be explained by sensory cues
              or stereotyped reward anticipation behavior. Across different
              virtual environments, most cells remapped randomly, but reward
              encoding consistently arose from a single pool of cells,
              suggesting that they formed a dedicated channel for reward. These
              observations represent a significant departure from the current
              understanding of CA1 as a relatively homogeneous ensemble without
              fixed coding properties and provide a new candidate for the
              cellular basis of goal memory in the hippocampus.",
  journal  = "Neuron",
  volume   =  99,
  number   =  1,
  pages    = "179--193.e7",
  month    =  jul,
  year     =  2018,
  keywords = "CA1; hippocampus; navigation; place cells; place fields; reward;
              subiculum; virtual reality;Spatial Navigation",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Horndli2018-ja,
  title     = "Machine Learning Reveals Modules of Economic Behavior from
               Foraging Mice",
  author    = "Horndli, C N S and Wong, E and Ferris, E and Rhodes, A N and
               {others}",
  abstract  = "The mechanisms shaping most ethological behavior patterns are
               elusive because we do not understand how complex patterns are
               constructed. Here, we develop a behavioral paradigm and data
               analysis methods to dissect foraging patterns in mice. We
               uncover discrete behavioral modules linked to round trip
               excursions from the home. Using machine learning, 59 modules are
               revealed across different genetic backgrounds and ages.
               Different modules develop at different ages and are linked to
               different aspects of economic behavior, including …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2018,
  keywords  = "Analysis/Modelling [Behaviour]"
}

@ARTICLE{Luo2018-cf,
  title    = "A dopaminergic switch for fear to safety transitions",
  author   = "Luo, Ray and Uematsu, Akira and Weitemier, Adam and Aquili, Luca
              and Koivumaa, Jenny and McHugh, Thomas J and Johansen, Joshua P",
  abstract = "Overcoming aversive emotional memories requires neural systems
              that detect when fear responses are no longer appropriate so that
              they can be extinguished. The midbrain ventral tegmental area
              (VTA) dopamine system has been implicated in reward and more
              broadly in signaling when a better-than-expected outcome has
              occurred. This suggests that it may be important in guiding fear
              to safety transitions. We report that when an expected aversive
              outcome does not occur, activity in midbrain dopamine neurons is
              necessary to extinguish behavioral fear responses and engage
              molecular signaling events in extinction learning circuits.
              Furthermore, a specific dopamine projection to the nucleus
              accumbens medial shell is partially responsible for this effect.
              In contrast, a separate dopamine projection to the medial
              prefrontal cortex opposes extinction learning. This demonstrates
              a novel function for the canonical VTA-dopamine reward system and
              reveals opposing behavioral roles for different dopamine neuron
              projections in fear extinction learning.",
  journal  = "Nat. Commun.",
  volume   =  9,
  number   =  1,
  pages    = "2483",
  month    =  jun,
  year     =  2018,
  keywords = "Threat response",
  language = "en"
}

@UNPUBLISHED{Torok2018-fl,
  title    = "A novel virtual plus-maze for studying electrophysiological
              correlates of spatial reorientation",
  author   = "Torok, Agoston and Kobor, Andrea and Honbolygo, Ferenc and Baker,
              Travis",
  abstract = "Quick reorientation is an essential part of successful
              navigation. Despite growing attention to this ability, little is
              known about how reorientation happens in humans. To this aim, we
              recorded EEG from 34 participants. Participants were navigating a
              simple virtual reality plus-maze where at the beginning of each
              trial they were randomly teleported to either the North or the
              South alley. Results show that the teleportation event caused a
              quick reorientation effect over occipito-parietal areas as early
              as 100 msec; meaning that despite the known stochastic nature of
              the teleportation, participants built up expectations for their
              place of arrival. This result has important consequences for the
              optimal design of virtual reality locomotion.",
  journal  = "bioRxiv",
  pages    = "369207",
  month    =  jul,
  year     =  2018,
  keywords = "Spatial Navigation",
  language = "en"
}

@ARTICLE{OConnell2018-st,
  title    = "Bridging Neural and Computational Viewpoints on Perceptual
              {Decision-Making}",
  author   = "O'Connell, Redmond G and Shadlen, Michael N and Wong-Lin,
              Kongfatt and Kelly, Simon P",
  abstract = "Sequential sampling models have provided a dominant theoretical
              framework guiding computational and neurophysiological
              investigations of perceptual decision-making. While these models
              share the basic principle that decisions are formed by
              accumulating sensory evidence to a bound, they come in many forms
              that can make similar predictions of choice behaviour despite
              invoking fundamentally different mechanisms. The identification
              of neural signals that reflect some of the core computations
              underpinning decision formation offers new avenues for
              empirically testing and refining key model assumptions. Here, we
              highlight recent efforts to explore these avenues and, in so
              doing, consider the conceptual and methodological challenges that
              arise when seeking to infer decision computations from complex
              neural data.",
  journal  = "Trends Neurosci.",
  month    =  jul,
  year     =  2018,
  keywords = "computational modelling; lateral intraparietal area (LIP);
              perceptual decision-making; sequential sampling;Decision Making",
  language = "en"
}

@ARTICLE{Stringer2048-xi,
  title    = "High-dimensional geometry of population responses in visual
              cortex",
  author   = "Stringer, C and Pachitariu, M and Steinmetz, N and Carandini, M
              and Harris, K",
  abstract = "A neuronal population encodes information most efficiently when
              its activity is uncorrelated and high-dimensional, but cor-
              related lower-dimensional codes provide robustness against noise.
              Here, we analyzed the correlation structure of natural image
              coding, in large visual cortical populations recorded from awake
              mice. Evoked population activity was high dimen- sional, with
              correlations obeying an unexpected power-law: the nth principal
              component variance scaled as 1/n. This was not inherited from the
              1/f spectrum of natural images, because it persisted after
              stimulus whitening. We proved mathemat- ically that the variance
              spectrum must decay at least this fast if a population code is
              smooth, i.e. if small changes in input cannot dominate population
              activity. The theory also predicted larger power-law exponents
              for lower-dimensional stimu- lus ensembles, which we validated
              experimentally. These results suggest that coding smoothness
              represents a fundamental constraint governing correlations in
              neural population codes.",
  journal  = "bioRxiv",
  pages    = "374090",
  month    =  jul,
  year     =  2048,
  keywords = "Authors;Authors/Harris/Carandini",
  language = "en"
}

@ARTICLE{Sweis2018-sg,
  title     = "Sensitivity to ``sunk costs'' in mice, rats, and humans",
  author    = "Sweis, Brian M and Abram, Samantha V and Schmidt, Brandy J and
               Seeland, Kelsey D and MacDonald, Angus W and Thomas, Mark J and
               David Redish, A",
  abstract  = "Sunk costs are irrecoverable investments that should not
               influence decisions, because decisions should be made on the
               basis of expected future consequences. Both human and nonhuman
               animals can show sensitivity to sunk costs, but reports from
               across species are inconsistent. In a temporal context, a
               sensitivity to sunk costs arises when an individual resists
               ending an activity, even if it seems unproductive, because of
               the time already invested. In two parallel foraging tasks that
               we designed, we found that mice, rats, and humans show similar
               sensitivities to sunk costs in their decision-making.
               Unexpectedly, sensitivity to time invested accrued only after an
               initial decision had been made. These findings suggest that
               sensitivity to temporal sunk costs lies in a vulnerability
               distinct from deliberation processes and that this distinction
               is present across species.",
  journal   = "Science",
  publisher = "American Association for the Advancement of Science",
  volume    =  361,
  number    =  6398,
  pages     = "178--181",
  month     =  jul,
  year      =  2018,
  keywords  = "Decision Making",
  language  = "en"
}

@ARTICLE{Djurdjevic2018-yn,
  title    = "Accuracy of Rats in Discriminating Visual Objects Is Explained by
              the Complexity of Their Perceptual Strategy",
  author   = "Djurdjevic, Vladimir and Ansuini, Alessio and Bertolini, Daniele
              and Macke, Jakob H and Zoccolan, Davide",
  abstract = "Despite their growing popularity as models of visual functions,
              it remains unclear whether rodents are capable of deploying
              advanced shape-processing strategies when engaged in visual
              object recognition. In rats, for instance, pattern vision has
              been reported to range from mere detection of overall object
              luminance to view-invariant processing of discriminative shape
              features. Here we sought to clarify how refined object vision is
              in rodents, and how variable the complexity of their visual
              processing strategy is across individuals. To this aim, we
              measured how well rats could discriminate a reference object from
              11 distractors, which spanned a spectrum of image-level
              similarity to the reference. We also presented the animals with
              random variations of the reference, and processed their responses
              to these stimuli to derive subject-specific models of rat
              perceptual choices. Our models successfully captured the highly
              variable discrimination performance observed across subjects and
              object conditions. In particular, they revealed that the animals
              that succeeded with the most challenging distractors were those
              that integrated the wider variety of discriminative features into
              their perceptual strategies. Critically, these strategies were
              largely preserved when the rats were required to discriminate
              outlined and scaled versions of the stimuli, thus showing that
              rat object vision can be characterized as a
              transformation-tolerant, feature-based filtering process.
              Overall, these findings indicate that rats are capable of
              advanced processing of shape information, and point to the
              rodents as powerful models for investigating the neuronal
              underpinnings of visual object recognition and other high-level
              visual functions.",
  journal  = "Curr. Biol.",
  volume   =  28,
  number   =  7,
  pages    = "1005--1015.e5",
  month    =  apr,
  year     =  2018,
  keywords = "classification; filtering; image; object; perception; processing;
              recognition; rodent; shape; vision",
  language = "en"
}

@ARTICLE{Berman2016-it,
  title    = "Predictability and hierarchy in Drosophila behavior",
  author   = "Berman, Gordon J and Bialek, William and Shaevitz, Joshua W",
  abstract = "Even the simplest of animals exhibit behavioral sequences with
              complex temporal dynamics. Prominent among the proposed
              organizing principles for these dynamics has been the idea of a
              hierarchy, wherein the movements an animal makes can be
              understood as a set of nested subclusters. Although this type of
              organization holds potential advantages in terms of motion
              control and neural circuitry, measurements demonstrating this for
              an animal's entire behavioral repertoire have been limited in
              scope and temporal complexity. Here, we use a recently developed
              unsupervised technique to discover and track the occurrence of
              all stereotyped behaviors performed by fruit flies moving in a
              shallow arena. Calculating the optimally predictive
              representation of the fly's future behaviors, we show that fly
              behavior exhibits multiple time scales and is organized into a
              hierarchical structure that is indicative of its underlying
              behavioral programs and its changing internal states.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  113,
  number   =  42,
  pages    = "11943--11948",
  month    =  oct,
  year     =  2016,
  keywords = "Drosophila; behavior; hierarchy; information
              bottleneck;Authors/Berman",
  language = "en"
}

@ARTICLE{Berman2014-pw,
  title    = "Mapping the stereotyped behaviour of freely moving fruit flies",
  author   = "Berman, Gordon J and Choi, Daniel M and Bialek, William and
              Shaevitz, Joshua W",
  abstract = "A frequent assumption in behavioural science is that most of an
              animal's activities can be described in terms of a small set of
              stereotyped motifs. Here, we introduce a method for mapping an
              animal's actions, relying only upon the underlying structure of
              postural movement data to organize and classify behaviours.
              Applying this method to the ground-based behaviour of the fruit
              fly, Drosophila melanogaster, we find that flies perform
              stereotyped actions roughly 50\% of the time, discovering over
              100 distinguishable, stereotyped behavioural states. These
              include multiple modes of locomotion and grooming. We use the
              resulting measurements as the basis for identifying subtle
              sex-specific behavioural differences and revealing the
              low-dimensional nature of animal motions.",
  journal  = "J. R. Soc. Interface",
  volume   =  11,
  number   =  99,
  month    =  oct,
  year     =  2014,
  keywords = "Drosophila; behaviour; phase reconstruction; stereotypy;
              unsupervised learning;Authors/Berman;Analysis/Modelling
              [Behaviour]",
  language = "en"
}

@ARTICLE{Klibaite2017-kd,
  title    = "An unsupervised method for quantifying the behavior of paired
              animals",
  author   = "Klibaite, Ugne and Berman, Gordon J and Cande, Jessica and Stern,
              David L and Shaevitz, Joshua W",
  abstract = "Behaviors involving the interaction of multiple individuals are
              complex and frequently crucial for an animal's survival. These
              interactions, ranging across sensory modalities, length scales,
              and time scales, are often subtle and difficult to characterize.
              Contextual effects on the frequency of behaviors become even more
              difficult to quantify when physical interaction between animals
              interferes with conventional data analysis, e.g. due to visual
              occlusion. We introduce a method for quantifying behavior in
              fruit fly interaction that combines high-throughput video
              acquisition and tracking of individuals with recent unsupervised
              methods for capturing an animal's entire behavioral repertoire.
              We find behavioral differences between solitary flies and those
              paired with an individual of the opposite sex, identifying
              specific behaviors that are affected by social and spatial
              context. Our pipeline allows for a comprehensive description of
              the interaction between two individuals using unsupervised
              machine learning methods, and will be used to answer questions
              about the depth of complexity and variance in fruit fly
              courtship.",
  journal  = "Phys. Biol.",
  volume   =  14,
  number   =  1,
  pages    = "015006",
  month    =  feb,
  year     =  2017,
  keywords = "Authors/Berman;Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Bassett2018-ni,
  title    = "On the nature and use of models in network neuroscience",
  author   = "Bassett, Danielle S and Zurn, Perry and Gold, Joshua I",
  abstract = "Network theory provides an intuitively appealing framework for
              studying relationships among interconnected brain mechanisms and
              their relevance to behaviour. As the space of its applications
              grows, so does the diversity of meanings of the term network
              model. This diversity can cause confusion, complicate efforts to
              assess model validity and efficacy, and hamper interdisciplinary
              collaboration. In this Review, we examine the field of network
              neuroscience, focusing on organizing principles that can help
              overcome these challenges. First, we describe the fundamental
              goals in constructing network models. Second, we review the most
              common forms of network models, which can be described
              parsimoniously along the following three primary dimensions: from
              data representations to first-principles theory; from biophysical
              realism to functional phenomenology; and from elementary
              descriptions to coarse-grained approximations. Third, we draw on
              biology, philosophy and other disciplines to establish validation
              principles for these models. We close with a discussion of
              opportunities to bridge model types and point to exciting
              frontiers for future pursuits.",
  journal  = "Nat. Rev. Neurosci.",
  month    =  jul,
  year     =  2018,
  language = "en"
}

@ARTICLE{Tovote2016-of,
  title    = "Midbrain circuits for defensive behaviour",
  author   = "Tovote, Philip and Esposito, Maria Soledad and Botta, Paolo and
              Chaudun, Fabrice and Fadok, Jonathan P and Markovic, Milica and
              Wolff, Steffen B E and Ramakrishnan, Charu and Fenno, Lief and
              Deisseroth, Karl and Herry, Cyril and Arber, Silvia and
              L{\"u}thi, Andreas",
  abstract = "Survival in threatening situations depends on the selection and
              rapid execution of an appropriate active or passive defensive
              response, yet the underlying brain circuitry is not understood.
              Here we use circuit-based optogenetic, in vivo and in vitro
              electrophysiological, and neuroanatomical tracing methods to
              define midbrain periaqueductal grey circuits for specific
              defensive behaviours. We identify an inhibitory pathway from the
              central nucleus of the amygdala to the ventrolateral
              periaqueductal grey that produces freezing by disinhibition of
              ventrolateral periaqueductal grey excitatory outputs to pre-motor
              targets in the magnocellular nucleus of the medulla. In addition,
              we provide evidence for anatomical and functional interaction of
              this freezing pathway with long-range and local circuits
              mediating flight. Our data define the neuronal circuitry
              underlying the execution of freezing, an evolutionarily conserved
              defensive behaviour, which is expressed by many species including
              fish, rodents and primates. In humans, dysregulation of this
              'survival circuit' has been implicated in anxiety-related
              disorders.",
  journal  = "Nature",
  volume   =  534,
  number   =  7606,
  pages    = "206--212",
  month    =  jun,
  year     =  2016,
  keywords = "Threat response",
  language = "en"
}

@ARTICLE{Tovote2015-ds,
  title    = "Neuronal circuits for fear and anxiety",
  author   = "Tovote, Philip and Fadok, Jonathan Paul and L{\"u}thi, Andreas",
  abstract = "Decades of research has identified the brain areas that are
              involved in fear, fear extinction, anxiety and related defensive
              behaviours. Newly developed genetic and viral tools, optogenetics
              and advanced in vivo imaging techniques have now made it possible
              to characterize the activity, connectivity and function of
              specific cell types within complex neuronal circuits. Recent
              findings that have been made using these tools and techniques
              have provided mechanistic insights into the exquisite
              organization of the circuitry underlying internal defensive
              states. This Review focuses on studies that have used
              circuit-based approaches to gain a more detailed, and also more
              comprehensive and integrated, view on how the brain governs fear
              and anxiety and how it orchestrates adaptive defensive
              behaviours.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  16,
  number   =  6,
  pages    = "317--331",
  month    =  jun,
  year     =  2015,
  keywords = "Threat response",
  language = "en"
}

@ARTICLE{Alexander2017-ho,
  title    = "Spatially Periodic Activation Patterns of Retrosplenial Cortex
              Encode Route Sub-spaces and Distance Traveled",
  author   = "Alexander, Andrew S and Nitz, Douglas A",
  abstract = "Traversal of a complicated route is often facilitated by
              considering it as a set of related sub-spaces. Such
              compartmentalization processes could occur within retrosplenial
              cortex, a structure whose neurons simultaneously encode position
              within routes and other spatial coordinate systems. Here,
              retrosplenial cortex neurons were recorded as rats traversed a
              track having recurrent structure at multiple scales. Consistent
              with a major role in compartmentalization of complex routes,
              individual retrosplenial cortex (RSC) neurons exhibited periodic
              activation patterns that repeated across route segments having
              the same shape. Concurrently, a larger population of RSC neurons
              exhibited single-cycle periodicity over the full route,
              effectively defining a framework for encoding of sub-route
              positions relative to the whole. The same population
              simultaneously provides a novel metric for distance from each
              route position to all others. Together, the findings implicate
              retrosplenial cortex in the extraction of path sub-spaces, the
              encoding of their spatial relationships to each other, and path
              integration.",
  journal  = "Curr. Biol.",
  volume   =  27,
  number   =  11,
  pages    = "1551--1560.e4",
  month    =  jun,
  year     =  2017,
  keywords = "distance; fragmentation; hippocampus; path integration;
              periodicity; retrosplenial cortex; spatial navigation; spatial
              representation; sub-route; sub-space;Spatial
              Navigation;Authors/Nitz",
  language = "en"
}

@ARTICLE{Behrens_undated-kg,
  title    = "What is a cognitive map? Organising knowledge for flexible
              behaviour",
  author   = "Behrens, Timothy E J and Muller, Timothy H and Whittington, James
              C R and Mark, Shirley and Baram, Alon B and Stachenfeld,
              Kimberley L and Kurth-Nelson, Zeb",
  abstract = "It is proposed that a cognitive map encoding the relationships
              between entities in the world supports flexible behaviour, but
              the majority of the neural evidence for such a system comes from
              studies of spatial navigation. Recent work describing neuronal
              parallels between spatial and non-spatial behaviours has
              rekindled the notion of a systematic organisation of knowledge
              across multiple domains. We review experimental evidence and
              theoretical frameworks that point to principles unifying these
              apparently disparate functions. These principles describe how to
              learn and use abstract, generalisable knowledge and suggest
              map-like representations observed in a spatial context may be an
              instance of general coding mechanisms capable of organising
              knowledge of all kinds. We highlight how artificial agents
              endowed with such principles exhibit flexible behaviour and learn
              map-like representations observed in the brain. Finally, we
              speculate on how these principles may offer insight into the
              extreme generalisations, abstractions and inferences that
              characterise human cognition.",
  journal  = "Biorxiv",
  keywords = "Spatial Navigation"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Patai2018-io,
  title     = "Neural signatures of detours, shortcuts and back-tracking during
               navigation",
  author    = "Patai, E Z and Javadi, A H and Margois, A and Tan, H R and
               Kumaran, D and {others}",
  abstract  = "Central to the concept of the 9cognitive map9 is that it confers
               flexibility in behaviour allowing animals to take efficient
               detours, exploit shortcuts and realise when they need to
               back-track rather than continue on a poorly chosen route.
               Currently the neural underpinnings of such behaviour remains
               unclear. During fMRI we tested human subjects on their ability
               to navigate to a set of goal locations in a virtual desert
               island riven by lava, which occasionally shifted to block
               selected paths (necessitating detours) or receded to …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2018,
  keywords  = "Spatial Navigation"
}

@ARTICLE{Berman2018-xu,
  title    = "Measuring behavior across scales",
  author   = "Berman, Gordon J",
  abstract = "The need for high-throughput, precise, and meaningful methods for
              measuring behavior has been amplified by our recent successes in
              measuring and manipulating neural circuitry. The largest
              challenges associated with moving in this direction, however, are
              not technical but are instead conceptual: what numbers should one
              put on the movements an animal is performing (or not performing)?
              In this review, I will describe how theoretical and data
              analytical ideas are interfacing with recently-developed
              computational and experimental methodologies to answer these
              questions across a variety of contexts, length scales, and time
              scales. I will attempt to highlight commonalities between
              approaches and areas where further advances are necessary to
              place behavior on the same quantitative footing as other
              scientific fields.",
  journal  = "BMC Biol.",
  volume   =  16,
  number   =  1,
  pages    = "23",
  month    =  feb,
  year     =  2018,
  keywords = "Authors/Berman;Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Severi2014-ox,
  title    = "Neural control and modulation of swimming speed in the larval
              zebrafish",
  author   = "Severi, Kristen E and Portugues, Ruben and Marques, Jo{\~a}o C
              and O'Malley, Donald M and Orger, Michael B and Engert, Florian",
  abstract = "Vertebrate locomotion at different speeds is driven by descending
              excitatory connections to central pattern generators in the
              spinal cord. To investigate how these inputs determine locomotor
              kinematics, we used whole-field visual motion to drive zebrafish
              to swim at different speeds. Larvae match the stimulus speed by
              utilizing more locomotor events, or modifying kinematic
              parameters such as the duration and speed of swimming bouts, the
              tail-beat frequency, and the choice of gait. We used laser
              ablations, electrical stimulation, and activity recordings in
              descending neurons of the nucleus of the medial longitudinal
              fasciculus (nMLF) to dissect their contribution to controlling
              forward movement. We found that the activity of single identified
              neurons within the nMLF is correlated with locomotor kinematics,
              and modulates both the duration and oscillation frequency of tail
              movements. By identifying the contribution of individual
              supraspinal circuit elements to locomotion kinematics, we build a
              better understanding of how the brain controls movement.",
  journal  = "Neuron",
  volume   =  83,
  number   =  3,
  pages    = "692--707",
  month    =  aug,
  year     =  2014,
  language = "en"
}

@ARTICLE{Marques2018-kf,
  title    = "Structure of the Zebrafish Locomotor Repertoire Revealed with
              Unsupervised Behavioral Clustering",
  author   = "Marques, Jo{\~a}o C and Lackner, Simone and F{\'e}lix, Rita and
              Orger, Michael B",
  abstract = "An important concept in ethology is that complex behaviors can be
              constructed from a set of basic motor patterns. Identifying the
              set of patterns available to an animal is key to making
              quantitative descriptions of behavior that reflect the underlying
              motor system organization. We addressed these questions in
              zebrafish larvae, which swim in bouts that are naturally
              segmented in time. We developed a robust and general purpose
              clustering method (clusterdv) to ensure accurate identification
              of movement clusters and applied it to a dataset consisting of
              millions of swim bouts, captured at high temporal resolution from
              a comprehensive set of behavioral contexts. We identified a set
              of thirteen basic swimming patterns that are used flexibly in
              various combinations across different behavioral contexts and
              show that this classification can be used to dissect the
              sensorimotor transformations underlying larval social behavior
              and hunting. Furthermore, using the same approach at different
              levels in the behavioral hierarchy, we show that the set of swim
              bouts are themselves constructed from a basic set of tail
              movements and that bouts are executed in sequences specific to
              different behaviors.",
  journal  = "Curr. Biol.",
  volume   =  28,
  number   =  2,
  pages    = "181--195.e5",
  month    =  jan,
  year     =  2018,
  keywords = "behavior; behavioral motifs; cluster analysis; clusterdv;
              locomotion; motor control; sequences; unsupervised machine
              learning; visual behavior; zebrafish",
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Mimica2018-ls,
  title     = "Efficient cortical coding of {3D} posture in freely behaving
               rats",
  author    = "Mimica, B and Dunn, B A and Tombaz, T and Bojja, V S and
               Whitlock, J R",
  abstract  = "In order to meet physical and behavioural demands of their
               environments animals constantly update their body posture, but
               little is known about the neural signals on which this ability
               depends. To better understand the role of cortex in coordinating
               natural pose and movement, we tracked the heads and backs of
               freely foraging rats in 3D while recording simultaneously from
               posterior parietal cortex (PPC) and frontal motor cortex (M2),
               areas critical for spatial movement planning and navigation.
               Single units in both regions were …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2018,
  keywords  = "Spatial Navigation;Analysis/Modelling [Behaviour]"
}

@ARTICLE{Dunn2016-zt,
  title    = "Neural Circuits Underlying Visually Evoked Escapes in Larval
              Zebrafish",
  author   = "Dunn, Timothy W and Gebhardt, Christoph and Naumann, Eva A and
              Riegler, Clemens and Ahrens, Misha B and Engert, Florian and Del
              Bene, Filippo",
  abstract = "Escape behaviors deliver organisms away from imminent
              catastrophe. Here, we characterize behavioral responses of freely
              swimming larval zebrafish to looming visual stimuli simulating
              predators. We report that the visual system alone can recruit
              lateralized, rapid escape motor programs, similar to those
              elicited by mechanosensory modalities. Two-photon calcium imaging
              of retino-recipient midbrain regions isolated the optic tectum as
              an important center processing looming stimuli, with ensemble
              activity encoding the critical image size determining escape
              latency. Furthermore, we describe activity in retinal ganglion
              cell terminals and superficial inhibitory interneurons in the
              tectum during looming and propose a model for how temporal
              dynamics in tectal periventricular neurons might arise from
              computations between these two fundamental constituents. Finally,
              laser ablations of hindbrain circuitry confirmed that visual and
              mechanosensory modalities share the same premotor output network.
              We establish a circuit for the processing of aversive stimuli in
              the context of an innate visual behavior.",
  journal  = "Neuron",
  volume   =  89,
  number   =  3,
  pages    = "613--628",
  month    =  feb,
  year     =  2016,
  language = "en"
}

@ARTICLE{Floyd2000-rj,
  title    = "Orbitomedial prefrontal cortical projections to distinct
              longitudinal columns of the periaqueductal gray in the rat",
  author   = "Floyd, N S and Price, J L and Ferry, A T and Keay, K A and
              Bandler, R",
  abstract = "We utilised retrograde and anterograde tracing procedures to
              study the origin and termination of prefrontal cortical (PFC)
              projections to the periaqueductal gray (PAG) in the rat. A
              previous study, in the primate, had demonstrated that distinct
              subgroups of PFC areas project to specific PAG columns.
              Retrograde tracing experiments revealed that projections to
              dorsolateral (dlPAG) and ventrolateral (vlPAG) periaqueductal
              gray columns arose from medial PFC, specifically prelimbic,
              infralimbic, and anterior cingulate cortices. Injections made in
              the vlPAG also labeled cells in medial, ventral, and dorsolateral
              orbital cortex and dorsal and posterior agranular insular cortex.
              Other orbital and insular regions, including lateral and
              ventrolateral orbital, ventral agranular insular, and dysgranular
              and granular insular cortex did not give rise to appreciable
              projections to the PAG. Anterograde tracing experiments revealed
              that the projections to different PAG columns arose from specific
              PFC areas. Projections from the caudodorsal medial PFC (caudal
              prelimbic and anterior cingulate cortices) terminated
              predominantly in dlPAG, whereas projections from the
              rostroventral medial PFC (rostral prelimbic cortex) innervated
              predominantly the vlPAG. As well, consistent with the retrograde
              data, projections arising from select orbital and agranular
              insular cortical areas terminated selectively in the vlPAG. The
              results indicate: (1) that rat orbital and medial PFC possesses
              an organisation broadly similar to that of the primate; and (2)
              that subdivisions within the rat orbital and medial PFC can be
              recognised on the basis of projections to distinct PAG columns.",
  journal  = "J. Comp. Neurol.",
  volume   =  422,
  number   =  4,
  pages    = "556--578",
  month    =  jul,
  year     =  2000,
  keywords = "Threat response",
  language = "en"
}

@ARTICLE{Arber2018-kx,
  title    = "Connecting neuronal circuits for movement",
  author   = "Arber, Silvia and Costa, Rui M",
  journal  = "Science",
  volume   =  360,
  number   =  6396,
  pages    = "1403--1404",
  month    =  jun,
  year     =  2018,
  language = "en"
}

@ARTICLE{Gris2017-ow,
  title    = "Supervised and Unsupervised Learning Technology in the Study of
              Rodent Behavior",
  author   = "Gris, Katsiaryna V and Coutu, Jean-Philippe and Gris, Denis",
  abstract = "Quantifying behavior is a challenge for scientists studying
              neuroscience, ethology, psychology, pathology, etc. Until now,
              behavior was mostly considered as qualitative descriptions of
              postures or labor intensive counting of bouts of individual
              movements. Many prominent behavioral scientists conducted studies
              describing postures of mice and rats, depicting step by step
              eating, grooming, courting, and other behaviors. Automated video
              assessment technologies permit scientists to quantify daily
              behavioral patterns/routines, social interactions, and postural
              changes in an unbiased manner. Here, we extensively reviewed
              published research on the topic of the structural blocks of
              behavior and proposed a structure of behavior based on the latest
              publications. We discuss the importance of defining a clear
              structure of behavior to allow professionals to write viable
              algorithms. We presented a discussion of technologies that are
              used in automated video assessment of behavior in mice and rats.
              We considered advantages and limitations of supervised and
              unsupervised learning. We presented the latest scientific
              discoveries that were made using automated video assessment. In
              conclusion, we proposed that the automated quantitative approach
              to evaluating animal behavior is the future of understanding the
              effect of brain signaling, pathologies, genetic content, and
              environment on behavior.",
  journal  = "Front. Behav. Neurosci.",
  volume   =  11,
  pages    = "141",
  month    =  jul,
  year     =  2017,
  keywords = "animal behavior; automatic analysis; computer learning;
              supervised; unsupervised;Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Robie2017-fu,
  title    = "Mapping the Neural Substrates of Behavior",
  author   = "Robie, Alice A and Hirokawa, Jonathan and Edwards, Austin W and
              Umayam, Lowell A and Lee, Allen and Phillips, Mary L and Card,
              Gwyneth M and Korff, Wyatt and Rubin, Gerald M and Simpson, Julie
              H and Reiser, Michael B and Branson, Kristin",
  abstract = "Assigning behavioral functions to neural structures has long been
              a central goal in neuroscience and is a necessary first step
              toward a circuit-level understanding of how the brain generates
              behavior. Here, we map the neural substrates of locomotion and
              social behaviors for Drosophila melanogaster using automated
              machine-vision and machine-learning techniques. From videos of
              400,000 flies, we quantified the behavioral effects of activating
              2,204 genetically targeted populations of neurons. We combined a
              novel quantification of anatomy with our behavioral analysis to
              create brain-behavior correlation maps, which are shared as
              browsable web pages and interactive software. Based on these
              maps, we generated hypotheses of regions of the brain causally
              related to sensory processing, locomotor control, courtship,
              aggression, and sleep. Our maps directly specify genetic tools to
              target these regions, which we used to identify a small
              population of neurons with a role in the control of walking.",
  journal  = "Cell",
  volume   =  170,
  number   =  2,
  pages    = "393--406.e28",
  month    =  jul,
  year     =  2017,
  keywords = "Drosophila; behavior; computer vision; machine learning; neural
              activation; neural anatomy; neural substrates; neuroscience;
              whole-brain mapping;Analysis/Modelling [Behaviour]",
  language = "en"
}

@ARTICLE{Grundemann2015-zj,
  title    = "Ensemble coding in amygdala circuits for associative learning",
  author   = "Gr{\"u}ndemann, Jan and L{\"u}thi, Andreas",
  abstract = "Associative fear learning in the basolateral amygdala (BLA) is
              crucial for an animal's survival upon environmental threats. BLA
              neurons are defined on the basis of their projection target,
              genetic markers, and associated function. BLA principal neuron
              responses to threat signaling stimuli are potentiated upon
              associative fear learning, which is tightly controlled by defined
              interneuron subpopulations. In addition, BLA population activity
              correlates with behavioral states and threat or safety signals.
              BLA neuronal ensembles activated by different behavioral signals
              can be identified using immediate early gene markers. The next
              challenge will be to determine the activity patterns and coding
              properties of defined BLA ensembles in relation to the whole
              neuronal population.",
  journal  = "Curr. Opin. Neurobiol.",
  volume   =  35,
  pages    = "200--206",
  month    =  dec,
  year     =  2015,
  keywords = "Threat response;Authors/Luthi",
  language = "en"
}

@ARTICLE{Colgin2016-ny,
  title    = "Rhythms of the hippocampal network",
  author   = "Colgin, Laura Lee",
  abstract = "The hippocampal local field potential (LFP) shows three major
              types of rhythms: theta, sharp wave-ripples and gamma. These
              rhythms are defined by their frequencies, they have behavioural
              correlates in several species including rats and humans, and they
              have been proposed to carry out distinct functions in hippocampal
              memory processing. However, recent findings have challenged
              traditional views on these behavioural functions. In this Review,
              I discuss our current understanding of the origins and the
              mnemonic functions of hippocampal theta, sharp wave-ripples and
              gamma rhythms on the basis of findings from rodent studies. In
              addition, I present an updated synthesis of their roles and
              interactions within the hippocampal network.",
  journal  = "Nat. Rev. Neurosci.",
  volume   =  17,
  number   =  4,
  pages    = "239--249",
  month    =  apr,
  year     =  2016,
  language = "en"
}

@ARTICLE{Bianco2015-sb,
  title    = "Visuomotor transformations underlying hunting behavior in
              zebrafish",
  author   = "Bianco, Isaac H and Engert, Florian",
  abstract = "Visuomotor circuits filter visual information and determine
              whether or not to engage downstream motor modules to produce
              behavioral outputs. However, the circuit mechanisms that mediate
              and link perception of salient stimuli to execution of an
              adaptive response are poorly understood. We combined a virtual
              hunting assay for tethered larval zebrafish with two-photon
              functional calcium imaging to simultaneously monitor neuronal
              activity in the optic tectum during naturalistic behavior.
              Hunting responses showed mixed selectivity for combinations of
              visual features, specifically stimulus size, speed, and contrast
              polarity. We identified a subset of tectal neurons with similar
              highly selective tuning, which show non-linear mixed selectivity
              for visual features and are likely to mediate the perceptual
              recognition of prey. By comparing neural dynamics in the optic
              tectum during response versus non-response trials, we discovered
              premotor population activity that specifically preceded
              initiation of hunting behavior and exhibited anatomical
              localization that correlated with motor variables. In summary,
              the optic tectum contains non-linear mixed selectivity neurons
              that are likely to mediate reliable detection of ethologically
              relevant sensory stimuli. Recruitment of small tectal assemblies
              appears to link perception to action by providing the premotor
              commands that release hunting responses. These findings allow us
              to propose a model circuit for the visuomotor transformations
              underlying a natural behavior.",
  journal  = "Curr. Biol.",
  volume   =  25,
  number   =  7,
  pages    = "831--846",
  month    =  mar,
  year     =  2015,
  language = "en"
}

@ARTICLE{Romero-Ferrero2018-dh,
  title    = "idtracker.ai: Tracking all individuals in large collectives of
              unmarked animals",
  author   = "Romero-Ferrero, F and Bergomi, M and Hinz, Robert and Heras, F
              and de Polavieja, G",
  journal  = "bioRxiv",
  month    =  mar,
  year     =  2018,
  keywords = "Analysis/Modelling [Behaviour]"
}

@ARTICLE{Skaggs1995-gd,
  title    = "A model of the neural basis of the rat's sense of direction",
  author   = "Skaggs, W E and Knierim, J J and Kudrimoti, H S and McNaughton, B
              L",
  abstract = "In the last decade the outlines of the neural structures
              subserving the sense of direction have begun to emerge. Several
              investigations have shed light on the effects of vestibular input
              and visual input on the head direction representation. In this
              paper, a model is formulated of the neural mechanisms underlying
              the head direction system. The model is built out of simple
              ingredients, depending on nothing more complicated than
              connectional specificity, attractor dynamics, Hebbian learning,
              and sigmoidal nonlinearities, but it behaves in a sophisticated
              way and is consistent with most of the observed properties of
              real head direction cells. In addition it makes a number of
              predictions that ought to be testable by reasonably
              straightforward experiments.",
  journal  = "Adv. Neural Inf. Process. Syst.",
  volume   =  7,
  pages    = "173--180",
  year     =  1995,
  keywords = "Spatial Navigation",
  language = "en"
}

@INCOLLECTION{Nitz2014-ca,
  title     = "The Posterior Parietal Cortex: Interface Between Maps of
               External Spaces and the Generation of Action Sequences",
  booktitle = "{Space,Time} and Memory in the Hippocampal Formation",
  author    = "Nitz, Douglas A",
  editor    = "Derdikman, Dori and Knierim, James J",
  abstract  = "In primates as well as rodents, the posterior parietal cortex
               maps spatial relationships having both egocentric and external
               frames of reference. In this chapter, the form in which rat
               posterior parietal cortex neuronal activity maps position within
               trajectories through the environment is considered in detail and
               compared to the forms of spatial mapping observed for neurons of
               the hippocampus and entorhinal cortex. Evidence is presented to
               indicate that posterior parietal neurons simultaneously map
               positions both within and across segments of paths through an
               environment. It is suggested that the specific nature of
               posterior parietal cortex mapping of space serves, in part, to
               transition knowledge of position in the environment, given by
               hippocampus and entorhinal cortex, into efficient path-running
               behavior via projections to primary and secondary sensory and
               motor cortices. Posterior parietal cortex activity is also
               hypothesized to play a role both in driving trajectory
               dependence of hippocampal place cells and in anchoring spatially
               specific hippocampal and entorhinal cortical activity to the
               boundaries of the observable environment.",
  publisher = "Springer Vienna",
  pages     = "27--54",
  year      =  2014,
  address   = "Vienna",
  keywords  = "Spatial Navigation;Authors/Nitz"
}

@ARTICLE{Nitz2009-vz,
  title    = "Parietal cortex, navigation, and the construction of arbitrary
              reference frames for spatial information",
  author   = "Nitz, Douglas",
  abstract = "The registration of spatial information by neurons of the
              parietal cortex takes on many forms. In most experiments,
              spatially modulated parietal activity patterns are found to take
              as their frame of reference some part of the body such as the
              retina. However, recent findings obtained in single neuron
              recordings from both rat and monkey parietal cortex suggest that
              the frame of reference utilized by parietal cortex may also be
              abstract or arbitrary in nature. Evidence in rats comes from work
              indicating that parietal activity in freely behaving rodents is
              organized according to the space defined by routes taken through
              an environment. In monkeys, evidence for an object-centered frame
              of reference has recently been presented. The present work
              reviews single neuron recording experiments in parietal cortex of
              freely behaving rats and considers the potential contribution of
              parietal cortex in solving navigational tasks. It is proposed
              that parietal cortex, in interaction with the hippocampus, plays
              a critical role in the selection of the most appropriate route
              between two points and, in addition, produces a route-based
              positional signal capable of guiding sensorimotor transitions.",
  journal  = "Neurobiol. Learn. Mem.",
  volume   =  91,
  number   =  2,
  pages    = "179--185",
  month    =  feb,
  year     =  2009,
  keywords = "navigation;Spatial Navigation;Authors/Nitz",
  language = "en"
}

@ARTICLE{Nitz2006-mn,
  title    = "Tracking route progression in the posterior parietal cortex",
  author   = "Nitz, Douglas A",
  abstract = "Quick and efficient traversal of learned routes is critical to
              the survival of many animals. Routes can be defined by both the
              ordering of navigational epochs, such as continued forward motion
              or execution of a turn, and the distances separating them. The
              neural substrates conferring the ability to fluidly traverse
              complex routes are not well understood, but likely entail
              interactions between frontal, parietal, and rhinal cortices and
              the hippocampus. This paper demonstrates that posterior parietal
              cortical neurons map both individual and multiple navigational
              epochs with respect to their order in a route. In direct contrast
              to spatial firing patterns of hippocampal neurons, parietal
              neurons discharged in a place- and direction-independent fashion.
              Parietal route maps were scalable and versatile in that they were
              independent of the size and spatial configuration of navigational
              epochs. The results provide a framework in which to consider
              parietal function in spatial cognition.",
  journal  = "Neuron",
  volume   =  49,
  number   =  5,
  pages    = "747--756",
  month    =  mar,
  year     =  2006,
  keywords = "navigation;Spatial Navigation;Authors/Nitz",
  language = "en"
}