Konstantin Willeke 205a438f96 Upload files to 'decoding scans'		2 tahun lalu
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Ellipse_25830-5-10.h5	205a438f96 Upload files to 'decoding scans'	2 tahun lalu
Ellipse_25891-7-7.h5	205a438f96 Upload files to 'decoding scans'	2 tahun lalu
Ellipse_26872-20-10.h5	205a438f96 Upload files to 'decoding scans'	2 tahun lalu
Objects_22904_3_9.h5	cf669e3eeb upload all decoding scans	2 tahun lalu
Objects_22904_4_5.h5	205a438f96 Upload files to 'decoding scans'	2 tahun lalu
Objects_25830_6_5.h5	cf669e3eeb upload all decoding scans	2 tahun lalu
Objects_25830_6_6.h5	cf669e3eeb upload all decoding scans	2 tahun lalu
Objects_25891_12_10.h5	cf669e3eeb upload all decoding scans	2 tahun lalu
Objects_25891_12_11.h5	cf669e3eeb upload all decoding scans	2 tahun lalu
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README.md	76ab6ea9e6 Update 'decoding scans/README.md'	2 tahun lalu

Dataset Structure

The decoding scans are provided as .h5 files. There are two types of decoding scans:

Objects: For the object discrimation task
Ellipse: For the detection task

The following attributes are present in each individual dataset:

pupil_trials: mean pupil size for each trial
- shape:n_trials,
class_trials: image class for each trial. See below for details.
- shape:n_trials,
activity_trials: mean activity per neuron for each trial
- shape:n_neurons x n_trials

`class_trials` description

Object discrimination task

Paradigm 1

o1BLfgv2: object 1, green channel, foreground (Fig. 5)
o2BLfgv2: object 2, green channel, foreground (Fig. 5)
o1UVfgv2: object 1, UV channel, foreground (Fig. 5)
o2UVfgv2: object 2, UV channel, foreground (Fig. 5)

Paradigm 2

o1BLfbv2: object 1, green channel, foreground & background & positive contrast (Extended Data Fig. 10)
o2BLfbv2: object 2, green channel, foreground & background & positive contrast (Extended Data Fig. 10)
o1UVfbv2: object 1, UV channel, foreground & background & positive contrast (Extended Data Fig. 10)
o2UVfbv2: object 2, UV channel, foreground & background & positive contrast (Extended Data Fig. 10)

Paradigm 3

o1BLfdv2: object 1, green channel, foreground & background & negative contrast (Extended Data Fig. 10)
o2BLfdv2: object 2, green channel, foreground & background & negative contrast (Extended Data Fig. 10)
o1UVfdv2: object 1, UV channel, foreground & background & negative contrast (Extended Data Fig. 10)
o2UVfdv2: object 2, UV channel, foreground & background & negative contrast (Extended Data Fig. 10)

Paradigm 4

o1BLnbv2: object 1, green channel, no background/foreground (Extended Data Fig. 10)
o2BLnbv2: object 2, green channel, no background/foreground (Extended Data Fig. 10)
o1UVnbv2: object 1, UV channel, no background/foreground (Extended Data Fig. 10)
o2UVnbv2: object 2, UV channel, no background/foreground (Extended Data Fig. 10)

Detection task

green: dark ellipse is present in the green color channel
uv: dark ellipse is present in the UV color channel
noise: no ellipse is present

datacite.yml
Title	State-dependent pupil dilation rapidly shifts visual feature representations
Authors	Franke,Katrin;Institute for Ophthalmic Research, Tuebingen University, Tuebingen, Germany. Willeke,Konstantin F.;Institute for Bioinformatics and Medical Informatics, Tuebingen University, Tuebingen, Germany Ponder,Kayla;Department of Neuroscience, Baylor College of Medicine, Houston, TX, US Galdamez,Mario;Department of Neuroscience, Baylor College of Medicine, Houston, TX, US Zhou,Na;Department of Neuroscience, Baylor College of Medicine, Houston, TX, US Muhammad,Taliah;Department of Neuroscience, Baylor College of Medicine, Houston, TX, US Patel,Saumil;Department of Neuroscience, Baylor College of Medicine, Houston, TX, US Froudarakis,Emmanouil;Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, Heraklion, Greece Reimer,Jacob;Department of Neuroscience, Baylor College of Medicine, Houston, TX, US Sinz,Fabian;Department of Computer Science, Goettingen University, Goettingen, Germany Tolias,Andreas;Department of Neuroscience, Baylor College of Medicine, Houston, TX, US
Description	Complete dataset for the article "State-dependent pupil dilation rapidly shifts visual feature representations".
License	CC-BY (http://creativecommons.org/licenses/by/4.0/)
References	Franke, K., Willeke, K.F., Ponder, K., Galdamez, M., Muhammad, T., Patel, S., Froudarakis, E., Reimer, J., Sinz, F., & Tolias, A.S. (2021). Behavioral state tunes mouse vision to ethological features through pupil dilation. bioRxiv. [doi:10.1101/2021.09.03.458870] (IsSupplementTo)
Funding	DFG, EXC 2064/1 IARPA, D16PC00003 NIH, R01 EY026927 NIH, T32-EY-002520-37 NSF, 1707400 Carl-Zeiss-Stiftung
Keywords	Neuroscience Systems Neuroscience Primary visual cortex Brain state Behavioral state Machine learning Deep neural networks
Resource Type	Dataset