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Paul Pfeiffer 29b8619001 refactored simulation of delayed inhibition into a separate class %!s(int64=4) %!d(string=hai) anos
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literature 25246b7e0b first paper on well timed inhibition %!s(int64=4) %!d(string=hai) anos
models 8b28da9f74 PRC of Hodkin-Huxley with H-current is as desired. Transfer from notebook to script %!s(int64=4) %!d(string=hai) anos
notebooks 8b28da9f74 PRC of Hodkin-Huxley with H-current is as desired. Transfer from notebook to script %!s(int64=4) %!d(string=hai) anos
reports 2926565fb1 collections of ideas to tackle feature competition by polar interneurons %!s(int64=5) %!d(string=hai) anos
scripts 29b8619001 refactored simulation of delayed inhibition into a separate class %!s(int64=4) %!d(string=hai) anos
simulations 57d9aa725c adapted synaptic strengths %!s(int64=4) %!d(string=hai) anos
src 179efaba46 spike count extraction, plooting of connectivity profile, allow strings in parameters %!s(int64=4) %!d(string=hai) anos
tests a1a6f75000 testing for spike train analysis %!s(int64=4) %!d(string=hai) anos
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AUTHORS.rst 3d18bfd015 meta files for scaffolding %!s(int64=4) %!d(string=hai) anos
CHANGELOG.rst 3d18bfd015 meta files for scaffolding %!s(int64=4) %!d(string=hai) anos
LICENSE.txt 3d18bfd015 meta files for scaffolding %!s(int64=4) %!d(string=hai) anos
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requirements.txt 767703b074 prepared spatial arrangement of the network, used pyscaffold as a scaffolding template %!s(int64=4) %!d(string=hai) anos
setup.cfg 767703b074 prepared spatial arrangement of the network, used pyscaffold as a scaffolding template %!s(int64=4) %!d(string=hai) anos
setup.py 767703b074 prepared spatial arrangement of the network, used pyscaffold as a scaffolding template %!s(int64=4) %!d(string=hai) anos

README.md

Functional aspects of interneuron morphology in the subiculum

Interneurons in the subiculum have a polar axonal cloud instead of a circular as found in other brain regions. Additionally, pyramidal neurons in the subiculum lack recurrent connections, but they connect via recurrent inhibition. Therefore, inhibition plays a major role in this circuitry and we pose the question, which function the extraordinary axon morphology serves in this setting.

Model

  1. Distribute excitatory somata in space.
  2. Distribute inhibitory somata in space.
  3. Choose an axonal shape (polar or circular).
  4. Connect excitatory neurons which are contained the same interneuron axonal cloud.

Analysis

  1. Compare first and second order connectivity

Two neurons directly connected neuron inhibit each other, because they project to the same interneuron (as a circuit motif E<->I<->E). Therefore, second order neighbors are effectively excitatory (via disinhibition). We therefore extracted the distance dependent first and second order connectivity to compare them for polar and circular axonal shapes.