pgleeson / GoCModel_Basic

network of gocs with low frequency background inputs

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GoCModel_Basic

Basic code to generate network of electrically coupled cerebellar Golgi cells with low frequency background inputs

Model descriptions

Channel and synapse mechanisms are in Mechanisms

Cell descriptions are in Cells/Golgi

More channel density sets are stored in Parameters that when inserted into the Solinas morphology, produce autonomous firing rates of 2-9 Hz and F-I slope of 14-25 Hz/nA.

Varying channel densities

To construct new GoC files using one of the morphologies and different parameter sets, use vary_channels.py or vary_channels_2pools.py - depending on whether you want a cell of class Cell or Cell2CaPools.

Generating networks

Utils

PythonUtils has function definitions for generating connectivity (electrical or chemical)

Known Issues 👷

  • Using reduced or full morphology with current channel densities causes model to fail (Vm goes to 80mV after around 500 ms -> which channel is unstable? Density adjustment for morphology?)
    • ✅ Fix: NaT reaches very small time constants at spike -> use much smaller integration dt (0.001 ms or lower)
  • Constructing network with a Population that has ComponentType from class Cell2CaPools -> LEMS file fails to be generated
    • 🔹 Diagnosis: Cannot create events file using event port 'spike' - not supported for class Cell2CaPools?
  • For some morphology?, synapses can only be inserted at location=0.5 along dendrite.
    • 🔹 In that case, comment line 156 and uncomment 158 that create connectionWD instances for each background input and insert them into dendrites (in generate _simple_network.py )

Requirements

  • python2.7

  • NeuroML and pyNeuroML python libraries

  • jvm

  • Neuron 7.3 or above (compile mod)

About

network of gocs with low frequency background inputs

License:GNU General Public License v3.0


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