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Optimal balance predicts/explains amplitude and decay time of iPSGs (Kim & Fiorillo 2017)

modeldb.science/226364

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
After_learning.hoc		After_learning.hoc
Before_learning.hoc		Before_learning.hoc
IEIs_50Hz.tmp		IEIs_50Hz.tmp
README.html		README.html
hh2.mod		hh2.mod
init.hoc		init.hoc
mosinit.hoc		mosinit.hoc
netstims.mod		netstims.mod
screenshot1.png		screenshot1.png
screenshot2.png		screenshot2.png
tc1.geo		tc1.geo

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<html><pre>
This is the readme for the model associated with the paper:
 
Kim, J. K. & Fiorillo, C. D. Theory of optimal balance predicts and
explains the amplitude and decay time of synaptic
inhibition. Nat. Commun. 8, 14566 doi: <a href="http://dx.doi.org/10.1038/ncomms14566">10.1038/ncomms14566</a> (2017).

This model was contributed by Jaekyung Kim.

This is a single-compartment model of a generic neuron. It was edited
from the single-compartment model of thalamocortical (TC) relay
neurons used in Destexhe et al. (1998). It includes passive (leakage),
excitatory synaptic (AMPAergic), inhibitory synaptic (GABAergic or
glycinergic), sodium and potassium (for action potential)
conductances. It was used to test optimal parameters of synaptic
inhibition.

Two "~.hoc" files provide voltage responses for the EPSG ensemble of
mean rate of 50 Hz, with parameters of IPSG before learning and after
learning by learning rule 2 shown in Fig. 8 in Kim and Fiorillo
(2017).

This model was developed in Neuron 7.3.

  PROGRAMS and FILES
  ==================

Before_learning.hoc : Voltage response with default parameters of
                      synaptic inhibition.
After_learning.hoc  : Voltage response with default parameters learned
		      from anti-Hebbian learnng rule (Rule 2 of
                      Fig. 8 in Kim and Fiorillo (2017)).
IEIs_50Hz.tmp       : Randomized inter-EPSG interval simulated in Kim
                      and Fiorillo (2017).
tc1.geo             : Geometry for single-compartment

  MECHANISMS
  ==========
hh2.mod             : Fast spikes (Na+ and K+ currents)
netstims.mod        : Presynaptic spike generator

  HOW TO RUN
  ==========
Either auto-launch from ModelDB or:
After compiling the mod files and starting the simulation with "~.hoc" files.
For additional help see:
<a href="https://senselab.med.yale.edu/ModelDB/NEURON_DwnldGuide.html">https://senselab.med.yale.edu/ModelDB/NEURON_DwnldGuide.html</a>

If starting from mosinit.hoc or init.hoc choose a simulation by
clicking a button.  Before learning generates these graphs:

<img src="./screenshot1.png" alt="screenshot 1" width="550">

After learning generates these graphs:

<img src="./screenshot2.png" alt="screenshot 2" width="550">

For further information, please contact Jaekyung Kim (kimjack0@kaist.ac.kr)
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