Models for cortical UP-DOWN states in a bistable inhibitory-stabilized network (Jercog et al 2017)

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Accession:227972
In the idling brain, neuronal circuits transition between periods of sustained firing (UP state) and quiescence (DOWN state), a pattern the mechanisms of which remain unclear. We analyzed spontaneous cortical population activity from anesthetized rats and found that UP and DOWN durations were highly variable and that population rates showed no significant decay during UP periods. We built a network rate model with excitatory (E) and inhibitory (I) populations exhibiting a novel bistable regime between a quiescent and an inhibition-stabilized state of arbitrarily low rate, where fluctuations triggered state transitions. In addition, we implemented these mechanisms in a more biophysically realistic spiking network, where DOWN-to-UP transitions are caused by synchronous high-amplitude events impinging onto the network.
Reference:
1 . Jercog D, Roxin A, Barthó P, Luczak A, Compte A, de la Rocha J (2017) UP-DOWN cortical dynamics reflect state transitions in a bistable network. Elife [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Abstract integrate-and-fire leaky neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program; MATLAB;
Model Concept(s): Spike Frequency Adaptation; Activity Patterns; Oscillations;
Implementer(s): Jercog, Daniel [daniel dot jercog at inserm dot fr] ; 
Contributed by Daniel Jercog.


This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details (http://www.gnu.org/licenses/).


Contains both rate and spiking network model implementations from the paper Jercog et al 2017. Both models generate the time courses for E & I population rates and adaptation presented. In addition, the Spiking network generates individual spiking activity in rasters. A complete description of the model is provided in the methods of the paper.

+ Rate model (compiled in Matlab 2009 - Linux).
  Include following files in a separated folder:
  -singleSimEIModel.m: main function (also plots the output traces).
  -eiModelParams.m: model parameters.
  -eiModel.mexa64: Compiled MEX-function from source eiModel.cpp (Unix).
  -eiModel.cpp: c++ mex-function source.
  -rate_readme.txt: description.

+ Spiking Model (compiled in g++ 6.4.3 - Linux):
  Include following files in a separated folder:
  -main.cpp: main function, generate output bin files.
  -functions.h:   auxiliar functions.
  -functions.cpp: auxiliar functions.
  -spiking_readme.txt: description.

Further instructions for usage of each model in their corresponding readme-files.