Large cortex model with map-based neurons (Rulkov et al 2004)

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Accession:45525
We develop a new computationally efficient approach for the analysis of complex large-scale neurobiological networks. Its key element is the use of a new phenomenological model of a neuron capable of replicating important spike pattern characteristics and designed in the form of a system of difference equations (a map). ... Interconnected with synaptic currents these model neurons demonstrated responses very similar to those found with Hodgkin-Huxley models and in experiments. We illustrate the efficacy of this approach in simulations of one- and two-dimensional cortical network models consisting of regular spiking neurons and fast spiking interneurons to model sleep and activated states of the thalamocortical system. See paper for more.
Reference:
1 . Rulkov NF, Timofeev I, Bazhenov M (2004) Oscillations in large-scale cortical networks: map-based model. J Comput Neurosci 17:203-23 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex fast spiking (FS) interneuron;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program;
Model Concept(s): Activity Patterns; Oscillations; Spatio-temporal Activity Patterns; Simplified Models; Sleep;
Implementer(s): Bazhenov, Maxim [Bazhenov at Salk.edu]; Rulkov, Nikolai [nrulkov at ucsd.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; GabaA; AMPA;
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largectx2004
index.html
colors.m
import2D.m
input2D.txt
movieMAP.m
network2D.cpp
                            
function pmovie()
global RAW2D 
[m,n,k]= size(RAW2D)

lo= -1.25; hi= -0.5;
S= (RAW2D<lo)*lo + (RAW2D>hi)*hi + ((RAW2D>=lo)&(RAW2D<=hi)).*RAW2D - lo;
S= round(4*S+1);

%colormap(flipud(pink(4*(hi-lo)+1)))
colors(1,128,1,1)

subplot(1,1,1);
for i=1:k
   image(30*S(:,:,i))
   set(gcf,'DefaultTextFontSize',10)
   ss=i*25;
   pp1=num2str(ss);
   pp2=['T=' pp1 ' '];
   text(3,-3,pp2)
   ii=num2str(i);
   rr=['mov' ii '.png']
   print('-dpng',rr)
end

%colormap(flipud(hot(4*(hi-lo)+1)))
%colormap(flipud(pink(4*(hi-lo)+1)))
%aa=axes('position',[0.92 0.33 0.02 0.2])
%colorbar(aa)
%colors(1,128,1,1)
%set(aa,'YLim',[50 100])
%set(aa,'YTicklabel',{'0';' ';'1'})