Surround Suppression in V1 via Withdraw of Balanced Local Excitation in V1 (Shushruth 2012)

 Download zip file 
Help downloading and running models
The model is mean-field network models, which is set up as a so-called ring-model, i. e. it is a highly idealized model of an orientation hypercolumn in primary visual cortex. Long-range intra-areal and inter-areal feedback connections are modeled phenomenologically as an external input. In this model, there are recurrent interactions via short-range local connections between orientation columns, but not between hypercolumns.
1 . Shushruth S, Mangapathy P, Ichida JM, Bressloff PC, Schwabe L, Angelucci A (2012) Strong recurrent networks compute the orientation tuning of surround modulation in the primate primary visual cortex. J Neurosci 32:308-21 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell;
Gap Junctions:
Receptor(s): GabaA; AMPA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: MATLAB;
Model Concept(s): Vision;
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; GabaA; AMPA; Gaba; Glutamate;
function showMultiplot( yResult, plotfun, plotfunxlim, plotfunylim, bFlipUD )

    if nargin <= 4
        bFlipUD = 0;

    nRows = size( yResult, 1 );
    nCols = size( yResult, 2 );

    for i = 1:nRows
        for j = 1:nCols
            if bFlipUD
                subplot( nRows, nCols, spos(nCols,j,nRows-(i-1),1,1) );
                subplot( nRows, nCols, spos(nCols,j,i,1,1) );
            plotfun( yResult{i,j} );
            set( gca, 'XLim', plotfunxlim(yResult{i,j}) );
            set( gca, 'YLim', plotfunylim(yResult{i,j}) );
            axis off;