A microcircuit model of the frontal eye fields (Heinzle et al. 2007)

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Accession:110022
" ... we show that the canonical circuit (Douglas et al. 1989, Douglas and Martin 1991) can, with a few modifications, model the primate FEF. The spike-based network of integrate-and-fire neurons was tested in tasks that were used in electrophysiological experiments in behaving macaque monkeys. The dynamics of the model matched those of neurons observed in the FEF, and the behavioral results matched those observed in psychophysical experiments. The close relationship between the model and the cortical architecture allows a detailed comparison of the simulation results with physiological data and predicts details of the anatomical circuit of the FEF."
Reference:
1 . Heinzle J, Hepp K, Martin KA (2007) A microcircuit model of the frontal eye fields. J Neurosci 27:9341-53 [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):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Spatio-temporal Activity Patterns; Action Selection/Decision Making; Vision;
Implementer(s):
% update_input_saccade updates the spatial visual input to the network
% according to the saccade.
%
% created: Jakob Heinzle 01/07

for k=1:inputs.ninputs
    if inputs.external{k}.retinotopic
        middle=fov+(nfac+1)/2;
        if middle>21
            helparray=zeros(nfac,1);
        elseif middle>11
            helparray=[inputs.external{k}.inarray(middle-10:nfac) zeros(1,middle-11)];
        elseif middle==11
            helparray=inputs.external{k}.inarray;
        elseif middle<0
            helparray=zeros(nfac,1);
        elseif middle<11
            helparray=[zeros(1,11-middle) inputs.external{k}.inarray(1:middle+10)];

        end
        % auxiliary variables.
        nperpop=pops.population{n_to}.poolsize;
        InpH=zeros(nperpop*nfac,1);
        for oo=1:nfac
            InpH((oo-1)*nperpop+1:oo*nperpop)=helparray(oo);
        end
        inputs.external{k}.ExtInp=inputs.external{k}.MeanInp*InpH;
        inputs.external{k}.NoiseExtInp=sqrt(gmaxE_ext*InpH/2);
        if strcmp(inputs.external{k}.name,'VisualInput') % change input timing for visual input only.
            inputs.external{k}.t_on=t+50;
            inputs.external{k}.t_trans_off=t+90;
            if ((middle<21.5)&(middle>0.5))
                stimatfovea=helparray(middle);
            else
                stimatfovea=0;
            end
        end
    elseif strcmp(inputs.external{k}.name,'FeatureSpace')  % check if the input is the input to white spaces detectors.
        nperpop=pops.population{n_to}.poolsize;
        InpH=zeros(nperpop,1)+(stimatfovea==0);
        inputs.external{k}.ExtInp=inputs.external{k}.MeanInp*InpH;
        inputs.external{k}.NoiseExtInp=sqrt(gmaxE_ext*InpH/2);
    end
end

disp('Visual input changed')