A cortical sheet mesoscopic model for investigating focal seizure onset dynamics (Wang et al. 2014)

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Accession:155565
The model uses realistically coupled, discretised, Wilson-Cowan units to describe the spatio-temporal activity of a cortical sheet. This model has been used the investigate the dynamic onset mechanisms of focal seizures.
Reference:
1 . Wang Y, Goodfellow M, Taylor PN, Baier G (2014) Dynamic mechanisms of neocortical focal seizure onset PLoS Computational Biology 10(8):e1003787 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neural mass;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Oscillations; Spatio-temporal Activity Patterns; Epilepsy; Delay; Brain Rhythms; Bifurcation;
Implementer(s): Wang, Yujiang [yujiang.wang at newcastle.ac.uk];
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WebPublication
lib
ConnLocGaussian.m *
ConnPatchyRemOverlap.m *
Conns_n150.mat
convolve2.m *
distSheet.m *
distTorus.m *
exindex.m *
FilterEEG.m
Gaussian.m *
GaussianLocConnFunc.m
generatePatchesOverlap.m *
getDelayMatrix.m
getNoise.m
getParam.m *
getParamDelay.m
makeCellCluster.m *
makeCellClusterToroidal.m *
MayColourMap.mat *
meanMacroCol.m *
runSheet.m *
runSheetDelay.m *
runSheetPRamp.m *
Sigm.m *
                            
function parameters=getParam(n,CeRem,CeLoc,CeLocI)


parameters.n=n;%sheet is nxn

parameters.Py2Py=10*speye(n^2)+.15*CeLoc+.05*CeRem;%conn matrix Py to Py
%parameters.Py2Py=10*speye(n^2)+.1*CeLoc+.1*CeRem;%conn matrix Py to Py
parameters.Inh2Py=25*speye(n^2);%in this parameter set the increase in this prolongs the onset & prevents too much going to the upper fixed point
parameters.Py2Inh=0.1*CeLocI+15*speye(n^2);%
parameters.Inh2Inh=0.0*speye(n^2);

parameters.PyInput=-2.5*(ones(n^2,1));
parameters.InhInput=-5*ones(n^2,1);
    


parameters.tauPy=1*ones(n^2,1)/25;%time scale of the populations
parameters.tauInh=0.5*ones(n^2,1)/25;
%parameters.tauInFast=0.1*ones(n^2,1);

parameters.SigThresh=4*ones(n^2,1);%sigmoid parameters
parameters.SigSteepness=1*ones(n^2,1);

parameters.h=1/(500);

end

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