Model of the cerebellar granular network (Sudhakar et al 2017)

 Download zip file 
Help downloading and running models
"The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. ..."
1 . Sudhakar SK, Hong S, Raikov I, Publio R, Lang C, Close T, Guo D, Negrello M, De Schutter E (2017) Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer. PLoS Comput Biol 13:e1005754 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum golgi cell;
Channel(s): I A; I Calcium; I K; I K,Ca; I Na,t; I h; I Na,p; I T low threshold;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; NMDA; Gaba;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Spatio-temporal Activity Patterns; Oscillations; Synchronization; Winner-take-all;
Implementer(s): Hong, Sungho [shhong at]; Guo, Daqing [dqguo at]; Raikov, Ivan [ivan.g.raikov at]; Publio, Rodrigo [publio at]; De Schutter, Erik [erik at];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; I Na,p; I Na,t; I T low threshold; I A; I K; I h; I K,Ca; I Calcium; Gaba; Glutamate;
// Template for connections from cerebellar Golgi to granule cells
// Written by Shyam Kumar Sudhakar, Ivan Raikov, Tom Close, Rodrigo Publio, Daqing Guo, and Sungho Hong
// Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Japan
// Supervisor: Erik De Schutter
// Correspondence: Sungho Hong (
// September 16, 2017

begintemplate GoCtoGC
external GranulePop,GolgiPop,MossyPop,numDendGolgi,step_time,gseed,CV_gmax
objref  inhNCelem,pc,r

proc init() { local i,j,count,gocid localobj nc,ncm,cell,gc

    print "Connecting GoCtoGC"

    numGC  = GranulePop.nCells
    numGoC = GolgiPop.nCells
    nD     = numDendGolgi

    p      = 1
    mGABA  = 100e-6
    SDGABA = mGABA*CV_gmax
    del    = 20
    thresh = -10

    pc = new ParallelContext()
    objref inhNCelem
    inhNCelem = new List()
    r = new Random(gseed)

    if (p==1) {

    // Inhibitory GoC to GC connections according rules defined by enPassage

    for (; i < numGC; i +=pc.nhost) {

        cell = pc.gid2cell(i+GranulePop.startindex)

        if (cell.GoCID.size()>1) { // At least 1 GoC connection

        for j=0, cell.GoCID.size()-1 {

            gocid = cell.GoCID.x(j)
            gc    = cell.gaba.object(0)

            nc    = pc.gid_connect(gocid, gc)

            if (cell.GoCdel.x(j)<=step_time) {

            w1 = r.normal(mGABA*8/cell.GoCID.size(), SDGABA*SDGABA*8/cell.GoCID.size())

            nc.weight = w1



    }//if p

} // end init
endtemplate GoCtoGC

objref ncGoCtoGC[1]
ncGoCtoGC[0] = new GoCtoGC()

Loading data, please wait...