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

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"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;
// Helper functions to create of the principal populations of the molecular layer
// 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

objref cvode,MFtoGCfile,MFtoGCfile1,MFtoGCfile2,MFtoGoCfile,pc1,IndexfileGoC,GCGLfile,GoCGLfile,GranuleVolfile
objref GoCtoGoCfile,GoCtoGoCgapfile,GoCtoGCfile,PFtoGoCfile,AxontoGoCfile,IndexfileGC,Granulegcurrentfile,Granulegconductancefile
objref MFGoCtotalfile,MFGCtotalfile,PFGoCtotalfile,AxonGoCtotalfile
objref GoCcoordinatesfile, GCcoordinatesfile, MFcoordinatesfile, MFspikefile, GoCadendcoordinatesfile, GoCbdendcoordinatesfile
objref GoCspiketimefile, cvector,GCspiketimefile, VMGoCfile, VMGCfile,BCSpikefile,BCfile,PCfile,GCTcoordinatesfile
objref PFtoSCfile, PFtoBCfile, PFSCtotalfile, PFBCtotalfile, BCgapfile,gapconfile,BCtoBCfile,SCSpikeFile,PCspike
objref SCcoordinatesfile, BCcoordinatesfile,SCGapFile,SCtoSCFile,nil,MFGCdelfile,MFGoCdelfile,PFGoCdelfile,AAGoCdelfile,GoCGCdelfile,GoCGoCdelfile
objref rand,timefile, Vtime, MFBundleCenter,MFBundleCenter_file,tmpfile,tmpfile1,GolgiVolfile
objref StellatePop , BasketPop,strobj,verify,GoCampafile,BCtoPCfile,SCtoPCfile,filea,fileb,current_GoC,GoCgapsourcefinal,GoCgaptargetfinal,GoCgapdistancefinal

rand = new Random()
pc1=new ParallelContext()
cvode = new CVode(0)
cvector = new Vector()
st = pc1.time

objref hines
hinest1 = startsw()
hinest2 = startsw()
hines = new FInitializeHandler(2, "hinest1=startsw() hinest2=startsw() hines1()")

proc hines1() {
        dt = step_time
        printf("%d t=%g dt=%g dreal=%g treal=%g\n", \
      , t, dt, startsw()-hinest2, startsw()-hinest1)
              //  if(pc1.gid_exists(5)){
              //        print "Vm",pc1.gid2cell(5).soma.v(0.5)
              //    }
        hinest2 = startsw()
        cvode.event(t + 1, "hines1()")

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