Cerebellar cortex oscil. robustness from Golgi cell gap jncs (Simoes de Souza and De Schutter 2011)

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Accession:139656
" ... Previous one-dimensional network modeling of the cerebellar granular layer has been successfully linked with a range of cerebellar cortex oscillations observed in vivo. However, the recent discovery of gap junctions between Golgi cells (GoCs), which may cause oscillations by themselves, has raised the question of how gap-junction coupling affects GoC and granular-layer oscillations. To investigate this question, we developed a novel two-dimensional computational model of the GoC-granule cell (GC) circuit with and without gap junctions between GoCs. ..."
Reference:
1 . Simões de Souza F, De Schutter E (2011) Robustness effect of gap junctions between Golgi cells on cerebellar cortex oscillations Neural Systems & Circuits 1:7:1-19
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 interneuron granule cell; Cerebellum golgi cell;
Channel(s):
Gap Junctions: Gap junctions;
Receptor(s): GabaA; AMPA; NMDA;
Gene(s): HCN1; HCN2;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Synchronization; Action Potentials;
Implementer(s): Simoes-de-Souza, Fabio [fabio.souza at ufabc.edu.br];
Search NeuronDB for information about:  Cerebellum interneuron granule cell; GabaA; AMPA; NMDA;
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network
data
README.txt
gap.mod
Golgi_BK.mod *
Golgi_Ca_HVA.mod *
Golgi_Ca_LVA.mod *
Golgi_CALC.mod *
Golgi_CALC_ca2.mod *
Golgi_hcn1.mod *
Golgi_hcn2.mod *
Golgi_KA.mod *
Golgi_KM.mod *
Golgi_KV.mod *
Golgi_lkg.mod *
Golgi_Na.mod *
Golgi_NaP.mod *
Golgi_NaR.mod *
Golgi_SK2.mod *
GRC_CA.mod *
GRC_CALC.mod *
GRC_KA.mod *
GRC_KCA.mod *
GRC_KIR.mod *
GRC_KM.mod *
GRC_KV.mod *
GRC_LKG1.mod *
GRC_LKG2.mod *
GRC_NA.mod *
K_conc.mod *
Na_conc.mod *
Golgi_ComPanel.hoc *
Golgi_template.hoc
granule_template.hoc
MF_template.hoc
mosinit.hoc
network.hoc
utils.hoc *
                            
load_file("nrngui.hoc")
/////////////////////////
//Simulation parameters//
////////////////////////
tmax=150         
cvode.active(0)  //Fixed time step 
DT=0.025	

//////////////////////////
//MF stimulus parameters//   
/////////////////////////
MFfreq=100
NETIN_SP_START=100
SEED=1

///////////////////////////////
//uncomment gap junction flag//
//////////////////////////////
GJ=1      // with GJ between GoCs
//GJ=0      // without GJ between GoCs

///////////////////////////
//Building Network Layers//
///////////////////////////
load_file("network.hoc") 

//////////////////////
//Running Simulation//
/////////////////////
cleanMF()      //clear MF buffers
stimulus(NETIN_SP_START, MFfreq, tmax, SEED)  //start MF stimulus

init()
tstop=DT 
run()  //run a single time step

//set vinit to randomize vrest
min=-84 
max=-56 

for i=0, NumberCellsb-1 {
  xprob=prob.uniform(min,max)
  GrC[i].setv(xprob)
}
for i=0, NumberCellsd-1 {
  xprob=prob.uniform(min,max)
  GoC[i].setv(xprob)
}

continuerun(tmax) //run the rest of simulation

//simulation finished

/////////////////////////
//Generate Raster Plots//
/////////////////////////
objref g1
g1 = new Graph()
idvec1.mark(g1, timevec1, "|")

objref g2
g2 = new Graph()
idvec2.mark(g2, timevec2, "|")

///////////////////////
//Save Data to Files//
//////////////////////

GoCMatrixS.resize(tmax,NumberCellsd) 
GrCMatrixS.resize(tmax,NumberCellsb) 
MFMatrixS.resize(tmax,NumberCellsa) 
for i = 0, NumberCellsa-1 {
MFMatrixS.setcol(i,fiber[i].spiketimes)  
}
for i = 0, NumberCellsb-1 {
GrCMatrixS.setcol(i,GrC[i].spiketimes) 
}
for i = 0, NumberCellsd-1 {
GoCMatrixS.setcol(i,GoC[i].spiketimes)  
}

//record Vectors to File	
MFMatrixS.fprint(sav_MFMatrixS," %g")
GrCMatrixS.fprint(sav_GrCMatrixS," %g")
GoCMatrixS.fprint(sav_GoCMatrixS," %g")

//Close Files	
sav_MFMatrixS.close()
sav_GrCMatrixS.close()
sav_GoCMatrixS.close()

//move the files to data folder
strdef command
sprint(command,"mv *.dat data/")
system(command)

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