Multicompartmental cerebellar granule cell model (Diwakar et al. 2009)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:116835
A detailed multicompartmental model was used to study neuronal electroresponsiveness of cerebellar granule cells in rats. Here we show that, in cerebellar granule cells, Na+ channels are enriched in the axon, especially in the hillock, but almost absent from soma and dendrites. Numerical simulations indicated that granule cells have a compact electrotonic structure allowing EPSPs to diffuse with little attenuation from dendrites to axon. The spike arose almost simultaneously along the whole axonal ascending branch and invaded the hillock, whose activation promoted spike back-propagation with marginal delay (<200 micros) and attenuation (<20 mV) into the somato-dendritic compartment. For details check the cited article.
Reference:
1 . Diwakar S, Magistretti J, Goldfarb M, Naldi G, D'Angelo E (2009) Axonal Na+ channels ensure fast spike activation and back-propagation in cerebellar granule cells J Neurophysiol 101(2):519-32 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum interneuron granule cell;
Channel(s): I A; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Active Dendrites; Detailed Neuronal Models; Axonal Action Potentials; Action Potentials; Intrinsic plasticity;
Implementer(s): Diwakar, Shyam [shyam at amrita.edu];
Search NeuronDB for information about:  Cerebellum interneuron granule cell; I A; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow;
/
GrC
fig10
readme.html
AmpaCOD.mod *
GRC_CA.mod *
GRC_CALC.mod *
GRC_GABA.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 *
NmdaS.mod *
Pregen.mod *
ComPanel.hoc
Grc_Cell.hoc
mosinit.hoc
Parametri.hoc
screenshot.jpg
simple.ses
Start.hoc
                            
// Detailed model of Cerebellar Granular Cell model
// Multicompartmental model - Control and synaptic mechanisms panel script
// Last updated 07-Jan-2009
// Model developer: Shyam Diwakar M.
// Developed at Egidio D'Angelo's Lab at Univ of Pavia
// Code contributors: Thierry Nieus, Sergio Solinas 
// Dept. of Gen. Physiology (Univ. of Pavia, Italy)
// School of biotech (Amrita University, India) 
// Email:shyam@unipv.it

/* Model published as [Diwakar et al, J.Neurophysiology] 
 Shyam Diwakar, Jacopo Magistretti, Mitchell Goldfarb, Giovanni Naldi, and Egidio D'Angelo.
 Axonal Na+ channels ensure fast spike activation and back-propagation in cerebellar granule cells, J Neurophysiol (December 10, 2008). 
 doi:10.1152/jn.90382.2008
 */ 

objref AmpaSchemeMenu,mfpanel,ifpanel


Ampa_Gmax=600
Gaba_gmax = Granule[0].synG[0].gmax
Nmda_Gmax2_ES=16000
GmaxCOD=Ampa_Gmax
GmaxNES = Nmda_Gmax2_ES
GmaxGaba = 2500
Ampa_G = 600
Nmda_G = Granule[0].synNS[0].gmax
NumSin=0
NumISin=0


xpanel("Control Panel")
	xlabel(" ===== Command Panel ===== ")
	//xbutton("GrC Soma","GrcPanel()")
	xbutton("Postsynaptic","Synapses()")
	xbutton("Exc Presyn Parameters","PresynParam()")
	xbutton("Inh Presyn Parameters","PresynGParam()")
	xmenu("Mossy Fibers")
		     xradiobutton("Homogeneous mf","HomogeneousMf()")	
		     //xradiobutton("Heterogeneous mf","HeterogeneousMF()")
		     xradiobutton("Mossy traces","MossyFiberTraces()")
	xmenu()
	xmenu("Inhibitory Synapses")
		     xradiobutton("Homogeneous if","HomogeneousIf()")	
		     //xradiobutton("Heterogeneous if","HeterogeneousIF()")
		     xradiobutton("Inhib Synaptic fiber traces","InhibFiberTraces()")
	xmenu()
xpanel()


// *************************** GrC parameters ***********************//

objref GRCparams

proc GrcPanel(){
	GRCparams = new VBox()
	GRCparams.intercept(1)   
	xpanel("1")  
	xlabel("Soma Properties")
	xvalue("gNabar","Granule[0].soma.gnabar_GRC_NA", 1,"", 0, 0 )
	xvalue("gKVbar","Granule[0].soma.gkbar_GRC_KV", 1,"", 0, 0 )
	xvalue("gKAbar","Granule[0].soma.gkbar_GRC_KA", 1,"", 0, 0 )
	xvalue("gKirbar","Granule[0].soma.gkbar_GRC_KIR", 1,"", 0, 0 )
	xvalue("gKCabar","Granule[0].soma.gkbar_GRC_KCA", 1,"", 0, 0 )
	xvalue("gCaHVAbar","Granule[0].soma.gcabar_GRC_CA", 1,"", 0, 0 )
	xvalue("gKSlowbar","Granule[0].soma.gkbar_GRC_KM", 1,"", 0, 0 )
	xvalue("gLeakage","Granule[0].soma.gl_GRC_LKG1", 1,"", 0, 0 )
	xvalue("gGabaA","Granule[0].soma.ggaba_GRC_LKG2", 1,"", 0, 0 )
	xpanel()
	xpanel("2")
	xlabel("Calcium parameters")
	xvalue("Shell thickness","Granule[0].soma.d_GRC_CALC", 1,"", 0, 0 )
	xvalue("Initial concentration","Granule[0].soma.cai0_GRC_CALC", 1,"", 0, 0 )
	xvalue("Removal rate","Granule[0].soma.beta_GRC_CALC", 1,"", 0, 0 ) 
	xpanel()
	GRCparams.intercept(0)
	GRCparams.map("Granule Cell Parameters")
}


proc UpdateAmpaNmda() {
	Ampa_Gmax = Ampa_G
	Nmda_Gmax2_ES = Nmda_G
	for(i=0;i<8;i=i+1) {
		AmpaCOD[i].gmax=Ampa_Gmax
		NMDAS[i].gmax=Nmda_Gmax2_ES
	}
	for(i=0;i<4;i=i+1) {
		Granule[0].synA[i].gmax=Ampa_Gmax
		Granule[0].synNS[i].gmax=Nmda_Gmax2_ES
	}
}

proc UpdateGaba() {
	for(i=0;i<8;i=i+1) {
		GRC_GABA[i].gmax=GmaxGaba
		GRC_GABA[i].U=0.34
	}
	for(i=0;i<4;i=i+1) {
		Granule[0].synG[i].gmax=GmaxGaba
	}
}

// ************************************* Presynpatic-Exc and Inh *********************************


proc PresynParam(){
	Tau_rec=Granule[0].synA[0].tau_rec
	Tau_facil=Granule[0].synA[0].tau_facil
	Tau_1=Granule[0].synA[0].tau_1
	U=Granule[0].synA[0].U
	xpanel("PRESYNAPTIC PARAMETERS")   
		xlabel("Exc Presynaptic parameters")
		xvalue("T_transition (ms)","Tau_1", 1,"UpDatePre()", 0, 0 )
		xvalue("T_recovery (ms)","Tau_rec", 1,"UpDatePre()", 0, 0 )
		xvalue("T_facilita (ms)","Tau_facil", 1,"UpDatePre()", 0, 0 )
		xvalue("Release probability","U", 1,"UpDatePre()", 0, 0 )
	xpanel()
}

proc UpDatePre(){
	for (i=0;i<NumSin+4;i=i+1) {
		AmpaCOD[i].tau_rec=Tau_rec
		AmpaCOD[i].tau_facil=Tau_facil
		AmpaCOD[i].tau_1=Tau_1
		AmpaCOD[i].U=U
		

		NMDAS[i].tau_rec=Tau_rec
		NMDAS[i].tau_facil=Tau_facil
		NMDAS[i].tau_1=Tau_1
		NMDAS[i].U=U

	}
}

proc PresynGParam(){
	Tau_rec_if=Granule[0].synG[0].tau_rec
	Tau_facil_if=Granule[0].synG[0].tau_facil
	Tau_1_if=Granule[0].synG[0].tau_1
	U_if=Granule[0].synG[0].U
	xpanel("If PRESYNAPTIC PARAMETERS")   
		xvalue("T_transition (ms)","Tau_1_if", 1,"UpDateGPre()", 0, 0 )
		xvalue("T_recovery (ms)","Tau_rec_if", 1,"UpDateGPre()", 0, 0 )
		xvalue("T_facilita (ms)","Tau_facil_if", 1,"UpDateGPre()", 0, 0 )
		xvalue("Release probability","U_if", 1,"UpDateGPre()", 0, 0 )
	xpanel()
}

proc UpDateGPre(){
	for (ifn=0;ifn<NumISin+4;ifn=ifn+1) {
		GRC_GABA[ifn].tau_rec=Tau_rec_if
		GRC_GABA[ifn].tau_facil=Tau_facil_if
		GRC_GABA[ifn].tau_1=Tau_1_if
		GRC_GABA[ifn].U=U_if
		
	}
}

// ******************************** Mossy Fiber  ************************************// 

objref grafici[8]
ngraph = 0

proc addgraph() { local ii	
	ngraph = ngraph+1
	ii = ngraph-1
	grafici[ii] = new Graph(0)
	grafici[ii].size(0,tstop,$2,$3)
	grafici[ii].view(0,0,150,48,0,48,150,48)
	grafici[ii].xaxis()
	grafici[ii].yaxis()
	grafici[ii].addvar($s1,1,0)
	grafici[ii].save_name("graphList[0].")
	graphList[0].append(grafici[ii])
	grafici[ii].exec_menu("View = plot")
	grafici[ii].flush()
}


proc MossyFiberTraces(){
	mfpanel = new VBox()
	mfpanel.intercept(1)
	xpanel("Mossy fibers traces")   
		addgraph("Mossy[0].y",0,2)
		addgraph("Mossy[1].y",0,2)
		addgraph("Mossy[2].y",0,2)
		addgraph("Mossy[3].y",0,2)
	xpanel()
	mfpanel.intercept(0)
	mfpanel.map("Mossy Fiber traces")
}

NumSin = 0
NumISin = 0

proc HomogeneousMf(){
	xpanel("MOSSY PARAMETERS")   
	xlabel("Homogeneous mossy fibers")
	InSpike=10
	InBurst=1e5
	NumSpikes=1
	StartIn=20
	EndIn=1e10
	Rumore=0
	NumSin=0
	delay=Mossy[0].delay		
	UpDateMossyO()
	xvalue("Number of synapses ","NumSin", 1,"UpDateMossyO()", 0, 0 )
	xvalue("Interspike interval (ms)","InSpike", 1,"UpDateMossyO()", 0, 0 )
	xvalue("Interburst interval (ms)","InBurst", 1,"UpDateMossyO()", 0, 0 )
	xvalue("Spikes per burst        ","NumSpikes", 1,"UpDateMossyO()", 0, 0 )
	xvalue("Begin of the Input (ms)","StartIn", 1,"UpDateMossyO()", 0, 0 )
	xvalue("End of the Input (ms)","EndIn", 1,"UpDateMossyO()", 0, 0 )
	xpanel()
}

proc HeterogeneousMF(){
	xpanel("Mossy heterogeneus")   
	xlabel("Heterogeneous mossy fibers")

	xvalue("Interspike interval (ms)","Mossy[0].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Mossy[0].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Mossy[0].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Mossy[0].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Mossy[0].end", 1,"", 0, 0 )

	xlabel("Mossy 2")
	xvalue("Interspike interval (ms)","Mossy[1].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Mossy[1].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Mossy[1].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Mossy[1].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Mossy[1].end", 1,"", 0, 0 )

	xlabel("Mossy 3")
	xvalue("Interspike interval (ms)","Mossy[2].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Mossy[2].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Mossy[2].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Mossy[2].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Mossy[2].end", 1,"", 0, 0 )

	xlabel("Mossy 4")
	xvalue("Interspike interval (ms)","Mossy[3].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Mossy[3].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Mossy[3].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Mossy[3].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Mossy[3].end", 1,"", 0, 0 )

	xpanel()
}

proc UpDateMossyO(){
	print "UpDating Mossy parameters"
	for(i=0;i<4;i=i+1) {	
		Mossy[i].fast_invl=InSpike
		Mossy[i].slow_invl=InBurst
		Mossy[i].burst_len=NumSpikes
		Mossy[i].start=StartIn
		Mossy[i].noise=Rumore
		Mossy[i].delay=delay
		if (i<NumSin) {
			Mossy[i].end=EndIn
		} else {
			Mossy[i].end=0
		}
	}
}
 

// *************Inhibitory Synaptic Fiber**************************// 

objref graffz[8]
ngraff = 0

proc addgraph() { local ix	
	ngraff = ngraff+1
	ix = ngraff-1
	graffz[ix] = new Graph(0)
	graffz[ix].size(0,tstop,$2,$3)
	graffz[ix].view(0,0,150,48,0,48,150,48)
	graffz[ix].xaxis()
	graffz[ix].yaxis()
	graffz[ix].addvar($s1,1,0)
	graffz[ix].save_name("graphList[1].")
	graphList[1].append(graffz[ix])
	graffz[ix].exec_menu("View = plot")
	graffz[ix].flush()
}


proc InhibFiberTraces(){
	ifpanel = new VBox()
	ifpanel.intercept(1)
	xpanel("Inhib fibers traces")   
		addgraph("Inhib[0].y",0,2)
		addgraph("Inhib[1].y",0,2)
		addgraph("Inhib[2].y",0,2)
		addgraph("Inhib[3].y",0,2)
	xpanel()
	ifpanel.intercept(0)
	ifpanel.map("Inhibitory synaptic Fiber traces")
}

proc HomogeneousIf(){
	xpanel("Inhib PARAMETERS")   
	xlabel("Homogeneous inhib fibers")
	IInSpike=10
	IInBurst=1e10
	INumSpikes=1
	IStartIn=24
	IEndIn=1e10
	IRumore=Inhib[0].noise	
	NumISin=0
	Idelay=Inhib[0].delay	
	UpDateInhibO()
	xvalue("Number of synapses ","NumISin", 1,"UpDateInhibO()", 0, 0 )
	xvalue("Interspike interval (ms)","IInSpike", 1,"UpDateInhibO()", 0, 0 )
	xvalue("Interburst interval (ms)","IInBurst", 1,"UpDateInhibO()", 0, 0 )
	xvalue("Spikes per burst        ","INumSpikes", 1,"UpDateInhibO()", 0, 0 )
	xvalue("Begin of the Input (ms)","IStartIn", 1,"UpDateInhibO()", 0, 0 )
	xvalue("End of the Input (ms)","IEndIn", 1,"UpDateInhibO()", 0, 0 )
	xpanel()
}

proc HeterogeneousIF(){
	xpanel("Inhib heterogeneus")   
	xlabel("Heterogeneous inhib fibers")

	xvalue("Interspike interval (ms)","Inhib[0].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Inhib[0].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Inhib[0].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Inhib[0].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Inhib[0].end", 1,"", 0, 0 )
	
	xlabel("Inhib 2")
	xvalue("Interspike interval (ms)","Inhib[1].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Inhib[1].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Inhib[1].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Inhib[1].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Inhib[1].end", 1,"", 0, 0 )
	
	xlabel("Inhib 3")
	xvalue("Interspike interval (ms)","Inhib[2].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Inhib[2].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Inhib[2].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Inhib[2].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Inhib[2].end", 1,"", 0, 0 )
	
	xlabel("Inhib 4")
	xvalue("Interspike interval (ms)","Inhib[3].fast_invl", 1,"", 0, 0 )
	xvalue("Interburst interval (ms)","Inhib[3].slow_invl", 1,"", 0, 0 )
	xvalue("Spikes per burst","Inhib[3].burst_len", 1,"", 0, 0 )
	xvalue("Begin of the Input (ms)","Inhib[3].start", 1,"", 0, 0 )
	xvalue("End of the Input (ms)","Inhib[3].end", 1,"", 0, 0 )
	
	xpanel()
}

proc UpDateInhibO(){
	print "UpDating Inhib-Synaptic parameters"
	for(kk=0;kk<4;kk=kk+1) {	
		Inhib[kk].fast_invl=IInSpike
		Inhib[kk].slow_invl=IInBurst
		Inhib[kk].burst_len=INumSpikes
		Inhib[kk].start=IStartIn
		Inhib[kk].noise=IRumore
		Inhib[kk].delay=Idelay
		if (kk<NumISin) {
			Inhib[kk].end=IEndIn
		} else {
			Inhib[kk].end=0
		}
	}
}

proc Synapses() {
		xpanel("Postsynaptic params")
		xvalue("AMPA Gmax (pS)","Ampa_G", 1,"UpdateAmpaNmda()", 0, 0 )
		xvalue("NMDA Gmax (pS)","Nmda_G", 1,"UpdateAmpaNmda()", 0, 0 )
		xvalue("GABA Gmax","Gaba_gmax",1,"UpdateGaba()",0,0)
		xpanel()
}


//Set up initials
UpDateMossyO()
UpDateInhibO()
UpdateGaba()
UpdateAmpaNmda()

Loading data, please wait...