Dentate gyrus network model pattern separation and granule cell scaling in epilepsy (Yim et al 2015)

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Accession:185355
The dentate gyrus (DG) is thought to enable efficient hippocampal memory acquisition via pattern separation. With patterns defined as spatiotemporally distributed action potential sequences, the principal DG output neurons (granule cells, GCs), presumably sparsen and separate similar input patterns from the perforant path (PP). In electrophysiological experiments, we have demonstrated that during temporal lobe epilepsy (TLE), GCs downscale their excitability by transcriptional upregulation of ‘leak’ channels. Here we studied whether this cell type-specific intrinsic plasticity is in a position to homeostatically adjust DG network function. We modified an established conductance-based computer model of the DG network such that it realizes a spatiotemporal pattern separation task, and quantified its performance with and without the experimentally constrained leaky GC phenotype. ...
Reference:
1 . Yim MY, Hanuschkin A, Wolfart J (2015) Intrinsic rescaling of granule cells restores pattern separation ability of a dentate gyrus network model during epileptic hyperexcitability. Hippocampus 25:297-308 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Dentate gyrus;
Cell Type(s): Dentate gyrus granule GLU cell; Dentate gyrus mossy cell; Dentate gyrus basket cell; Dentate gyrus hilar cell; Dentate gyrus MOPP cell;
Channel(s): I Chloride; I K,leak; I Cl, leak; Kir; Kir2 leak;
Gap Junctions:
Receptor(s): GabaA; AMPA;
Gene(s): IRK; Kir2.1 KCNJ2; Kir2.2 KCNJ12; Kir2.3 KCNJ4; Kir2.4 KCNJ14;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Spatio-temporal Activity Patterns; Intrinsic plasticity; Pathophysiology; Epilepsy; Homeostasis; Pattern Separation;
Implementer(s): Yim, Man Yi [manyi.yim at googlemail.com]; Hanuschkin, Alexander ; Wolfart, Jakob ;
Search NeuronDB for information about:  Dentate gyrus granule GLU cell; GabaA; AMPA; I Chloride; I K,leak; I Cl, leak; Kir; Kir2 leak; Gaba; Glutamate;
//**********************       HIPP CELL         ****************************************
// HIPP CELL template

// extracted from
// Dentate gyrus network model 
// Santhakumar V, Aradi I, Soltesz I (2005) J Neurophysiol 93:437-53 
// https://senselab.med.yale.edu/ModelDB/showModel.cshtml?model=51781&file=\dentategyrusnet2005\DG500_M7.hoc

// ModelDB file along with publication:
// Yim MY, Hanuschkin A, Wolfart J (2015) Hippocampus 25:297-308.
// http://onlinelibrary.wiley.com/doi/10.1002/hipo.22373/abstract

// modified by
// Man Yi Yim / 2015
// Alexander Hanuschkin / 2011

objref Hcell[nhcell]

begintemplate HIPPCell

ndend1=3
ndend2=3
ndend3=3
ndend4=3
public  pre_list, connect_pre, subsets, is_art, is_connected
public vbc2gc, vmc2gc, vhc2gc, vgc2bc, vbc2bc, vmc2bc, vhc2bc, vgc2mc, vbc2mc, vmc2mc, vhc2mc, vgc2hc, vmc2hc
public soma, hcdend1, hcdend2, hcdend3, hcdend4
create soma, hcdend1[ndend1], hcdend2[ndend2], hcdend3[ndend3], hcdend4[ndend4]
public all, pdend, ddend
objref syn, pre_list


objref syn
proc init() {
	pre_list = new List()
	subsets()
	temp()
	synapse()
}

objref all, pdend, ddend

proc subsets() { local i
	objref all, pdend, ddend
	all = new SectionList()
		soma all.append()
		for i=0, 2 hcdend1 [i] all.append()
		for i=0, 2 hcdend2 [i] all.append()
		for i=0, 2 hcdend3 [i] all.append()
		for i=0, 2 hcdend4 [i] all.append()

	pdend  = new SectionList()
		hcdend1 [0] pdend.append()
		hcdend2 [0] pdend.append()
		hcdend3 [0] pdend.append()
		hcdend4 [0] pdend.append()

	ddend  = new SectionList()
		for i=1, 2 hcdend1 [i] ddend.append()
		for i=1, 2 hcdend2 [i] ddend.append()
		for i=1, 2 hcdend3 [i] ddend.append()
		for i=1, 2 hcdend4 [i] ddend.append()
}

proc temp() {

	soma {nseg=1 L=20 diam=10} 
		
	hcdend1 [0] {nseg=1 L=75 diam=3}
	hcdend1 [1] {nseg=1 L=75 diam=2}
	hcdend1 [2] {nseg=1 L=75 diam=1}

	hcdend2 [0] {nseg=1 L=75 diam=3}
	hcdend2 [1] {nseg=1 L=75 diam=2}
	hcdend2 [2] {nseg=1 L=75 diam=1}
 		 
	hcdend3 [0] {nseg=1 L=50 diam=3}
	hcdend3 [1] {nseg=1 L=50 diam=2}
	hcdend3 [2] {nseg=1 L=50 diam=1}
	
	hcdend4 [0] {nseg=1 L=50 diam=3}
	hcdend4 [1] {nseg=1 L=50 diam=2}
	hcdend4 [2] {nseg=1 L=50 diam=1}	

    
	forall {
		insert ccanl
	catau_ccanl = 10
	caiinf_ccanl = 5.e-6
		insert ka
	gkabar_ka=0.0008
		insert nca  
	gncabar_nca=0.0  
		insert lca
	glcabar_lca=0.0015
		insert sk
	gskbar_sk=0.003
		insert bk
	gkbar_bk=0.003
		insert ih 
	ghyfbar_ih=0.000015
	ghysbar_ih=0.000015
	}

	soma {insert ichan2  
	gnatbar_ichan2=0.2
	gkfbar_ichan2=0.006  
	gl_ichan2 = 0.000036
	cm=1.1} 

	forsec pdend {insert ichan2
	gnatbar_ichan2=0.2  
	gkfbar_ichan2=0.006
	gl_ichan2 = 0.000036
	cm=1.1}
		
	forsec ddend {insert ichan2
	gnatbar_ichan2=0.0
	gkfbar_ichan2=0.00
	gl_ichan2 = 0.000036
	cm=1.1}

	connect hcdend1[0](0), soma(1)
	connect hcdend2[0](0), soma(1)
	connect hcdend3[0](0), soma(0)
	connect hcdend4[0](0), soma(0)
	for i=1,2 {connect hcdend1[i](0), hcdend1[i-1](1)}
	for i=1,2 {connect hcdend2[i](0), hcdend2[i-1](1)}
	for i=1,2 {connect hcdend3[i](0), hcdend3[i-1](1)}
	for i=1,2 {connect hcdend4[i](0), hcdend4[i-1](1)}

	forall {Ra=100}
	forall {
        	ena 		= 	50        	// ena was unified from enat=55 (BC, HIPP, MC) and enat=45 (GC) in Santhakumar et al. (2005) <ah>
                ek		=	-90          	// simplified ekf=eks=ek=esk; note the eK was erroneously reported as -105mV in the Yim et al. 2015 <ah>
                el_ichan2 	=	-70.45
		ehyf		=	-40
		ehys		=	-40
                cao_ccanl	=	2 }
		}

// Defining synapses on to HIPP cells

	objref syn  
	proc synapse() {

	hcdend1 [0] syn = new Exp2Syn(0.5)	//GC(AMPA) syn to prox dend similar to GC>BC
	syn.tau1 = .3	syn.tau2 = .6	syn.e = 0
	pre_list.append(syn)

	hcdend2 [0] syn = new Exp2Syn(0.5)	//GC(AMPA) syn to prox dend similar to GC>BC
	syn.tau1 = .3	syn.tau2 = .6	syn.e = 0
	pre_list.append(syn)

	hcdend3 [0] syn = new Exp2Syn(0.5)	//GC(AMPA) syn to prox dend similar to GC>BC
	syn.tau1 = .3 syn.tau2 = .6	syn.e = 0
	pre_list.append(syn)

	hcdend4 [0] syn = new Exp2Syn(0.5)	//GC(AMPA) syn to prox dend similar to GC>BC
	syn.tau1 = .3	syn.tau2 = .6	syn.e = 0
	pre_list.append(syn)

	hcdend1 [1] syn = new Exp2Syn(0.5)	//MC(AMPA) syn to mid dend similar to CA3>int Aaron
	syn.tau1 = .9	syn.tau2 = 3.6	syn.e = 0 //*** Assumed data at physio temp
	pre_list.append(syn)

	hcdend2 [1] syn = new Exp2Syn(0.5)	//MC(AMPA) syn to mid dend similar to CA3>int Aaron
	syn.tau1 = 0.9	syn.tau2 = 3.6	syn.e = 0 //*** Assumed data at physio temp
	pre_list.append(syn)

	hcdend3 [1] syn = new Exp2Syn(0.5)	//MC(AMPA) syn to mid dend similar to CA3>int Aaron
	syn.tau1 = 0.9	syn.tau2 = 3.6	syn.e = 0  //*** Assumed data at physio temp
	pre_list.append(syn)

	hcdend4 [1] syn = new Exp2Syn(0.5)	//MC(AMPA) syn to mid dend similar to CA3>int Aaron
	syn.tau1 = 0.9		syn.tau2 = 3.6 	syn.e = 0  //*** Assumed data at physio temp
	pre_list.append(syn)

// Total of 12 synapses 	0-3 PP; 	4-7 GC; 	8-11 MC	
	}

	proc connect_pre() {  
	soma $o2 = new NetCon (&v(1), $o1)
	}

func is_art()  { return 0 }

endtemplate HIPPCell

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