Calcium waves and mGluR-dependent synaptic plasticity in CA1 pyr. neurons (Ashhad & Narayanan 2013)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:150551
A morphologically realistic, conductance-based model equipped with kinetic schemes that govern several calcium signalling modules and pathways in CA1 pyramidal neurons
Reference:
1 . Ashhad S, Narayanan R (2013) Quantitative interactions between the A-type K+ current and inositol trisphosphate receptors regulate intraneuronal Ca2+ waves and synaptic plasticity. J Physiol 591:1645-69 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse; Channel/Receptor; Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; Ca pump;
Gap Junctions:
Receptor(s): AMPA; NMDA; mGluR; IP3;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Active Dendrites; Synaptic Plasticity; Signaling pathways; Calcium dynamics; G-protein coupled; Calcium waves;
Implementer(s): Narayanan, Rishikesh [rishi at iisc.ac.in]; Ashhad, Sufyan [soofy at mbu.iisc.ernet.in];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; AMPA; NMDA; mGluR; IP3; I Na,t; I L high threshold; I T low threshold; I A; I K; Ca pump; Glutamate;
/
AshhadNarayanan2013
Readme.html
cal4.mod
Calamp.mod
caltype.mod
camax.mod
cat.mod
ghknmda.mod
ip3dif.mod
kadist.mod *
kaprox.mod *
kdrca1.mod
mglur.mod
na3.mod
nax.mod *
Wghkampa.mod
CalciumWave.hoc
distance.hoc
Fig4F-G.hoc
Fig6C-F.hoc
mosinit.hoc
n123.hoc
n123_all.dis
n123_all.rdis
ObliquePath.hoc
oblique-paths.hoc
parameters.hoc
screenshot4F.png
screenshot4G.png
screenshot6C-F.png
                            
load_file("nrngui.hoc")
create soma[1], apical[1], basal[1]
objectvar st
objectvar sh
strdef str1

tstop = 1500
steps_per_ms = 40
ra     = 200			
rm     = 60000
c_m       = 0.75

v_init    = -65
celsius   = 30

t = 0.025

proc setpassive() {
	forall {
	  	insert pas
	  	cm = c_m 
	  	e_pas = v_init
		Ra=ra
		g_pas=1/rm
	}
}

objref Trunk

proc load_3dcell() {
	xopen("n123.hoc")
	forall { 
		soma area(0.5)
		nseg = int((L/(0.1*lambda_f(100))+.9)/2)*2 + 1  
		totcomp=totcomp+nseg
	}
	setpassive()
	access soma[0]
	Trunk = new SectionList()
	soma[0]  Trunk.append() // 13.40um from soma
	apical[0]  Trunk.append() // 13.40um from soma
	apical[4]  Trunk.append() // 46.03 
	apical[6]  Trunk.append() // 45.75
	apical[14] Trunk.append() // 52.53
	apical[15] Trunk.append() // 58.97
	apical[16] Trunk.append() // 70.89
	apical[22] Trunk.append() // 72.93
	apical[23] Trunk.append() // 74.48
	apical[25] Trunk.append() // 93.56
	apical[26] Trunk.append() // 98.55
	apical[27] Trunk.append() // 121.89
	apical[41] Trunk.append() // 144.46
	apical[42] Trunk.append() // 142.81
	apical[46] Trunk.append() // 156.96
	apical[48] Trunk.append() // 162.99
	apical[56] Trunk.append() // 179.58
	apical[58] Trunk.append() // 180.11
	apical[60] Trunk.append() // 210.33
	apical[62] Trunk.append() // 222.80
	apical[64] Trunk.append() // 233.67
	apical[65] Trunk.append() // 252.71
	apical[69] Trunk.append() // 292.06
	apical[71] Trunk.append() // 324.53
	apical[81] Trunk.append() // 346.84
	apical[83] Trunk.append() // 387.00
	apical[95] Trunk.append() // 413.05
	apical[103] Trunk.append() // 417.73
	apical[104] Trunk.append() // 423.75
}	

/*****************************************************************/

objref netlist, s, ampasyn, f1, DEND, sapamp, sampvec, sampvec
strdef  str2

somax=2.497
somay=-13.006
somaz=11.12
double distances[200]

proc compute_distances() {
	
		wopen("n123_all.rdis")
		load_3dcell()
		access soma[0]
		distance()
		
		DEND = new SectionList()
		forsec "basal" { 
			DEND.append()
		}
		forsec "apical"{
			DEND.append()
		}

		forsec Trunk {
			for(x) {
				if(x!=0){
					rdist=raddist(x)
					//rdist=distance(x)
					fprint("%s\t%f\t%f\n", secname(),x,rdist) 
					print secname(), "\t\t", x,"\t\t", rdist, "\t\t", distance(x)
				}	
			}	
		}
		wopen()
}

/*****************************************************************/

func raddist() {
	distn0=distance(0)
	distances[0]=0
	sum=0

	for i=1,n3d()-1 {
		xx=(x3d(i)-x3d(i-1))*(x3d(i)-x3d(i-1))
		yy=(y3d(i)-y3d(i-1))*(y3d(i)-y3d(i-1))
		zz=(z3d(i)-z3d(i-1))*(z3d(i)-z3d(i-1))
		sum=sum+sqrt(xx+yy+zz)
		distances[i]=sum
	}

	xval=$1

// Amoung the various pt3d's find which one matches the distance of
// current x closely

	distn=distance(xval)
	match=distn-distn0
	matchptdist=100000
	for i=0,n3d()-1 {		
		matptdist=(match-distances[i])*(match-distances[i])
		if(matchptdist>matptdist){
			matchptdist=matptdist
			matchi=i
		}
	}

	//print "Match for ", x, " is ", matchi, " XDIST ", match, " MATCH ", distances[matchi], " ERROR ", sqrt(matchptdist)

			
// Find the distance of the closely matched point to the somatic
// centroid and use that as the distance for this BPAP measurement			

	xx=(x3d(matchi)-somax)*(x3d(matchi)-somax)
	yy=(y3d(matchi)-somay)*(y3d(matchi)-somay)
	zz=(z3d(matchi)-somaz)*(z3d(matchi)-somaz)
	return sqrt(xx+yy+zz)
}

/*****************************************************************/
proc update_init(){
    finitialize(v_init)
    fcurrent()
}	
 
/*****************************************************************/
// CA3b4: Centroid of Soma is: -2.68892  13.0872  1.07191

/*

proc saveradialamps(){local count, distn, nlcount, distn0, sum, match,\
						matchptdist, matchptdist, raddist

	wopen($s1)
	count=0
	nlcount=0

	forall {
		distn0=distance(0)
		distances[0]=0
		sum=0

		for i=1,n3d()-1 {
			xx=(x3d(i)-x3d(i-1))*(x3d(i)-x3d(i-1))
			yy=(y3d(i)-y3d(i-1))*(y3d(i)-y3d(i-1))
			zz=(z3d(i)-z3d(i-1))*(z3d(i)-z3d(i-1))
			sum=sum+sqrt(xx+yy+zz)
			distances[i]=sum
		}

		for (x) {

// Amoung the various pt3d's find which one matches the distance of
// current x closely

			distn=distance(x)
			match=distn-distn0
			matchptdist=100000
			for i=0,n3d()-1 {		
				matptdist=(match-distances[i])*(match-distances[i])
				if(matchptdist>matptdist){
					matchptdist=matptdist
					matchi=i
				}
			}

			//print "Match for ", x, " is ", matchi, " XDIST ", match, " MATCH ", distances[matchi], " ERROR ", sqrt(matchptdist)

			
// Find the distance of the closely matched point to the somatic
// centroid and use that as the distance for this BPAP measurement			

			xx=(x3d(matchi)-somax)*(x3d(matchi)-somax)
			yy=(y3d(matchi)-somay)*(y3d(matchi)-somay)
			zz=(z3d(matchi)-somaz)*(z3d(matchi)-somaz)
			raddist=sqrt(xx+yy+zz)

			if (ampvec[count].size()>0){
				fprint("%s\t%f\t%f\n", secname(), raddist, \
						ampvec[count].x[0]-v_init)
			} else {
				nlcount=nlcount+1
				fprint("%s\t%f\t0\n", secname(), raddist)
			}	
			count=count+1
		}	
	}
	print "Nilcount = ", nlcount
	wopen()
}	

*/

compute_distances()

Loading data, please wait...