CA1 pyramidal neurons: binding properties and the magical number 7 (Migliore et al. 2008)

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Accession:87535
NEURON files from the paper: Single neuron binding properties and the magical number 7, by M. Migliore, G. Novara, D. Tegolo, Hippocampus, in press (2008). In an extensive series of simulations with realistic morphologies and active properties, we demonstrate how n radial (oblique) dendrites of these neurons may be used to bind n inputs to generate an output signal. The results suggest a possible neural code as the most effective n-ple of dendrites that can be used for short-term memory recollection of persons, objects, or places. Our analysis predicts a straightforward physiological explanation for the observed puzzling limit of about 7 short-term memory items that can be stored by humans.
Reference:
1 . Migliore M, Novara G, Tegolo D (2008) Single neuron binding properties and the magical number 7. Hippocampus 18:1122-30 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I A; I K; I h; I Sodium;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Pattern Recognition; Activity Patterns; Dendritic Action Potentials; Coincidence Detection; Spatio-temporal Activity Patterns; Active Dendrites; Detailed Neuronal Models; Action Potentials; Synaptic Integration; Working memory; Learning; Action Selection/Decision Making;
Implementer(s): Migliore, Michele [Michele.Migliore at Yale.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; AMPA; I A; I K; I h; I Sodium;
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magical7
readme.txt
h.mod *
kadist.mod *
kaprox.mod *
kdrca1.mod *
na3n.mod *
naxn.mod *
netstims.mod *
2ap-distr-c62564AP.hoc
face.exe *
fixnseg.hoc *
geoc62564.hoc *
mosinit.hoc
Project1.exe *
sinapsi_weights.txt
                            
load_file("nrngui.hoc")
cvode_active(1)

dist=1

rel=0.3
rel1=0.3
rel2=0.3

numaxon=1
numsoma=1
numbasal=61
numapical=53
numtrunk=42
pesi = 3


double vett[pesi]

xopen("geoc62564.hoc")             // geometry file
xopen("fixnseg.hoc")           

Rm = 28000
RmDend = Rm
RmSoma = Rm
RmAx = Rm

Cm    = 1
CmSoma= Cm
CmAx  = Cm
CmDend = Cm

RaAll= 150
RaSoma=150  
RaAx = 50

Vrest = -65
dt = 0.1
gna =  .025
AXONM = 5
gkdr = 0.01
celsius = 35.0  
KMULT =  0.03
KMULTP = 0.03
ghd=0.00005

objref g, b,c, stim, outfile,vbox
objref  p, s[3], rsyn[3], nc[3], sref, blist[numtrunk]
strdef filename, dend, trunk

outfile = new File()


forsec "axon" {insert pas e_pas=Vrest g_pas = 1/RmAx Ra=RaAx cm=CmAx}
forsec "soma" {insert pas e_pas=Vrest g_pas = 1/RmSoma Ra=RaSoma cm=CmSoma}
forsec "dendrite"{insert pas e_pas=Vrest g_pas = 1/RmDend Ra=RaAll cm=CmDend}
forsec "user5" {insert pas e_pas=Vrest g_pas = 1/RmDend Ra=RaAll cm=CmDend}

access soma

freq=50
geom_nseg()
tot=0
forall {tot=tot+nseg}
distance()

maxdist=0
forsec "user5" for(x) {if (distance(x)>maxdist) {maxdist=distance(x)}}
print "total # of segments (50Hz): ",tot, "  max path distance: ", maxdist

/*****************lettura da file********************/



ropen("sinapsi_weights.txt")
for i=0, pesi-1 {
vett[i]=fscan()*1.e-3
}



/********************  fine  **********************/





if (vett[2]==8.e-3) {vett[2]=vett[2]-2.e-3}

vett[0]=(vett[0])+(20*1.e-3)

vett[1]=(vett[1])+(30*1.e-3)

vett[2]=(vett[2])+(41*1.e-3)



ropen()

tstim=1
strength = 1 /*namps*/
tstop=200



vbox = new VBox()

vbox.intercept(1)


g = new Graph()
g.size(0,tstop,-70,30)
g.addvar("soma[0].v(0.5)",1,1,2*tstop,0,2)
g.color(1)

g.label("")

g.label("Soma")

g.label(3, 3, "geoc62564", 1, 2, -1, -2, 8)



g.xaxis(1)

xpanel("")
xbutton("runm - refresh ", "runm()")
xpanel()


vbox.intercept(0)

vbox.map("geoc62564",1,530,-100,1)	



b = new VBox()
b.intercept(1)


p = new PlotShape()
p.exec_menu("Shape Plot")


p.size(30,30,0,500)

p.label(0,0,"geoc62564")
p.variable("v")
p.show(0)


b.intercept(0)
b.map("geoc62564",1100, 320, 200, 400)




apical_dendrite[21] {

print distance(rel)

		s[0] = new NetStims(rel)
		s[0].interval=0.2
		s[0].number = 1
		s[0].start=100
		s[0].noise=0
		s[0].seed(987651119)
		rsyn[0] = new Exp2Syn(rel)
		rsyn[0].tau1 = 1
		rsyn[0].tau2 = 5
		rsyn[0].e=0
		nc[0] = new NetCon(s[0],rsyn[0],0,0,vett[0])

}

apical_dendrite[28] {

print distance(rel1)

		s[1] = new NetStims(rel1)
		s[1].interval=0.2
		s[1].number = 1
		s[1].start=100
		s[1].noise=0
		s[1].seed(987651119)
		rsyn[1] = new Exp2Syn(rel1)
		rsyn[1].tau1 = 1
		rsyn[1].tau2 = 5
		rsyn[1].e=0
		nc[1] = new NetCon(s[1],rsyn[1],0,0,vett[1])

}





apical_dendrite[30] {

print distance(rel2)



		s[2] = new NetStims(rel2)
		s[2].interval=0.2
		s[2].number = 1
		s[2].start=100
		s[2].noise=0
		s[2].seed(987651119)
		rsyn[2] = new Exp2Syn(rel2)
		rsyn[2].tau1 = 1
		rsyn[2].tau2 = 5
		rsyn[2].e=0
		nc[2] = new NetCon(s[2],rsyn[2],0,0,vett[2])

}

user5[28] {
print distance(0.5)

stim= new IClamp(0.5)
stim.amp=0.59
stim.dur=tstop
stim.del=0

}

forsec "axon" {   
                insert nax gbar_nax=gna*AXONM	
                insert kdr gkdrbar_kdr=gkdr
                insert kap gkabar_kap = KMULTP
}

forsec "soma" {   
		insert hd ghdbar_hd=ghd	vhalfl_hd=-73
                insert na3  gbar_na3=gna
                insert kdr gkdrbar_kdr=gkdr
                insert kap gkabar_kap = KMULTP
}

for i=0, numbasal-1 dendrite[i] {
		insert hd ghdbar_hd=ghd vhalfl_hd=-73
                insert na3 gbar_na3=gna
                insert kdr gkdrbar_kdr=gkdr
		insert kap gkabar_kap=0
		insert kad gkabar_kad=0

		for (x,0) { xdist = distance(x)
                	ghdbar_hd(x) = ghd*(1+3*xdist/100)
                		if (xdist > 100){
					vhalfl_hd=-81
                        		gkabar_kad(x) = KMULT*(1+xdist/100)
                			} else {
					vhalfl_hd=-73
                        		gkabar_kap(x) = KMULTP*(1+xdist/100)
               				}
		}
}
                
forsec "apical_dendrite" {
		insert hd ghdbar_hd=ghd
                insert na3 gbar_na3=gna
                insert kdr gkdrbar_kdr=gkdr
		insert kap gkabar_kap=0
		insert kad gkabar_kad=0

		for (x,0) { xdist = distance(x)
                	ghdbar_hd(x) = ghd*(1+3*xdist/100)
                		if (xdist > 100){
					vhalfl_hd=-81
                        		gkabar_kad(x) = KMULT*(1+xdist/100)
                			} else {
					vhalfl_hd=-73
                        		gkabar_kap(x) = KMULTP*(1+xdist/100)
               				}
		}
}

forsec "user5" {
		insert hd ghdbar_hd=ghd
                insert na3 gbar_na3=gna 
                insert kdr gkdrbar_kdr=gkdr
		insert kap gkabar_kap=0
		insert kad gkabar_kad=0

		for (x,0) { xdist = distance(x)
                	ghdbar_hd(x) = ghd*(1+3*xdist/100)
                		if (xdist > 100){
					vhalfl_hd=-81
                        		gkabar_kad(x) = KMULT*(1+xdist/100)
                			} else {
					vhalfl_hd=-73
                        		gkabar_kap(x) = KMULTP*(1+xdist/100)
               				}
		}
}

proc init() {
	t=0
        forall {
        v=Vrest
        if (ismembrane("nax") || ismembrane("na3")) {ena=55}
        if (ismembrane("kdr") || ismembrane("kap") || ismembrane("kad")) {ek=-90}
        if (ismembrane("hd") ) {ehd_hd=-30}
	}
	finitialize(Vrest)
        fcurrent()

        forall {
	for (x) {
	if (ismembrane("na3")||ismembrane("nax")){e_pas(x)=v(x)+(ina(x)+ik(x))/g_pas(x)}
	if (ismembrane("hd")) {e_pas(x)=e_pas(x)+i_hd(x)/g_pas(x)}
		}
	}
	cvode.re_init()
	cvode.event(tstop)
	access soma
	g.begin()
}


proc advance() {
	fadvance()
	g.plot(t)
	g.flush()
	p.flush()
	doNotify()
}

proc runp() {

ropen("sinapsi_weights.txt")

for i=0, pesi-1 {

nc[i].weight = fscan()*1.e-3

}

if (nc[2].weight==8.e-3) {nc[2].weight=nc[2].weight-2.e-3}

nc[0].weight=(nc[0].weight)+(20*1.e-3)

nc[1].weight=(nc[1].weight)+(30*1.e-3)

nc[2].weight=(nc[2].weight)+(41*1.e-3)







ropen()
stdinit()
continuerun(tstop)
doNotify()


}

proc runm() {
runp(1)
}


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