Ca3 pyramidal neuron: membrane response near rest (Hemond et al. 2009)

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Accession:118098
In this paper, the model was used to show how the temporal summation of excitatory inputs in CA3 pyramidal neurons was affected by the presence of Ih in the dendrites in a frequency- and distance-dependent fashion.
Reference:
1 . Hemond P, Migliore M, Ascoli GA, Jaffe DB (2009) The membrane response of hippocampal CA3b pyramidal neurons near rest: Heterogeneity of passive properties and the contribution of hyperpolarization-activated currents. Neuroscience 160:359-70 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA3 pyramidal cell;
Channel(s): I h;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Synaptic Integration;
Implementer(s): Migliore, Michele [Michele.Migliore at Yale.edu];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal cell; AMPA; I h; Glutamate;
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ca3-summ
readme.txt
distr.mod *
hca3.mod
fig-8b.hoc
fixnseg.hoc *
geo-cell1zr.hoc *
mosinit.hoc
                            
load_file("nrngui.hoc")
cvode_active(1)

Vrest = -65
dt = 0.05
celsius = 34.0
freq=50

Rm = 41358
Cm    = 0.85
RaAll= 634
ghd=0.0001
ghdd=0	
ehd=-30

tstop=200

xopen("geo-cell1zr.hoc")
xopen("fixnseg.hoc")           

objref s, nc, syn, pd, ps, psn, pdn

pd = new Vector()
ps = new Vector()
psn = new Vector()
pdn = new Vector()

access soma

soma {
	s = new NetStim(.5)
	s.start=5
	s.interval=1000
	s.number=5

	syn = new Exp2Syn(.5)
	syn.tau1=.4
	syn.tau2=5
	syn.e=0
}

nc = new NetCon(s, syn, 0, 0, 0.05e-3)

forall { 
	insert pas
	insert ds
	insert hd ehd_hd=ehd ghdbar_hd=ghdd

	e_pas=Vrest 
	g_pas = 1/Rm 
	Ra=RaAll 
	cm=Cm
}

	geom_nseg()
	tot=0
	forall {tot=tot+nseg}

	access soma
	distance()

proc init() {
	finitialize(Vrest)
        fcurrent()
        forall for (z,0) {
		ghdbar_hd(z)=ghdd
		e_pas(z)=v(z)+i_hd(z)/g_pas
	}
	cvode.re_init()
}

proc runl() {
ff=50 
if (flag>0) {ghdd=ghd} else {ghdd=0}
print " running with Ih=",ghdd
for (mind=0; mind<650; mind=mind+100) {
	pd.resize(0)
	ps.resize(0)
	psn.resize(0)
	forsec "apical" for(gg,0) {if (distance(gg)>mind && distance(gg)<mind+100) {
	syn.loc(gg)
	s.interval=1000
	run()
	ref=soma.vmax_ds(.5)-Vrest
	refd=vmax_ds(gg)-Vrest
	s.interval=1000/ff
	run()
	pd.append(vmax_ds(gg)-Vrest)
	pdn.append((vmax_ds(gg)-Vrest)/refd)
	ps.append(soma.vmax_ds(gg)-Vrest)
	psn.append((soma.vmax_ds(gg)-Vrest)/ref)
	}
	}
	print " avr soma summ ", psn.mean()," +/- ", psn.stderr(), " at ", mind+50, "um"  
}
}

flag=0
xpanel(" ")
xbutton(" run ", "runl()") 
xcheckbox(" with Ih ",&flag)
xpanel()

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