Parallel network simulations with NEURON (Migliore et al 2006)

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Accession:64229
The NEURON simulation environment has been extended to support parallel network simulations. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters.
Reference:
1 . Migliore M, Cannia C, Lytton WW, Markram H, Hines ML (2006) Parallel Network Simulations with NEURON. J Comp Neurosci 21:110-119 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu];
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netmod
pardentategyrus
readme.html *
bgka.mod *
CaBK.mod *
ccanl.mod *
Gfluct2.mod *
gskch.mod *
hyperde3.mod *
ichan2.mod *
LcaMig.mod *
nca.mod *
tca.mod *
DG500_M7.hoc *
dgnetactivity.jpg *
dgnettraces.jpg *
init.hoc
initorig.hoc *
M2I10sp.txt
modstat *
mosinit.hoc *
parRI10sp.hoc
perfrun.hoc
RI10sp.hoc
test1.sh *
time *
                            
TITLE l-calcium channel
: l-type calcium channel


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(molar) = (1/liter)
	(mM) = (millimolar)
	FARADAY = 96520 (coul)
	R = 8.3134 (joule/degC)
	KTOMV = .0853 (mV/degC)
}

PARAMETER {
	v (mV)
	celsius 	(degC)
	glcabar		 (mho/cm2)
	ki=.001 (mM)
	cai (mM)
	cao (mM)
        tfa=1
}


NEURON {
	SUFFIX lca
	USEION lca READ elca WRITE ilca VALENCE 2
	USEION ca READ cai, cao VALENCE 2 
        RANGE glcabar, cai, ilca, elca
        GLOBAL minf,matu
}

STATE {
	m
}

ASSIGNED {
	ilca (mA/cm2)
        glca (mho/cm2)
        minf
        matu   (ms)
	elca (mV)   

}

INITIAL {
	rate(v)
	m = minf
	VERBATIM
	cai=_ion_cai;
	ENDVERBATIM
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	glca = glcabar*m*m*h2(cai)
	ilca = glca*ghk(v,cai,cao)

}

FUNCTION h2(cai(mM)) {
	h2 = ki/(ki+cai)
}


FUNCTION ghk(v(mV), ci(mM), co(mM)) (mV) {
        LOCAL nu,f

        f = KTF(celsius)/2
        nu = v/f
        ghk=-f*(1. - (ci/co)*exp(nu))*efun(nu)
}

FUNCTION KTF(celsius (DegC)) (mV) {
        KTF = ((25./293.15)*(celsius + 273.15))
}


FUNCTION efun(z) {
	if (fabs(z) < 1e-4) {
		efun = 1 - z/2
	}else{
		efun = z/(exp(z) - 1)
	}
}

FUNCTION alp(v(mV)) (1/ms) {
	TABLE FROM -150 TO 150 WITH 200
	alp = 15.69*(-1.0*v+81.5)/(exp((-1.0*v+81.5)/10.0)-1.0)
}

FUNCTION bet(v(mV)) (1/ms) {
	TABLE FROM -150 TO 150 WITH 200
	bet = 0.29*exp(-v/10.86)
}

DERIVATIVE state {  
        rate(v)
        m' = (minf - m)/matu
}

PROCEDURE rate(v (mV)) { :callable from hoc
        LOCAL a
        a = alp(v)
        matu = 1/(tfa*(a + bet(v)))
        minf = tfa*a*matu
}
 



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