Dentate gyrus network model (Tejada et al 2014)

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Accession:155568
" ... Here we adapted an existing computational model of the dentate gyrus (J Neurophysiol 93: 437-453, 2005) by replacing the reduced granule cell models with morphologically detailed models coming from (3D) reconstructions of mature cells. ... Different fractions of the mature granule cell models were replaced by morphologically reconstructed models of newborn dentate granule cells from animals with PILO-induced Status Epilepticus, which have apical dendritic alterations and spine loss, and control animals, which do not have these alterations. This complex arrangement of cells and processes allowed us to study the combined effect of mossy fiber sprouting, altered apical dendritic tree and dendritic spine loss in newborn granule cells on the excitability of the dentate gyrus model. Our simulations suggest that alterations in the apical dendritic tree and dendritic spine loss in newborn granule cells have opposing effects on the excitability of the dentate gyrus after Status Epilepticus. Apical dendritic alterations potentiate the increase of excitability provoked by mossy fiber sprouting while spine loss curtails this increase. "
References:
1 . Tejada J, Garcia-Cairasco N, Roque AC (2014) Combined role of seizure-induced dendritic morphology alterations and spine loss in newborn granule cells with mossy fiber sprouting on the hyperexcitability of a computer model of the dentate gyrus. PLoS Comput Biol 10:e1003601 [PubMed]
2 . Tejada J, Arisi GM, Garci­a-Cairasco N, Roque AC (2012) Morphological alterations in newly born dentate gyrus granule cells that emerge after status epilepticus contribute to make them less excitable. PLoS One 7:e40726-78 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Dentate gyrus;
Cell Type(s): Dentate gyrus granule cell; Dentate gyrus mossy cell; Dentate gyrus basket cell; Dentate gyrus hilar cell;
Channel(s): I L high threshold; I T low threshold; I K; I h; I K,Ca; I Calcium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Spatio-temporal Activity Patterns; Epilepsy; Neurogenesis;
Implementer(s): Tejada, Julian [julian.tejada at gmail.com];
Search NeuronDB for information about:  Dentate gyrus granule cell; I L high threshold; I T low threshold; I K; I h; I K,Ca; I Calcium; I Potassium;
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TejadaEtAl2014
readme.html
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SimCtrl.ses
                            
TITLE T-calcium channel From Migliore CA3
: T-type calcium channel


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)

	FARADAY = 96520 (coul)
	R = 8.3134 (joule/degC)
	KTOMV = .0853 (mV/degC)
}

PARAMETER {
	v (mV)
	celsius = 6.3	(degC)
	gcatbar=.003 (mho/cm2)
	cai (mM)
	cao (mM)
}


NEURON {
	SUFFIX cat
	USEION tca READ etca WRITE itca VALENCE 2
	USEION ca READ cai, cao VALENCE 2
        RANGE gcatbar,cai, itca, etca
}

STATE {
	m h 
}

ASSIGNED {
	itca (mA/cm2)
        gcat (mho/cm2)
	etca (mV)
}

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

BREAKPOINT {
	SOLVE states METHOD cnexp
	gcat = gcatbar*m*m*h
	itca = gcat*ghk(v,cai,cao)

}

DERIVATIVE states {	: exact when v held constant
	m' = (minf(v) - m)/m_tau(v)
	h' = (hinf(v) - h)/h_tau(v)
}


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 hinf(v(mV)) {
	LOCAL a,b
	TABLE FROM -150 TO 150 WITH 200
	a = 1.e-6*exp(-v/16.26)
	b = 1/(exp((-v+29.79)/10)+1)
	hinf = a/(a+b)
}

FUNCTION minf(v(mV)) {
	LOCAL a,b
	TABLE FROM -150 TO 150 WITH 200
        
	a = 0.2*(-1.0*v+19.26)/(exp((-1.0*v+19.26)/10.0)-1.0)
	b = 0.009*exp(-v/22.03)
	minf = a/(a+b)
}

FUNCTION m_tau(v(mV)) (ms) {
	LOCAL a,b
	TABLE FROM -150 TO 150 WITH 200
	a = 0.2*(-1.0*v+19.26)/(exp((-1.0*v+19.26)/10.0)-1.0)
	b = 0.009*exp(-v/22.03)
	m_tau = 1/(a+b)
}

FUNCTION h_tau(v(mV)) (ms) {
	LOCAL a,b
        TABLE FROM -150 TO 150 WITH 200
	a = 1.e-6*exp(-v/16.26)
	b = 1/(exp((-v+29.79)/10.)+1.)
	h_tau = 1/(a+b)
}

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