Dentate gyrus network model (Santhakumar et al 2005)

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Accession:51781
Mossy cell loss and mossy fiber sprouting are two characteristic consequences of repeated seizures and head trauma. However, their precise contributions to the hyperexcitable state are not well understood. Because it is difficult, and frequently impossible, to independently examine using experimental techniques whether it is the loss of mossy cells or the sprouting of mossy fibers that leads to dentate hyperexcitability, we built a biophysically realistic and anatomically representative computational model of the dentate gyrus to examine this question. The 527-cell model, containing granule, mossy, basket, and hilar cells with axonal projections to the perforant-path termination zone, showed that even weak mossy fiber sprouting (10-15% of the strong sprouting observed in the pilocarpine model of epilepsy) resulted in the spread of seizure-like activity to the adjacent model hippocampal laminae after focal stimulation of the perforant path. See reference for more and details.
Reference:
1 . Santhakumar V, Aradi I, Soltesz I (2005) Role of mossy fiber sprouting and mossy cell loss in hyperexcitability: a network model of the dentate gyrus incorporating cell types and axonal topography. J Neurophysiol 93:437-53 [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 GLU 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): GabaA; AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; neuroConstruct (web link to model);
Model Concept(s): Activity Patterns; Spatio-temporal Activity Patterns; Axonal Action Potentials; Epilepsy; Synaptic Integration;
Implementer(s): Santhakumar, Vijayalakshmi [santhavi at umdnj.edu];
Search NeuronDB for information about:  Dentate gyrus granule GLU cell; GabaA; AMPA; I L high threshold; I T low threshold; I K; I h; I K,Ca; I Calcium; I Potassium;
Files displayed below are from the implementation
/
dentategyrusnet2005
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 *
mosinit.hoc *
RI10sp.hoc
testnet.hoc
                            
TITLE gskch.mod  calcium-activated potassium channel (non-voltage-dependent)

COMMENT

gsk granule

ENDCOMMENT

UNITS {
        (molar) = (1/liter)
        (mM)    = (millimolar)
	(mA)	= (milliamp)
	(mV)	= (millivolt)
}

NEURON {
	SUFFIX gskch
	USEION sk READ esk WRITE isk VALENCE 1
	USEION nca READ ncai VALENCE 2
	USEION lca READ lcai VALENCE 2
	USEION tca READ tcai VALENCE 2
	RANGE gsk, gskbar, qinf, qtau, isk
}

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

PARAMETER {
	celsius=6.3 (degC)
	v		(mV)
	dt		(ms)
	gskbar  (mho/cm2)
	esk	(mV)
	cai (mM)
	ncai (mM)
	lcai (mM)
	tcai (mM)
}

STATE { q }

ASSIGNED {
	isk (mA/cm2) gsk (mho/cm2) qinf qtau (ms) qexp
}


BREAKPOINT {          :Computes i=g*q^2*(v-esk)
	SOLVE state
        gsk = gskbar * q*q
	isk = gsk * (v-esk)
}

UNITSOFF

INITIAL {
	cai = ncai + lcai + tcai	
	rate(cai)
	q=qinf
	VERBATIM
	ncai = _ion_ncai;
	lcai = _ion_lcai;
	tcai = _ion_tcai;
	ENDVERBATIM
}


PROCEDURE state() {  :Computes state variable q at current v and dt.
	cai = ncai + lcai + tcai
	rate(cai)
	q = q + (qinf-q) * qexp
	VERBATIM
	return 0;
	ENDVERBATIM
}

LOCAL q10
PROCEDURE rate(cai) {  :Computes rate and other constants at current v.
	LOCAL alpha, beta, tinc
	q10 = 3^((celsius - 6.3)/10)
		:"q" activation system
alpha = 1.25e1 * cai * cai
beta = 0.00025 

:	alpha = 0.00246/exp((12*log10(cai)+28.48)/-4.5)
:	beta = 0.006/exp((12*log10(cai)+60.4)/35)
: alpha = 0.00246/fctrap(cai)
: beta = 0.006/fctrap(cai)
	qtau = 1 / (alpha + beta)
	qinf = alpha * qtau
	tinc = -dt*q10
	qexp = 1 - exp(tinc/qtau)*q10
}

UNITSON

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