Dentate gyrus network model (Santhakumar et al 2005)

 Download zip file   Auto-launch 
Help downloading and running models
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 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 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
                            
COMMENT
	calcium accumulation into a volume of area*depth next to the
	membrane with a decay (time constant tau) to resting level
	given by the global calcium variable cai0_ca_ion
ENDCOMMENT

NEURON {
	SUFFIX ccanl
USEION nca READ ncai, inca, enca WRITE enca, ncai VALENCE 2
USEION lca READ lcai, ilca, elca WRITE elca, lcai VALENCE 2
USEION tca READ tcai, itca, etca WRITE etca, tcai VALENCE 2
RANGE caiinf, catau, cai, ncai, lcai,tcai, eca, elca, enca, etca
}

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

INDEPENDENT {t FROM 0 TO 100 WITH 100 (ms)}

PARAMETER {
        celsius = 6.3 (degC)
	depth = 200 (nm)	: assume volume = area*depth
	catau = 9 (ms)
	caiinf = 50.e-6 (mM)	: takes precedence over cai0_ca_ion
			: Do not forget to initialize in hoc if different
			: from this default.
	cao = 2 (mM)
	ica (mA/cm2)
	inca (mA/cm2)
	ilca (mA/cm2)
	itca (mA/cm2)
	cai= 50.e-6 (mM)
}

ASSIGNED {
	enca (mV)
	elca (mV)
	etca (mV)
	eca (mV)
}

STATE {
	ncai (mM)
	lcai (mM)
	tcai (mM)
}

INITIAL {
	VERBATIM
	ncai = _ion_ncai;
	lcai = _ion_lcai;
	tcai = _ion_tcai; 
	ENDVERBATIM
	ncai=caiinf/3
	lcai=caiinf/3
	tcai=caiinf/3
	cai = caiinf	
	eca = ktf() * log(cao/caiinf)	
	enca = eca
	elca = eca
	etca = eca
}


BREAKPOINT {
	SOLVE integrate METHOD derivimplicit
	cai = ncai+lcai+tcai	
	eca = ktf() * log(cao/cai)	
	enca = eca
	elca = eca
	etca = eca
}

DERIVATIVE integrate {
ncai' = -(inca)/depth/FARADAY * (1e7) + (caiinf/3 - ncai)/catau
lcai' = -(ilca)/depth/FARADAY * (1e7) + (caiinf/3 - lcai)/catau
tcai' = -(itca)/depth/FARADAY * (1e7) + (caiinf/3 - tcai)/catau
}

FUNCTION ktf() (mV) {
	ktf = (1000)*R*(celsius +273.15)/(2*FARADAY)
} 

Loading data, please wait...