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 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
                            
TITLE ichan2.mod  
 
COMMENT
konduktivitas valtozas hatasa- somaban 
ENDCOMMENT
 
UNITS {
        (mA) =(milliamp)
        (mV) =(millivolt)
        (uF) = (microfarad)
	(molar) = (1/liter)
	(nA) = (nanoamp)
	(mM) = (millimolar)
	(um) = (micron)
	FARADAY = 96520 (coul)
	R = 8.3134	(joule/degC)
}
 
? interface 
NEURON { 
SUFFIX ichan2 
USEION nat READ enat WRITE inat VALENCE 1
USEION kf READ ekf WRITE ikf  VALENCE 1
USEION ks READ eks WRITE iks  VALENCE 1
NONSPECIFIC_CURRENT il 
RANGE  gnat, gkf, gks
RANGE gnatbar, gkfbar, gksbar
RANGE gl, el
RANGE minf, mtau, hinf, htau, nfinf, nftau, inat, ikf, nsinf, nstau, iks
}
 
INDEPENDENT {t FROM 0 TO 100 WITH 100 (ms)}
 
PARAMETER {
        v (mV) 
        celsius = 6.3 (degC)
        dt (ms) 
        enat  (mV)
	gnatbar (mho/cm2)   
        ekf  (mV)
	gkfbar (mho/cm2)
        eks  (mV)
	gksbar (mho/cm2)
	gl (mho/cm2)    
 	el (mV)
}
 
STATE {
	m h nf ns
}
 
ASSIGNED {
         
        gnat (mho/cm2) 
        gkf (mho/cm2)
        gks (mho/cm2)

        inat (mA/cm2)
        ikf (mA/cm2)
        iks (mA/cm2)


	il (mA/cm2)

	minf hinf nfinf nsinf
 	mtau (ms) htau (ms) nftau (ms) nstau (ms)
	mexp hexp nfexp nsexp
} 

? currents
BREAKPOINT {
	SOLVE states
        gnat = gnatbar*m*m*m*h  
        inat = gnat*(v - enat)
        gkf = gkfbar*nf*nf*nf*nf
        ikf = gkf*(v-ekf)
        gks = gksbar*ns*ns*ns*ns
        iks = gks*(v-eks)

	il = gl*(v-el)
}
 
UNITSOFF
 
INITIAL {
	trates(v)
	
	m = minf
	h = hinf
      nf = nfinf
      ns = nsinf
	
	VERBATIM
	return 0;
	ENDVERBATIM
}

? states
PROCEDURE states() {	:Computes state variables m, h, and n 
        trates(v)	:      at the current v and dt.
        m = m + mexp*(minf-m)
        h = h + hexp*(hinf-h)
        nf = nf + nfexp*(nfinf-nf)
        ns = ns + nsexp*(nsinf-ns)
        VERBATIM
        return 0;
        ENDVERBATIM
}
 
LOCAL q10

? rates
PROCEDURE rates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
        LOCAL  alpha, beta, sum
       q10 = 3^((celsius - 6.3)/10)
                :"m" sodium activation system - act and inact cross at -40
	alpha = -0.3*vtrap((v+60-17),-5)
	beta = 0.3*vtrap((v+60-45),5)
	sum = alpha+beta        
	mtau = 1/sum      minf = alpha/sum
                :"h" sodium inactivation system
	alpha = 0.23/exp((v+60+5)/20)
	beta = 3.33/(1+exp((v+60-47.5)/-10))
	sum = alpha+beta
	htau = 1/sum 
        hinf = alpha/sum 
             :"ns" sKDR activation system
        alpha = -0.028*vtrap((v+65-35),-6)
	beta = 0.1056/exp((v+65-10)/40)
	sum = alpha+beta        
	nstau = 1/sum      nsinf = alpha/sum
            :"nf" fKDR activation system
        alpha = -0.07*vtrap((v+65-47),-6)
	beta = 0.264/exp((v+65-22)/40)
	sum = alpha+beta        
	nftau = 1/sum      nfinf = alpha/sum
	
}
 
PROCEDURE trates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
	LOCAL tinc
        TABLE minf, mexp, hinf, hexp, nfinf, nfexp, nsinf, nsexp, mtau, htau, nftau, nstau
	DEPEND dt, celsius FROM -100 TO 100 WITH 200
                           
	rates(v)	: not consistently executed from here if usetable_hh == 1
		: so don't expect the tau values to be tracking along with
		: the inf values in hoc

	       tinc = -dt * q10
        mexp = 1 - exp(tinc/mtau)
        hexp = 1 - exp(tinc/htau)
	nfexp = 1 - exp(tinc/nftau)
	nsexp = 1 - exp(tinc/nstau)
}
 
FUNCTION vtrap(x,y) {  :Traps for 0 in denominator of rate eqns.
        if (fabs(x/y) < 1e-6) {
                vtrap = y*(1 - x/y/2)
        }else{  
                vtrap = x/(exp(x/y) - 1)
        }
}
 
UNITSON


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