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Modelling reduced excitability in aged CA1 neurons as a Ca-dependent process (Markaki et al. 2005)

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Accession:119266
"We use a multi-compartmental model of a CA1 pyramidal cell to study changes in hippocampal excitability that result from aging-induced alterations in calcium-dependent membrane mechanisms. The model incorporates N- and L-type calcium channels which are respectively coupled to fast and slow afterhyperpolarization potassium channels. Model parameters are calibrated using physiological data. Computer simulations reproduce the decreased excitability of aged CA1 cells, which results from increased internal calcium accumulation, subsequently larger postburst slow afterhyperpolarization, and enhanced spike frequency adaptation. We find that aging-induced alterations in CA1 excitability can be modelled with simple coupling mechanisms that selectively link specific types of calcium channels to specific calcium-dependent potassium channels."
Reference:
1 . Markaki M, Orphanoudakis S, Poirazi P (2005) Modelling reduced excitability in aged CA1 neurons as a calcium-dependent process Neurocomputing 65-66:305-314
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I N; I A; I K; I M; I K,Ca; I R;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Aging/Alzheimer`s;
Implementer(s):
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; I Na,p; I Na,t; I L high threshold; I N; I A; I K; I M; I K,Ca; I R;
TITLE HH channel that includes both a sodium and a delayed rectifier channel
: and accounts for sodium conductance attenuation
: Bartlett Mel-modified Hodgkin - Huxley conductances (after Ojvind et al.)
: Terrence Brannon-added attenuation 
: Yiota Poirazi-modified Kdr and Na threshold and time constants
: to make it more stable, 2000, poirazi@LNC.usc.edu
: Used in all BUT somatic and axon sections. The spike threshold is about -50 mV
:
: Modified to use CVode --Carl Gold 08/12/03
:  Updated by Maria Markaki  12/05/03

NEURON {
	SUFFIX hha2
	USEION na READ ena WRITE ina 
	USEION k READ ek WRITE ik
	NONSPECIFIC_CURRENT il
	RANGE gnabar, gkbar, gl, el,ik,ina
	RANGE ar2, vhalfs
	GLOBAL inf, tau, taumin
}

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


PARAMETER {   : parameters that can be entered when function is called in cell-setup
        a0r = 0.0003 (/ms)
        b0r = 0.0003 (/ms)
       : a0r = 0.0003 (ms)
        :b0r = 0.0003 (ms)
        zetar = 12    
	zetas = 12   
        gmr = 0.2   
	ar2 = 1.0               :initialized parameter for location-dependent
                                :Na-conductance attenuation, "s", (ar=1 -> zero attenuation)
:	taumin = 3   (ms)       :min activation time for "s" attenuation system
	taumin = 10   (ms)       : smax=10		(ms)
        vvs  = 2     (mV)       :slope for "s" attenuation system
        vhalfr = -60 (mV)       :half potential for "s" attenuation system
        vvh=-58		(mV) 
        gnabar = 0   (mho/cm2)  :initialized conductances
	gkbar = 0    (mho/cm2)  :actual values set in hoc code
	gl = 0       (mho/cm2)  : keep this to zero if using the NEURON pas mechanism
	el = -70.0   (mV)       :steady state 

}


ASSIGNED {
	celsius      (degC)
	v            (mV)
	ena          (mV)       :Na reversal potential (also reset in
	ek           (mV)       :K reversal potential  cell-setup.hoc)
	ina          (mA/cm2)
	ik           (mA/cm2)
	il           (mA/cm2)
	inf[4]
	tau[4]	     (ms)
}

STATE {
	m 
	h 
	n 
	s
}

INITIAL {                       : initialize the following parameter using states()
	rates(v,ar2)
	m = inf[0]
	h = inf[1]
	n = inf[2]
	s = inf[3]
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	ina = gnabar*m*m*h*s*(v - ena) :Sodium current
	ik = gkbar*n*n*(v - ek)        :Potassium current
	il = gl*(v - el)               :leak current
}


DERIVATIVE states {
	rates(v,ar2)
	m' = (inf[0]-m)/tau[0]
	h' = (inf[1]-h)/tau[1]
	n' = (inf[2]-n)/tau[2]
	s' = (inf[3]-s)/tau[3]
}

PROCEDURE rates(v(mV),a2) {
	LOCAL tmp, c
	FROM i=0 TO 2 {
		tau[i] = vartau(v,i)
		inf[i] = varss(v,i)
	}
	tau[3] = betr(v)/(a0r*(1+alpr(v))) 
	if (tau[3]<taumin) {tau[3]=taumin} :s activation tau
	c = alpv(v)
	inf[3] = c+a2*(1-c) 
}


FUNCTION varss(v(mV), i) { :steady state values
	if (i==0) {
		varss = 1 / (1 + exp((v + 44)/(-3(mV)))) :Na activation
	}
	else if (i==1) {
		varss = 1 / (1 + exp((v + 49)/(3.5(mV))))  :Na inactivation
	}
	else if (i==2) {	
		varss = 1 / (1 + exp((v + 46.3)/(-3(mV)))) :K activation

	}
}


FUNCTION alpv(v(mV)) {
         alpv = 1/(1+exp((v-vvh)/vvs))
}

FUNCTION alpr(v(mV)) {       :used in "s" activation system tau
UNITSOFF
  alpr = exp(1.e-3*zetar*(v-vhalfr)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}

FUNCTION betr(v(mV)) {       :used in "s" activation system tau
UNITSOFF
  betr = exp(1.e-3*zetar*gmr*(v-vhalfr)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}

FUNCTION vartau(v(mV), i) (ms){ :estimate tau values
	LOCAL tmp
	if (i==0) {
	   vartau = 0.05(ms)      :Na activation tau
	}
	else if (i==1) {
           vartau = 1(ms)       :Na inactivation tau
        }
	else if (i==2) {
            vartau = 3.5(ms)      :K activation tau
       	}: else {
	  :   tmp =1* betr(v)/(a0r+b0r*alpr(v)) 
	   :  if (tmp<taumin) {tmp=taumin}
	 :    vartau = tmp      :s activation tau
       :}
}	
















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