Hippocampus CA1 pyramidal model with Na channel exhibiting slow inactivation (Menon et al. 2009)

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Accession:222716
These NEURON simulations show the effect of prolonged inactivation of sodium channels on attenuation of trains of backpropagating action potentials (bAPs). The new sodium channel model is a Markov model derived using a state-mutating genetic algorithm, as described in the paper.
Reference:
1 . Menon V, Spruston N, Kath WL (2009) A state-mutating genetic algorithm to design ion-channel models. Proc Natl Acad Sci U S A 106:16829-34 [PubMed]
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 A; I K; I Sodium; I Na, slow inactivation;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; Ion Channel Kinetics; Markov-type model;
Implementer(s): Menon, Vilas [vilasmenon2008 at u dot northwestern dot edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; I A; I K; I Sodium; I Na, slow inactivation;
COMMENT
Synaptic current with exponential rise and decay conductance defined by
        i = g * (v - e)      i(nanoamps), g(micromhos);
        where
         g = 0 for t < onset and
         g=amp*((1-exp(-(t-onset)/tau0))-(1-exp(-(t-onset)/tau1)))
          for t > onset
ENDCOMMENT
					       
INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	POINT_PROCESS synampa
	RANGE onset, tau0, tau1, gmax, e, i
	NONSPECIFIC_CURRENT i
}
UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(umho) = (micromho)
}

PARAMETER {
	onset=0  (ms)
	tau0=0.2 (ms)
	tau1=3.0 (ms)
	gmax=0 	 (umho)
	e=0	 (mV)
	v	 (mV)
}

ASSIGNED { i (nA)  g (umho) }

LOCAL   a[2]
LOCAL   tpeak
LOCAL   adjust
LOCAL   amp

BREAKPOINT {
        g = cond(t)
	i = g*(v - e)
}

FUNCTION cond(x) {
	tpeak=tau0*tau1*log(tau0/tau1)/(tau0-tau1)
	adjust=1/((1-exp(-tpeak/tau0))-(1-exp(-tpeak/tau1)))
	amp=adjust*gmax
	if (x < onset) {
		cond = 0
	}else{
		a[0]=1-exp(-(x-onset)/tau0)
		a[1]=1-exp(-(x-onset)/tau1)
		cond = amp*(a[0]-a[1])
	}
}

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