Medial vestibular neuron models (Quadroni and Knopfel 1994)

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Accession:53876
The structure and the parameters of the model cells were chosen to reproduce the responses of type A and type B MVNns as described in electrophysiological recordings. The emergence of oscillatory firing under these two specific experimental conditions is consistent with electrophysiological recordings not used during construction of the model. We, therefore, suggest that these models have a high predictive value.
Reference:
1 . Quadroni R, Knöpfel T (1994) Compartmental models of type A and type B guinea pig medial vestibular neurons. J Neurophysiol 72:1911-24 [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:
Cell Type(s): Vestibular neuron;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h;
Gap Junctions:
Receptor(s): NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Action Potentials; Calcium dynamics;
Implementer(s): Morse, Tom [Tom.Morse at Yale.edu];
Search NeuronDB for information about:  NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h;
COMMENT
This file, nmda.mod, implements the NMDA-type glutamate receptors
current from Quadroni and Knopfel 1994 equations (9)
This mechanism is applied uniformly to all dendrites in the above paper.
ENDCOMMENT

NEURON {
	SUFFIX nmda
	NONSPECIFIC_CURRENT i
	RANGE i, Erev, gbar
}

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

PARAMETER {
	gbar = 2570e-6	(S/cm2) < 0, 1e9 >
	Erev = 0 (mV)
	mg_o = 2 (mM)	: Magnesium concentration outside cell
}

ASSIGNED {
	i (mA/cm2)
	v (mV)
	g (S/cm2)
	ninf
	tau_n (ms)
}

STATE {	n }

BREAKPOINT {
	SOLVE states METHOD cnexp
	g = gbar * n
	i = g * (v - Erev)
}

INITIAL {
	: assume that v has been constant for a long time
	n = alphan(v)/(alphan(v) + betan(v))
}

DERIVATIVE states {
	rates(v)
	n' = (ninf - n)/tau_n
}

FUNCTION alphan(Vm (mV)) (/ms) {
	UNITSOFF
	alphan = 3.0 * exp(0.035 * (Vm + 10.0))
	UNITSON
}

FUNCTION betan(Vm (mV)) (/ms) {
	UNITSOFF
	betan = mg_o * exp(-0.035 * (Vm + 10.0))
	UNITSON
}

FUNCTION taun(Vm (mV)) (/ms) {
	UNITSOFF
	taun = 1.0 / (alphan(Vm) + betan(Vm))
	UNITSON
}

PROCEDURE rates(Vm(mV)) {
	tau_n = taun(Vm)
	ninf = alphan(Vm) * tau_n      : change back to a/(a+b) if use taun_min
}

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