CA1 pyramidal neuron to study INaP properties and repetitive firing (Uebachs et al. 2010)

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Accession:125152
A model of a CA1 pyramidal neuron containing a biophysically realistic morphology and 15 distributed voltage and Ca2+-dependent conductances. Repetitive firing is modulated by maximal conductance and the voltage dependence of the persistent Na+ current (INaP).
Reference:
1 . Uebachs M, Opitz T, Royeck M, Dickhof G, Horstmann MT, Isom LL, Beck H (2010) Efficacy loss of the anticonvulsant carbamazepine in mice lacking sodium channel beta subunits via paradoxical effects on persistent sodium currents. J Neurosci 30:8489-501 [PubMed]
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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 p,q; I A; I K,leak; I M; I K,Ca; I CAN; I Calcium; ATP-senstive potassium current;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Epilepsy;
Implementer(s): Horstmann, Marie-Therese [mhorstma at uni-bonn.de];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; I Na,p; I Na,t; I p,q; I A; I K,leak; I M; I K,Ca; I CAN; I Calcium; ATP-senstive potassium current;
TITLE nap
:persisten sodium current with inactivation

NEURON {
	SUFFIX napIn
	USEION na READ ena WRITE ina
	RANGE  gbar, thegna, htau
	GLOBAL minf, mtau, hinf
}

PARAMETER {
	gbar = .0052085   	(mho/cm2)
    htau = 15	(ms)
	
	eNa = 55 	(mV)		
	ena		(mV)            
	celsius (degC)
	v 		(mV)
}


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(pS) = (picosiemens)
	(um) = (micron)
} 

ASSIGNED {
	ina 		(mA/cm2)
	thegna		(mho/cm2)
	minf 		hinf 		
	mtau (ms)		
}
 

STATE { m h}

: hier eigener Befehl
UNITSOFF

BREAKPOINT {
        SOLVE states METHOD cnexp
    		
	trates(v)	
	thegna =gbar*m*h 
	ina = thegna * (v - eNa)
	} 

INITIAL {
	trates(v)
	m=minf  
	h=hinf
}

DERIVATIVE states {   
    trates(v)      
	m' = (minf-m)/mtau
    h' = (hinf-h)/htau

}

PROCEDURE trates(vm) {  
    mtau = 1
	minf = 1/(1+exp(-(v+52.3)/6.8))
    hinf = 1/(1+exp((v+48)/10.0))
	
}



UNITSON