Sympathetic Preganglionic Neurone (Briant et al. 2014)

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Accession:151482
A model of a sympathetic preganglionic neurone of muscle vasoconstrictor-type.
Reference:
1 . Briant LJ, Stalbovskiy AO, Nolan MF, Champneys AR, Pickering AE (2014) Increased intrinsic excitability of muscle vasoconstrictor preganglionic neurons may contribute to the elevated sympathetic activity in hypertensive rats. J Neurophysiol 112:2756-2778 [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): Spinal cord L motor neuron alpha; Spinal cord sympathetic preganglionic neuron;
Channel(s): I Na,t; I L high threshold; I N; I A; I K; I K,Ca; I_AHP;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Action Potential Initiation; Activity Patterns; Bursting; Ion Channel Kinetics; Temporal Pattern Generation; Parameter Fitting; Action Potentials; Parameter sensitivity;
Implementer(s):
Search NeuronDB for information about:  Spinal cord L motor neuron alpha; I Na,t; I L high threshold; I N; I A; I K; I K,Ca; I_AHP;
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SPN_ModelDB
hoc_code
MATLAB_code
README.txt
borgka.mod
borgkdr.mod
cadifus2.mod
cagk.mod *
cal2.mod *
can2.mod
gap.mod
gapcalcium.mod
kadist.mod *
kahp.mod *
kaprox.mod *
na3.mod
ActivationProtocol_GKA.dat
ActivationProtocol_IA.dat
ActivationProtocol_V.dat
Cell.hoc
ClampFiddy.dat
ClampFiddy_vhalfm.dat
ClampFiddy_ZetaK.dat
ClampFiddy_ZetaM.dat
ClampHundred.dat
ClampHundred_vhalfm.dat
ClampHundred_ZetaK.dat
ClampHundred_ZetaM.dat
CurrentMagnitude_GKA.dat
CurrentMagnitude_IA.dat
CurrentMagnitude_V.dat
EPSCs_Filtered.txt
InactivationProtocol_GKA.dat
InactivationProtocol_IA.dat
InactivationProtocol_V.dat
init.hoc
mosinit.hoc *
                            
TITLE K-A channel from Klee Ficker and Heinemann
: modified to account for Dax A Current --- M.Migliore Jun 1997
: modified to be used with cvode  M.Migliore 2001

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

}

PARAMETER {
	v (mV)
	celsius		(degC)
	gkabar=.008 (mho/cm2)
        vhalfn=11   (mV)
        vhalfl=-56   (mV)
        a0l=0.05      (/ms)
        a0n=0.05    (/ms)
        zetan=-1.5    (1)
        zetal=3    (1)
        gmn=0.55   (1)
        gml=1   (1)
	lmin=2  (mS)
	nmin=0.1  (mS)
	pw=-1    (1)
	tq=-40
	qq=5
	q10=5
	qtl=1
	ek
}


NEURON {
	SUFFIX kap
	USEION k READ ek WRITE ik
        RANGE gkabar,gka
        GLOBAL ninf,linf,taul,taun,lmin
}

STATE {
	n
        l
}

ASSIGNED {
	ik (mA/cm2)
        ninf
        linf      
        taul
        taun
        gka
}

INITIAL {
	rates(v)
	n=ninf
	l=linf
}


BREAKPOINT {
	SOLVE states METHOD cnexp
	gka = gkabar*n*l
	ik = gka*(v-ek)

}


FUNCTION alpn(v(mV)) {
LOCAL zeta
  zeta=zetan+pw/(1+exp((v-tq)/qq))
  alpn = exp(1.e-3*zeta*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION betn(v(mV)) {
LOCAL zeta
  zeta=zetan+pw/(1+exp((v-tq)/qq))
  betn = exp(1.e-3*zeta*gmn*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION alpl(v(mV)) {
  alpl = exp(1.e-3*zetal*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION betl(v(mV)) {
  betl = exp(1.e-3*zetal*gml*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius))) 
}

DERIVATIVE states {     : exact when v held constant; integrates over dt step
        rates(v)
        n' = (ninf - n)/taun
        l' =  (linf - l)/taul
}

PROCEDURE rates(v (mV)) { :callable from hoc
        LOCAL a,qt
        qt=q10^((celsius-24)/10)
        a = alpn(v)
        ninf = 1/(1 + a)
        taun = betn(v)/(qt*a0n*(1+a))
	if (taun<nmin) {taun=nmin}
        a = alpl(v)
        linf = 1/(1+ a)
	taul = 0.26*(v+50)/qtl
	if (taul<lmin/qtl) {taul=lmin/qtl}
}















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