Neurophysiological impact of inactivation pathways in A-type K+ channels (Fineberg et al 2012)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:145672
These models predict the differential effects of varying pathways of inactivation (closed state inactivation, CSI, or open state inactivation, OSI). Specifically, Markov models of Kv4 potassium channels with CSI or CSI+OSI were inserted into the CA1 pyramidal neuron model from Migliore et al (1999; ModelDB accession #2796) to determine the neurophysiological impact of inactivation pathways. Furthermore, Markov models of Kv4.2 and Kv3.4 channels are used to illustrate a method by which to test what pathway of inactivation a channel uses.
Reference:
1 . Fineberg JD, Ritter DM, Covarrubias M (2012) Modeling-independent elucidation of inactivation pathways in recombinant and native A-type Kv channels J Gen Physiol 140:513-527
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Channel/Receptor;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,t; I A; I K;
Gap Junctions:
Receptor(s):
Gene(s): Kv4.2 KCND2; Kv3.4 KCNC4;
Transmitter(s):
Simulation Environment: NEURON; IonChannelLab;
Model Concept(s): Ion Channel Kinetics; Markov-type model;
Implementer(s): Ritter, David [david.ritter at jefferson.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; I Na,t; I A; I K;
/
Fineberg_et_al_2012
IonChannelLab Files
README.html
Kv4_csi.mod
Kv4_csiosi.mod
migliore_kaprox.mod *
migliore_kdrca1.mod *
migliore_na3.mod *
migliore_nax.mod *
csi.hoc
csin160_mod.nrn
csiosi.hoc
csiosin160_mod.nrn
Figure11C CSI.hoc
Figure11C CSIOSI.hoc
Figure11D.hoc
Figure11E.hoc
graphavailability.ses
graphvoltage.ses
iclamp250.ses
iclamp40.ses
mosinit.hoc
n160_mod.nrn *
screenshot1.png
screenshot2.png
                            
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}
}















Loading data, please wait...