Neural Query System NQS Data-Mining From Within the NEURON Simulator (Lytton 2006)

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Accession:97874
NQS is a databasing program with a query command modeled loosely on the SQL select command. Please see the manual NQS.pdf for details of use. An NQS database must be populated with data to be used. This package includes MFP (model fingerprint) which provides an example of NQS use with the model provided in the modeldb folder (see readme for usage).
Reference:
1 . Lytton WW (2006) Neural Query System: Data-mining from within the NEURON simulator. Neuroinformatics 4:163-76 [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):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Lytton, William [billl at neurosim.downstate.edu];
/
NQS_with_example
modeldb
readme.txt *
exp2i.mod *
h.mod *
kadist.mod *
kaprox.mod *
kdrca1.mod *
na3s.mod *
naxn.mod *
netstims.mod *
nmdanet.mod *
vecst.mod *
forfig5A.hoc *
n160.nrn *
orig_mosinit.hoc *
                            
TITLE K-A channel from Klee Ficker and Heinemann
: modified to account for Dax A Current ----------
: M.Migliore Jun 1997

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

PARAMETER {
	celsius
        v (mV)
        gkabar=.008 (mho/cm2)
        vhalfn=-1   (mV)
        vhalfl=-56   (mV)
        a0l=0.05      (/ms)
        a0n=.1    (/ms)
        zetan=-1.8    (1)
        zetal=3    (1)
        gmn=0.39   (1)
        gml=1   (1)
        lmin=2  (mS)
        nmin=0.2  (mS)
        pw=-1    (1)
        tq=-40
        qq=5
        q10=5
        qtl=1
	ek
}


NEURON {
        SUFFIX kad
        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
}

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

}

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


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 {  
        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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