Spine head calcium in a CA1 pyramidal cell model (Graham et al. 2014)

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Accession:154732
"We use a computational model of a hippocampal CA1 pyramidal cell to demonstrate that spine head calcium provides an instantaneous readout at each synapse of the postsynaptic weighted sum of all presynaptic activity impinging on the cell. The form of the readout is equivalent to the functions of weighted, summed inputs used in neural network learning rules. Within a dendritic layer, peak spine head calcium levels are either a linear or sigmoidal function of the number of coactive synapses, with nonlinearity depending on the ability of voltage spread in the dendrites to reach calcium spike threshold. ..."
Reference:
1 . Graham BP, Saudargiene A, Cobb S (2014) Spine head calcium as a measure of summed postsynaptic activity for driving synaptic plasticity. Neural Comput 26:2194-222 [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: Hippocampus;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Synaptic Integration;
Implementer(s): Graham, Bruce [B.Graham at cs.stir.ac.uk];
/
GrahamEtAl2014
Cells
Results
readme.html
burststim2.mod *
cad.mod
cagk.mod
carF.mod
distca.mod
distr.mod *
h.mod *
kadist.mod *
kaprox.mod *
kca.mod *
kdrca1.mod *
km.mod
na3n.mod *
naxn.mod *
nmdaca.mod *
burst_cell.hoc *
CA1PC.hoc
mosinit.hoc
randomlocation.hoc
ranstream.hoc *
run_batsyn.hoc
run_PC.hoc
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setup_PC.hoc
synstim.ses
                            
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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