CA1 pyramidal neuron: Persistent Na current mediates steep synaptic amplification (Hsu et al 2018)

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Accession:240960
This paper shows that persistent sodium current critically contributes to the subthreshold nonlinear dynamics of CA1 pyramidal neurons and promotes rapidly reversible conversion between place-cell and silent-cell in the hippocampus. A simple model built with realistic axo-somatic voltage-gated sodium channels in CA1 (Carter et al., 2012; Neuron 75, 1081–1093) demonstrates that the biophysics of persistent sodium current is sufficient to explain the synaptic amplification effects. A full model built previously (Grienberger et al., 2017; Nature Neuroscience, 20(3): 417–426) with detailed morphology, ion channel types and biophysical properties of CA1 place cells naturally reproduces the steep voltage dependence of synaptic responses.
Reference:
1 . Hsu CL, Zhao X, Milstein AD, Spruston N (2018) Persistent sodium current mediates the steep voltage dependence of spatial coding in hippocampal pyramidal neurons Neuron 99:1-16
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Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Channel/Receptor; Neuron or other electrically excitable cell; Axon; Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal cell; Abstract single compartment conductance based cell;
Channel(s): I Sodium; I A; I M; I h; I K;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Ion Channel Kinetics; Membrane Properties; Synaptic Integration; Synaptic Amplification; Place cell/field; Active Dendrites; Conductance distributions; Detailed Neuronal Models; Electrotonus; Markov-type model;
Implementer(s): Hsu, Ching-Lung [hsuc at janelia.hhmi.org]; Milstein, Aaron D. [aaronmil at stanford.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; AMPA; NMDA; I A; I K; I M; I h; I Sodium; Glutamate;
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HsuEtAl2018
FullModel
data
morphologies
README.md
ampa_kin.mod *
exp2EPSC.mod
gaba_a_kin.mod *
h.mod
kad.mod *
kap.mod *
kdr.mod *
km2.mod
nas.mod
nax.mod
nmda_kin5.mod *
pr.mod *
vecevent.mod *
batch_nap_EPSC_amplification.sh
batch_nap_EPSP_amplification.sh
batch_nap_EPSP_amplification_IO.sh
function_lib.py
install notes.txt
plot_nap_EPSC_amplification.py
plot_nap_EPSP_amplification.py
plot_nap_EPSP_amplification_IO.py
plot_results.py
simulate_nap_EPSC_amplification.py
simulate_nap_EPSP_amplification.py
simulate_nap_EPSP_amplification_IO.py
specify_cells.py
visualize_ion_channel_gating_parameters.py
                            
TITLE K-A channel from Klee Ficker and Heinemann
: modified to account for Dax A Current ----------
: M.Migliore Jun 1997

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

UNITS {
    (mA) = (milliamp)
    (mV) = (millivolt)
    (mol) = (1)
}

PARAMETER {
    temp    = 24                    (degC)
    gkabar                          (mho/cm2)

    vhalfn  = 11                    (mV)
    a0n     = 0.05                  (/ms)
    zetan   = -1.5                  (1)
    gmn     = 0.55                  (1)
    pw      = -1                    (1)
    tq      = -40                   (mV)
    qq      = 5                     (mV)
    nmin    = 0.1                   (ms)
    nscale  = 1

    vhalfl  = -56                   (mV)
    a0l     = 0.05                  (/ms)
    zetal   = 3                     (1)
    lmin    = 2                     (ms)
    lscale  = 1

    q10     = 5
}

STATE {
    n
    l
}

ASSIGNED {
    v           (mV)
    ik          (mA/cm2)
    ninf
    linf
    taul        (ms)
    taun        (ms)
    gka         (mho/cm2)
    qt
    celsius     (degC)
    ek          (mV)
}

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

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

DERIVATIVE states {
    rates(v)
    n' = (ninf-n)/taun
    l' = (linf-l)/taul
}

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

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


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

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

PROCEDURE rates(v (mV)) { :callable from hoc
    LOCAL a,qt
    qt=q10^((celsius-temp)/10(degC))
    a = alpn(v)
    ninf = 1/(1 + a)
    taun = betn(v)/(qt*a0n*(1+a))
    if (taun<nmin) {taun=nmin}
    taun=taun/nscale

    a = alpl(v)
    linf = 1/(1 + a)
    taul = 0.26(ms/mV)*(v+50)
    if (taul<lmin) {taul=lmin}
    taul=taul/lscale
}