Encoding and retrieval in a model of the hippocampal CA1 microcircuit (Cutsuridis et al. 2009)

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Accession:123815
This NEURON code implements a small network model (100 pyramidal cells and 4 types of inhibitory interneuron) of storage and recall of patterns in the CA1 region of the mammalian hippocampus. Patterns of PC activity are stored either by a predefined weight matrix generated by Hebbian learning, or by STDP at CA3 Schaffer collateral AMPA synapses.
Reference:
1 . Cutsuridis V, Cobb S, Graham BP (2009) Encoding and retrieval in a model of the hippocampal CA1 microcircuit. Hippocampus 20(3):423-46 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal cell; Hippocampus CA1 basket cell;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Pattern Recognition; Activity Patterns; Temporal Pattern Generation; Learning; STDP; Connectivity matrix; Storage/recall;
Implementer(s): Graham, Bruce [B.Graham at cs.stir.ac.uk]; Cutsuridis, Vassilis [vcutsuridis at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; GabaA; AMPA; NMDA;
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Hipp_paper_code
Results
Weights
readme.txt
ANsyn.mod *
bgka.mod *
burststim2.mod *
cad.mod *
cagk.mod *
cal.mod *
calH.mod *
car.mod *
cat.mod *
ccanl.mod *
gskch.mod *
h.mod *
hha_old.mod *
hha2.mod *
hNa.mod *
IA.mod *
ichan2.mod *
Ih.mod *
kad.mod *
kap.mod *
Kaxon.mod *
kca.mod *
Kdend.mod *
km.mod *
Ksoma.mod *
LcaMig.mod *
my_exp2syn.mod *
Naaxon.mod *
Nadend.mod *
Nasoma.mod *
nca.mod *
nmda.mod *
regn_stim.mod *
somacar.mod *
STDPE2Syn.mod *
axoaxonic_cell17S.hoc *
basket_cell17S.hoc *
bistratified_cell13S.hoc *
burst_cell.hoc *
HAM_SR.ses
HAM_StoRec_par.hoc
HAM_StoRec_ser.hoc
mosinit.hoc
olm_cell2.hoc
pyramidal_cell_14Vb.hoc
ranstream.hoc *
stim_cell.hoc *
                            
COMMENT
A synaptic current with two dual exponential function conductances,
representing non-voltage-dependent AMPA and voltage-dependent NMDA
components.  The basic dual exponential conductance is given by:
         g = 0 for t < onset and
         g = gmax*((tau1*tau2)/(tau1-tau2)) *
                             (exp(-(t-onset)/tau1)-exp(-(t-onset)/tau2))
         for t > onset (tau1 and tau2 are fast and slow time constants)
The synaptic current is:
        i = (gA + gN) * (v - e)      i(nanoamps), g(micromhos);
NMDA model taken from Mel, J. Neurophys. 70:1086-1101, 1993
BPG 1-12-00
ENDCOMMENT
                           
INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
    POINT_PROCESS ANSynapse
    RANGE onset, gmax, e, i, g, gA, gN, tau1, tau2, Ntau1, Ntau2, eta, Mg, gamma, Nfrac
    NONSPECIFIC_CURRENT i
}

UNITS {
    (nA) = (nanoamp)
    (mV) = (millivolt)
    (umho) = (micromho)
}

PARAMETER {
    onset=0 (ms)
    tau1=.2 (ms)    <1e-3,1e6>
    tau2=2 (ms)    <1e-3,1e6>
    Nfrac=0.5
    Ntau1=.66 (ms)    <1e-3,1e6>
    Ntau2=80 (ms)    <1e-3,1e6>
    eta=0.33 (/mM)
    Mg=1 (mM)
    gamma=0.06 (/mV)
    gmax=0  (umho)  <0,1e9>
    e=0 (mV)
    v   (mV)
}

ASSIGNED { i (nA)  g (umho) gA (umho) gN (umho) Agmax (umho) Ngmax (umho)}

INITIAL {
    Agmax = (1-Nfrac)*gmax
    Ngmax = Nfrac*gmax
}

BREAKPOINT {
    gA = Agmax*((tau1*tau2)/(tau1-tau2))*duale((t-onset)/tau1,(t-onset)/tau2)
    gN = Ngmax*((Ntau1*Ntau2)/(Ntau1-Ntau2))*duale((t-onset)/Ntau1,(t-onset)/Ntau2)
    gN = gN / (1 + (eta*Mg*exp(-gamma*v)))
    g = gA + gN
    i = g*(v - e)
}

FUNCTION duale(x,y) {
    if (x < 0 || y < 0) {
        duale = 0
    }else{
        duale = exp(-x) - exp(-y)
    }
}

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