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 *
                            
TITLE K-A channel from Klee Ficker and Heinemann
: modified to account for Dax A Current ----------
: M.Migliore Jun 1997
: modified by Poirazi on 10/2/00 according to Hoffman_etal97 
: to account for I_A distal (>100microns)
: (n) activation, (l) inactivation


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

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

PARAMETER {
        dt (ms)
	v (mV)
        ek (mV)              : must be explicitely def. in hoc
	gkabar=0.018 (mho/cm2)
        vhalfn= -1   (mV)
        vhalfl=-56   (mV)
}

NEURON {
	SUFFIX kad
	USEION k READ ek WRITE ik
        RANGE gkabar,gka
        GLOBAL ninf,linf,taul,taun
}

STATE {
	n
        l
}

ASSIGNED {
	ik (mA/cm2)
        ninf
        linf
        taul
        taun
        gka
}

INITIAL {
	rates(v)
	n=ninf
	l=linf
	gka = gkabar*n^4*l
	ik = gka*(v-ek)
}

BREAKPOINT {
	SOLVE states
	gka = gkabar*n^4*l
	ik = gka*(v-ek)
}

FUNCTION alpn(v(mV)) {
  alpn = -0.01*(v+34.4)/(exp((v+34.4)/-21)-1)
}


FUNCTION betn(v(mV)) {
  betn = 0.01*(v+34.4)/(exp((v+34.4)/21)-1)
}

FUNCTION alpl(v(mV)) {
  alpl = -0.01*(v+58)/(exp((v+58)/8.2)-1)
}

FUNCTION betl(v(mV)) {
  betl = 0.01*(v+58)/(exp((v+58)/-8.2)-1)
}

LOCAL facn,facl
PROCEDURE states() {     : exact when v held constant; integrates over dt step
        rates(v)
        n = n + facn*(ninf - n)
        l = l + facl*(linf - l)
        VERBATIM
        return 0;
        ENDVERBATIM
}

PROCEDURE rates(v (mV)) { :callable from hoc
        LOCAL a,b
        a = alpn(v)
        b = betn(v)
        ninf = a/(a + b)
        taun = 0.2
        facn = (1 - exp(-dt/taun))
        a = alpl(v)
        b = betl(v)
        linf = a/(a + b)
        
        if (v > -20) {
	   taul = 5 + 2.6*(v+20)/10
        } else {
	   taul = 5
        }
        facl = (1 - exp(-dt/taul))
}

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