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 (2010) Encoding and retrieval in a model of the hippocampal CA1 microcircuit. Hippocampus 20:423-46 [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 CaGk
: Calcium activated mAHP K channel.
: From Moczydlowski and Latorre (1983) J. Gen. Physiol. 82

UNITS {
	(molar) = (1/liter)
}

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

INDEPENDENT {t FROM 0 TO 1 WITH 100 (ms)}

NEURON {
	SUFFIX mykca
	USEION ca READ cai
	USEION k READ ek WRITE ik
	RANGE gkbar, ik
	GLOBAL oinf, tau
}

UNITS {
	FARADAY = (faraday)  (kilocoulombs)
	R = 8.313424 (joule/degC)
}

PARAMETER {
	v		(mV)
	dt		(ms)
	ek		(mV)
	celsius = 20	(degC)
	gkbar = 0.01	(mho/cm2)	: Maximum Permeability
	cai = 1e-3	(mM)
	d1 = 0.84
	d2 = 1.0
	k1 = 0.18	(mM)
	k2 = 0.011	(mM)
	bbar = 0.28	(/ms)
	abar = 0.48	(/ms)
}
COMMENT
the preceding two numbers were switched on 8/19/92 in response to a bug
report by Bartlett Mel. In the paper the kinetic scheme is
C <-> CCa (K1)
CCa <-> OCa (beta2,alpha2)
OCa <-> OCa2 (K4)
In this model abar = beta2 and bbar = alpha2 and K4 comes from d2 and k2
I was forcing things into a nomenclature where alpha is the rate from
closed to open. Unfortunately I didn't switch the numbers.
ENDCOMMENT

ASSIGNED {
	ik		(mA/cm2)
	oinf
	tau		(ms)
}

STATE {	o }		: fraction of open channels

BREAKPOINT {
	SOLVE state
	ik = gkbar*o*(v - ek) : potassium current induced by this channel
}

LOCAL fac

:if state_cagk is called from hoc, garbage or segmentation violation will
:result because range variables won't have correct pointer.  This is because
:only BREAKPOINT sets up the correct pointers to range variables.
PROCEDURE state() {	: exact when v held constant; integrates over dt step
	rate(v, cai)
	o = o + fac*(oinf - o)
	VERBATIM
	return 0;
	ENDVERBATIM
}

INITIAL {           : initialize the following parameter using rate()
	rate(v, cai)
	o = oinf
}

FUNCTION alp(v (mV), ca (mM)) (1/ms) { :callable from hoc
	alp = abar/(1 + exp1(k1,d1,v)/ca)
}

FUNCTION bet(v (mV), ca (mM)) (1/ms) { :callable from hoc
	bet = bbar/(1 + ca/exp1(k2,d2,v))
}  

FUNCTION exp1(k (mM), d, v (mV)) (mM) { :callable from hoc
	exp1 = k*exp(-2*d*FARADAY*v/R/(273.15 + celsius))
}

PROCEDURE rate(v (mV), ca (mM)) { :callable from hoc
	LOCAL a
	a = alp(v,ca)
	tau = 1/(a + bet(v, ca)) : estimation of activation tau
	oinf = a*tau             : estimation of activation steady state value
	fac = (1 - exp(-dt/tau))
}

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