CA1 pyramidal neuron: synaptic plasticity during theta cycles (Saudargiene et al. 2015)

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Accession:157157
This NEURON code implements a microcircuit of CA1 pyramidal neuron and consists of a detailed model of CA1 pyramidal cell and four types of inhibitory interneurons (basket, bistratified, axoaxonic and oriens lacunosum-moleculare cells). Synaptic plasticity during theta cycles at a synapse in a single spine on the stratum radiatum dendrite of the CA1 pyramidal cell is modeled using a phenomenological model of synaptic plasticity (Graupner and Brunel, PNAS 109(20):3991-3996, 2012). The code is adapted from the Poirazi CA1 pyramidal cell (ModelDB accession number 20212) and the Cutsuridis microcircuit model (ModelDB accession number 123815)
Reference:
1 . Saudargiene A, Cobb S, Graham BP (2015) A computational study on plasticity during theta cycles at Schaffer collateral synapses on CA1 pyramidal cells in the hippocampus. Hippocampus 25:208-18 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 pyramidal cell; Hippocampus CA1 basket cell; Hippocampus CA1 bistratified cell; Hippocampus CA1 axo-axonic cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Long-term Synaptic Plasticity; STDP;
Implementer(s): Saudargiene, Ausra [ausra.saudargiene at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell;
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SaudargieneEtAl2015
readme.html
ANsyn.mod *
bgka.mod *
bistableGB_DOWNUP.mod
burststim2.mod *
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kadbru.mod
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kapbru.mod
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Kaxon.mod *
kca.mod *
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km.mod *
Ksoma.mod *
LcaMig.mod *
my_exp2syn.mod *
Naaxon.mod *
Nadend.mod *
nap.mod
Nasoma.mod *
nca.mod *
nmda.mod *
nmdaca.mod *
regn_stim.mod *
somacar.mod *
STDPE2Syn.mod *
apical-non-trunk-list.hoc
apical-tip-list.hoc
apical-tip-list-addendum.hoc
apical-trunk-list.hoc
axoaxonic_cell17S.hoc
axon-sec-list.hoc
BasalPath.hoc
basal-paths.hoc
basal-tree-list.hoc
basket_cell17S.hoc
bistratified_cell13S.hoc
burst_cell.hoc
current-balance.hoc *
main.hoc
map-segments-to-3d.hoc *
mod_func.c
mosinit.hoc
ObliquePath.hoc *
oblique-paths.hoc
olm_cell2.hoc
pattsN100S20P5_single.dat
PC.ses
peri-trunk-list.hoc
pyramidalNeuron.hoc
randomLocation.hoc
ranstream.hoc
screenshot.png
soma-list.hoc
stim_cell.hoc *
vector-distance.hoc
                            
COMMENT
Two state kinetic scheme synapse described by rise time tau1,
and decay time constant tau2. The normalized peak condunductance is 1.
Decay time MUST be greater than rise time.

The solution of A->G->bath with rate constants 1/tau1 and 1/tau2 is
 A = a*exp(-t/tau1) and
 G = a*tau2/(tau2-tau1)*(-exp(-t/tau1) + exp(-t/tau2))
	where tau1 < tau2

If tau2-tau1 -> 0 then we have a alphasynapse.
and if tau1 -> 0 then we have just single exponential decay.

The factor is evaluated in the
initial block such that an event of weight 1 generates a
peak conductance of 1.

Because the solution is a sum of exponentials, the
coupled equations can be solved as a pair of independent equations
by the more efficient cnexp method.

ENDCOMMENT

NEURON {
	POINT_PROCESS MyExp2Syn
	RANGE tau1, tau2, e, i
	NONSPECIFIC_CURRENT i

	RANGE g
	GLOBAL total
}

UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(uS) = (microsiemens)
}

PARAMETER {
	tau1=.1 (ms) <1e-9,1e9>
	tau2 = 10 (ms) <1e-9,1e9>
	e=0	(mV)
}

ASSIGNED {
	v (mV)
	i (nA)
	g (uS)
	factor
	total (uS)
}

STATE {
	A (uS)
	B (uS)
}

INITIAL {
	LOCAL tp
	total = 0
	if (tau1/tau2 > .9999) {
		tau1 = .9999*tau2
	}
	A = 0
	B = 0
	tp = (tau1*tau2)/(tau2 - tau1) * log(tau2/tau1)
	factor = -exp(-tp/tau1) + exp(-tp/tau2)
	factor = 1/factor
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	g = B - A
	i = g*(v - e)
}

DERIVATIVE state {
	A' = -A/tau1
	B' = -B/tau2
}

NET_RECEIVE(weight (uS)) {
	state_discontinuity(A, A + weight*factor)
	state_discontinuity(B, B + weight*factor)
	total = total+weight
}