Effect of the initial synaptic state on the probability to induce LTP and LTD (Migliore et al. 2015)

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Accession:157339
NEURON mod files from the paper: M. Migliore, et al. (2015). In this paper, we investigate the possibility that the experimental protocols on synaptic plasticity may result in different consequences (e.g., LTD instead of LTP), according to the initial conditions of the stimulated synapses, and can generate confusing results. Using biophysical models of synaptic plasticity and hippocampal CA1 pyramidal neurons, we study how, why, and to what extent EPSPs observed at the soma after induction of LTP/LTD reflects the actual (local) synaptic state. The model and the results suggest a physiologically plausible explanation of why LTD induction is experimentally difficult, and they offer experimentally testable predictions on the stimulation protocols that may be more effective.
Reference:
1 . Migliore M, De Simone G, Migliore R (2015) Effect of the Initial Synaptic State on the Probability to Induce Long-Term Potentiation and Depression Biophysical Journal 108:1038-1046 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,t; I A; I K; I h;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Long-term Synaptic Plasticity;
Implementer(s): Migliore, Michele [Michele.Migliore at Yale.edu]; Migliore, Rosanna [rosanna.migliore at cnr.it];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; AMPA; I Na,t; I A; I K; I h; Glutamate;
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MiglioreEtAl2015
readme.html
h.mod *
kadist.mod *
kaprox.mod *
kdrca1.mod *
ltpltd.mod
na3n.mod *
naxn.mod *
netstims.mod *
fig1C.hoc
fixnseg.hoc *
geo5038804.hoc *
mosinit.hoc
screenshot.png
                            
TITLE K-DR channel
: from Klee Ficker and Heinemann
: modified to account for Dax et al.
: M.Migliore 1997

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

}

PARAMETER {
	v (mV)
        ek (mV)		: must be explicitely def. in hoc
	celsius		(degC)
	gkdrbar=.003 (mho/cm2)
        vhalfn=13   (mV)
        a0n=0.02      (/ms)
        zetan=-3    (1)
        gmn=0.7  (1)
	nmax=2  (1)
	q10=1
}


NEURON {
	SUFFIX kdr
	USEION k READ ek WRITE ik
        RANGE gkdr,gkdrbar
	GLOBAL ninf,taun
}

STATE {
	n
}

ASSIGNED {
	ik (mA/cm2)
        ninf
        gkdr
        taun
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	gkdr = gkdrbar*n
	ik = gkdr*(v-ek)

}

INITIAL {
	rates(v)
	n=ninf
}


FUNCTION alpn(v(mV)) {
  alpn = exp(1.e-3*zetan*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION betn(v(mV)) {
  betn = exp(1.e-3*zetan*gmn*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
}

DERIVATIVE states {     : exact when v held constant; integrates over dt step
        rates(v)
        n' = (ninf - n)/taun
}

PROCEDURE rates(v (mV)) { :callable from hoc
        LOCAL a,qt
        qt=q10^((celsius-24)/10)
        a = alpn(v)
        ninf = 1/(1+a)
        taun = betn(v)/(qt*a0n*(1+a))
	if (taun<nmax) {taun=nmax}
}















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