Conductance based model for short term plasticity at CA3-CA1 synapses (Mukunda & Narayanan 2017)

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Accession:244922
We develop a new biophysically rooted, physiologically constrained conductance-based synaptic model to mechanistically account for short-term facilitation and depression, respectively through residual calcium and transmitter depletion kinetics. The model exhibits different synaptic filtering profiles upon changing certain parameters in the base model. We show degenercy in achieving similar plasticity profiles with different presynaptic parameters. Finally, by virtually knocking out certain conductances, we show the differential contribution of conductances.
Reference:
1 . Mukunda CL, Narayanan R (2017) Degeneracy in the regulation of short-term plasticity and synaptic filtering by presynaptic mechanisms. J Physiol 595:2611-2637 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA3 pyramidal GLU cell;
Channel(s): I h; I K; I CAN;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Conductance distributions; Short-term Synaptic Plasticity; Calcium dynamics; Neurotransmitter dynamics;
Implementer(s): Mukunda, Chinmayee L [chinmayeelm at gmail.com];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal GLU cell; AMPA; I K; I h; I CAN;
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MukundaNarayanan2017
data
readme.html
cal2.mod
cal4.mod
can2.mod
ghkampaC.mod
h.mod *
kadist.mod
kdr.mod
minmax.mod
nahh.mod
pulses.mod
stp.mod
BPF.hoc
EPSC_1.txt
mosinit.hoc
plot_ca_data.m
screenshot.png
                            
TITLE AMPA receptors modelled according to GHK equations
NEURON 
{
	POINT_PROCESS ghkampaC
	USEION na WRITE ina
	USEION k WRITE ik
		
	RANGE C, TRise, tau, lr
	RANGE Alpha, Beta

	RANGE iampa
	RANGE P, Pmax
}

UNITS 
{
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(uS) = (microsiemens)
	(molar) = (1/liter)
	(mM) = (millimolar)
	R = (k-mole) (joule/degC)
	FARADAY = (faraday) (coulomb)
	
}

PARAMETER 
{
	TRise=0.6 	(ms)<1e-9,1e9>  : Andrasfalvy and Magee, JNS, 2001
	tau=3   	(ms)<1e-9,1e9>	 : Andrasfalvy and Magee, JNS, 2001
	
	nai = 18	(mM)	: Set for a reversal pot of +55mV
	nao = 140	(mM)
	ki = 140	(mM)	: Set for a reversal pot of -90mV
	ko = 5		(mM)
	celsius	 = 35	(degC)
	Pmax = 1e-6
}


ASSIGNED 
{
	v (mV)
	ina     (nA)
	ik      (nA)
	Alpha	(/ms mM): forward (binding) rate
	Beta	(/ms)	: backward (unbinding) rate
	C		(mM)		: transmitter concentration
	P (cm/s)
	iampa	(nA)
	Area (cm2)
	lr

}

STATE
{
	S				: fraction of open channels
}

INITIAL 
{
	S = 0
	Beta=1/tau
	Alpha=1/TRise - Beta
	Area=1
	
}

BREAKPOINT 
{
	SOLVE states METHOD cnexp
	P = (Pmax * S * (Alpha+Beta)) / (Alpha*(1-1/exp(1)))

	ina= P*ghk(v, nai, nao,1) * Area
	ik= P*ghk(v, ki, ko,1)* Area
	iampa=ina+ik : only for display purposes.
}

DERIVATIVE states
{	
	S'=Alpha * C * (1-S) - Beta * S
}

FUNCTION ghk(v(mV), ci(mM), co(mM),z) (0.001 coul/cm3) {
	LOCAL arg, eci, eco
	arg = (0.001)*z*FARADAY*v/(R*(celsius+273.15))
	eco = co*efun(arg)
	eci = ci*efun(-arg)
	ghk = (0.001)*z*FARADAY*(eci - eco)
}

FUNCTION efun(z) {
	if (fabs(z) < 1e-4) {
		efun = 1 - z/2
	}else{
		efun = z/(exp(z) - 1)
	}
}


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