Multiplication by NMDA receptors in Direction Selective Ganglion cells (Poleg-Polsky & Diamond 2016)

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Accession:189347
The model demonstrates how signal amplification with NMDARs depends on the synaptic environment. When direction selectivity (DS) detection is mediated by DS inhibition, NMDARs multiply other synaptic conductances. In the case of DS tuned excitation, NMDARs contribute additively.
Reference:
1 . Poleg-Polsky A, Diamond JS (2016) NMDA Receptors Multiplicatively Scale Visual Signals and Enhance Directional Motion Discrimination in Retinal Ganglion Cells. Neuron 89:1277-1290 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Dendrite; Neuron or other electrically excitable cell; Realistic Network; Synapse;
Brain Region(s)/Organism:
Cell Type(s): Retina ganglion GLU cell;
Channel(s): I K; I Na,t;
Gap Junctions:
Receptor(s): AMPA; NMDA; GabaA; Nicotinic;
Gene(s):
Transmitter(s): Glutamate; Acetylcholine; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Direction Selectivity; Synaptic Integration; Vision;
Implementer(s): Polsky, Alon [alonpol at tx.technion.ac.il];
Search NeuronDB for information about:  Retina ganglion GLU cell; Nicotinic; GabaA; AMPA; NMDA; I Na,t; I K; Acetylcholine; Gaba; Glutamate;
:5403813100

:glutamate (AMPA+NMDA) release dependent on presynaptic voltage modeled here
NEURON {
POINT_PROCESS bipNMDA
	RANGE Vpre,Vdel,Vdur,Vamp,Vbase,locx,locy,local_v,i,g,release,numves :Vpre1,Vpre2,
	RANGE gAMPA,gNMDA,s_inf,t1,A,B,Vinf	:1,Vinf2
	GLOBAL maxves,newves,gAMPAsingle,gNMDAsingle,Vtau,Voff,Vset,VampK	:,Vnoiserate,Vnoiseamp,Vnoise,Vtau2
	GLOBAL icaconst ,gama,n,e,tauAMPA,tau1NMDA ,tau2NMDA
	NONSPECIFIC_CURRENT iAMPA,iNMDA
	:USEION ca WRITE ica
}

UNITS {
	(nA) 	= (nanoamp)
	(mV)	= (millivolt)
	(nS) 	= (nanomho)
}
PARAMETER {
							:presynaptic
	maxves=10				:TOTAL NUMBER OF VESICLES
	newves=0.01				:REPLENISHMENT RATE - VESICLES
	:Vnoise=0				:VOLTAGE VARIABILITY-INPUT NOISE
	Vdel=50 	(ms)		:START OF ACTIVATION
	Vdur=100	(ms)		:DURATION OF ACTIVATION
	Vamp=10		(mV)		:PEAK AMPLITUDE -STIMULUS
	Vbase=0		(mV)		:BACKGROUND ACTIVATION
	VampK=2					:SIZE OF THE INITIAL RESPONSE
	:Vnoiseamp=.1			:INTRINSIC NOISE
	:Vnoiserate=50			:INTRINSIC NOISE
	Vtau=30	(/ms)		:STIMULUS DEPOLARIZATION RATE
	:Vtau2=100	(/ms)		:STIMULUS HYPERPOLARIZATION RATE
							:postsynaptic
	gAMPAsingle=0.2	(nS)	:AMPA CONDUCTANCE
	gNMDAsingle=0.2	(nS)	:NMDA CONDUCTANCE
	tau1NMDA=50	(ms)		:DEACTIVATION
	tau2NMDA=2	(ms)		:ACTIVATION
	tauAMPA=2	(ms)		:DEACTIVATION
	n=0.25 		(/mM)		:NMDA VOLTAGE DEPENDENCE 
	gama=0.08 	(/mV)		:NMDA VOLTAGE DEPENDENCE 
	e = 0 		(mV)		:REVERSAL POTENTIAL
	locx=0					:location x
	locy=0					:location y
	icaconst =0.1			:CALCIUM FRACTION
	Voff=0					:0 - voltage dependent 1- voltage independent
	Vset=-60				:set voltage when voltage independent
}

ASSIGNED {
	:presynaptic
	Vinf 		(mV)
	:Vinf2 		(mV)	
	s_inf
	t1	
	numves
	release

	:postsynaptic
	v 			(mV)
	i 			(nA)
	g           (nS)
	iNMDA		(nA)
	iAMPA		(nA)
	gNMDA		(nS)
	local_v		(mV)
	:ica			(nA)
}

STATE {
	A
	B
	gAMPA 		(nS)
	:Vpre1 		(mV)
	:Vpre2 		(mV)
	Vpre		(mV)
}

BREAKPOINT {
	SOLVE state METHOD euler
	if (t>t1){										:EVERY 1 MS
		:Vpre=Vpre1-Vpre2+Vbase						:+normrand(0,Vnoise)	:PRESYNAPTIC VOLTAGE
		:if (Vpre<0){
		:	Vpre=0
		:}
:		if (scop_random()<1/Vnoiserate){			:ADDED INTRINSIC NOISE
:			Vinf1=Vinf1*(1+Vnoiseamp*(scop_random()-.5))
:		}
		releasefunc(Vpre)
		t1=t1+1
	}
	:IF(at_time(Vdel)){								:START STIMULUS 
	:	Vinf1=Vamp*VampK									:*(1+Vnoiseamp*(scop_random()-.5))
	:	Vinf2=Vamp*(VampK-1)
	:}
	:IF(at_time(Vdel+Vdur)){							:END STIMULUS
	:	Vinf1=Vbase									:*(1+Vnoiseamp*(scop_random()-.5))
	:	Vinf2=Vbase
	:}

	local_v=v*(1-Voff)+Vset*Voff					:VOLTAGE DEPENDENCE
	gNMDA=(A-B)/(1+n*exp(-gama*local_v) )
	iAMPA = (1e-3)*gAMPA * (v - e)
	iNMDA = (1e-3)*gNMDA * (v - e)
	i= iAMPA+iNMDA									:INDICATOR OF TOTAL CURRENT
	g=gNMDA+gAMPA									:INDICATOR OF TOTAL CONDUCTANCE

	:ica=iNMDA*icaconst	
	:iNMDA=iNMDA-ica
}

INITIAL {
	:presynaptic
	s_inf=0
	release=0
	numves=maxves
	t1=0
	Vinf=0	:Vbase
	Vpre=Vinf
	:Vinf2=Vbase
	:Vpre1=Vbase
	:Vpre2=Vbase

	:postsynaptic
	gAMPA=0
	gNMDA=0
	A=0
	B=0
}
 
FUNCTION releasefunc(vpre){
	LOCAL rand,addves
	s_inf=vpre/100
	release=0	
	FROM rand=0 TO numves-1 {			:GOES OVER ALL RRP
		if (scop_random()<s_inf){
			release=release+1
		}
	}
	if (release>0){						:RELEASE
		numves=numves-release
		if (numves<0){numves=0}
		state_discontinuity( gAMPA, gAMPA+ release*gAMPAsingle)
		state_discontinuity( A, A+ release*gNMDAsingle)
		state_discontinuity( B, B+ release*gNMDAsingle)
	}
	addves=0							:REPLINISHMENT
	FROM rand=0 TO maxves-numves-1 {
		if (scop_random()<newves){addves=addves+1}
	}
	numves=numves+addves
}
DERIVATIVE state {
	A'=-A/tau1NMDA
	B'=-B/tau2NMDA
	gAMPA'=-gAMPA/tauAMPA
	Vpre'=(-Vpre+Vinf)/Vtau
	:Vpre2'=(-Vpre2+Vinf2)/Vtau2

}

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