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A fast model of voltage-dependent NMDA Receptors (Moradi et al. 2013)

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Accession:145836
These are two or triple-exponential models of the voltage-dependent NMDA receptors. Conductance of these receptors increase voltage-dependently with a "Hodgkin and Huxley-type" gating style that is also depending on glutamate-binding. Time course of the gating of these receptors in response to glutamate are also changing voltage-dependently. Temperature sensitivity and desensitization of these receptor are also taken into account. Three previous kinetic models that are able to simulate the voltage-dependence of the NMDARs are also imported to the NMODL. These models are not temperature sensitive. These models are compatible with the "event delivery system" of NEURON. Parameters that are reported in our paper are applicable to CA1 pyramidal cell dendrites.
Reference:
1 . Moradi K, Moradi K, Ganjkhani M, Hajihasani M, Gharibzadeh S, Kaka G (2013) A fast model of voltage-dependent NMDA receptors. J Comput Neurosci 34:521-31 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism: Neocortex; Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s):
Gap Junctions:
Receptor(s): NMDA; Glutamate;
Gene(s): NR2B GRIN2B;
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Ion Channel Kinetics; Simplified Models; Long-term Synaptic Plasticity; Methods;
Implementer(s): Moradi, Keivan [k.moradi at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; NMDA; Glutamate; Glutamate;
/* In this experiment desensitization of NMDAR is going to be tested
*/
load_file("nrngui.hoc")
load_file("params.hoc")

//fully activates cache efficiency
cvode.cache_efficient(1)  

tstop = 1747.875
dt = .025
celsius = 23	//room temperature in Erreger05 experiment
v_init = 40

SynWeight = 0.9242
D = 0.2
Tau_D = 2500

Tau1 = 1.0327
Tau2_0 = 25.057
Tau3_0 = 232.27
A2 = 2.2364
A3 = 43.495

// ------------------
create soma
access soma

objref sNMDA, stim, nc
stim = new NetStim(.5)
	stim.interval = 195	//ms (mean) time between spikes
	stim.number = 6	//(average) number of spikes
	stim.start 	= 88.69	//ms (most likely) start time of first spike
	stim.noise 	= 0		//---- range 0 to 1. Fractional randomness.
	//0 deterministic, 1 intervals have negexp distribution.
sNMDA = new Exp5NMDA2(.5)
nc = new NetCon(stim, sNMDA)

proc init_NMDA() {
	sNMDA.d = D
	sNMDA.tau_D = Tau_D
	
	sNMDA.tau1 = Tau1
	sNMDA.a2 = A2
	sNMDA.tau2_0 = Tau2_0
	sNMDA.a3 = A3
	sNMDA.tau3_0 = Tau3_0
	
	nc.weight = SynWeight
	nc.delay = 1
}
objref FinNMDA
FinNMDA = new FInitializeHandler(3,"init_NMDA()")
	
//----------------------------------------------------	
objref vc, vscr, tvec

vscr = new Vector(12)
tvec = new Vector(12)

vc = new VClamp(.5)
	vc.dur[0] = tstop
	vc.amp[0] = -60

// objref iNMDA, vSoma
// iNMDA = new Graph()
// iNMDA.size(0,tstop,-6,0)
// iNMDA.addvar("sNMDA.i",3,0)
// iNMDA.save_name("graphList[0].")
// graphList[0].append(iNMDA)

// vSoma = new Graph()
// vSoma.size(0,tstop,-100,50)
// vSoma.addvar("soma.v(.5)",3,0)
// vSoma.save_name("graphList[0].")
// graphList[0].append(vSoma)

// xpanel("PSP amplitudes")
	// xvalue("D1")
	// xvalue("Tau_D1")
	// xvalue("SynWeight")
	// xbutton("InitRun()")
// xpanel(500,500)

// proc InitRun() {
// init()
// run()
// }

load_file("MRF-Desen-5Hz.ses")

// objref iNMDA, iFile, time, tFile
// iNMDA = new Vector()
// iNMDA.record(&sNMDA.i)
// iFile = new File("iFile.dat")
// iFile.wopen("iFile.dat")

// time = new Vector()
// time.record(&t)
// tFile = new File("tFile.dat")
// tFile.wopen("tFile.dat")

// init()
// run()

// iNMDA.printf(iFile)
// iFile.close()

// time.printf(tFile)
// tFile.close()

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