Schiz.-linked gene effects on intrinsic single-neuron excitability (Maki-Marttunen et al. 2016)

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Accession:169457
Python scripts for running NEURON simulations that model a layer V pyramidal cell with certain genetic variants implemented. The genes included are obtained from genome-wide association studies of schizophrenia.
Reference:
1 . Mäki-Marttunen T, Halnes G, Devor A, Witoelar A, Bettella F, Djurovic S, Wang Y, Einevoll GT, Andreassen OA, Dale AM (2016) Functional Effects of Schizophrenia-Linked Genetic Variants on Intrinsic Single-Neuron Excitability: A Modeling Study. Biol Psychiatry Cogn Neurosci Neuroimaging 1:49-59 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I K,leak; I M; I h; I K,Ca; I A, slow; Ca pump;
Gap Junctions:
Receptor(s):
Gene(s): Nav1.1 SCN1A; Nav1.7 SCN9A; Cav3.3 CACNA1I; Cav1.3 CACNA1D; Cav1.2 CACNA1C; Kv2.1 KCNB1; HCN1;
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Coincidence Detection; Active Dendrites; Detailed Neuronal Models; Schizophrenia;
Implementer(s): Maki-Marttunen, Tuomo [tuomo.maki-marttunen at tut.fi];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I K,leak; I M; I h; I K,Ca; I A, slow; Ca pump;
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Maki-MarttunenEtAl2015
models
morphologies
readme.txt
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collectscalings.py
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drawfig1.py
drawfig2.py
drawfig3.py
drawfig4.py
drawfig5.py
findthresholddistalamps.py
mutation_stuff.py
mytools.py
runcontrols.py
savesynapselocations.py
scalemutations.py
scalings.sav
                            
:Comment :
:Reference : :		Kole,Hallermann,and Stuart, J. Neurosci. 2006

NEURON	{
	SUFFIX Ih
	NONSPECIFIC_CURRENT ihcn
	RANGE gIhbar, gIh, ihcn, ehcn, offma, sloma, tauma, offmb, slomb, taumb
}

UNITS	{
	(S) = (siemens)
	(mV) = (millivolt)
	(mA) = (milliamp)
}

PARAMETER	{
	gIhbar = 0.00001 (S/cm2) 
	ehcn =  -45.0 (mV)
	offma = -154.9 (mV)
	sloma = 11.9 (mV)
	tauma = 155.521 (ms)
	offmb = 0.0 (mV)
	slomb = 33.1 (mV)
	taumb = 5.18135 (ms)
}

ASSIGNED	{
	v	(mV)
	ihcn	(mA/cm2)
	gIh	(S/cm2)
	mInf
	mTau
	mAlpha
	mBeta
}

STATE	{ 
	m
}

BREAKPOINT	{
	SOLVE states METHOD cnexp
	gIh = gIhbar*m
	ihcn = gIh*(v-ehcn)
}

DERIVATIVE states	{
	rates()
	m' = (mInf-m)/mTau
}

INITIAL{
	rates()
	m = mInf
}

PROCEDURE rates(){
	UNITSOFF
        if(v == offma){
            v = v + 0.0001
        }
		mAlpha = -(offma-v)/tauma/(exp(-(offma-v)/sloma)-1)
		mBeta  = exp(-(offmb-v)/slomb)/taumb
		mInf = mAlpha/(mAlpha + mBeta)
		mTau = 1/(mAlpha + mBeta)
	UNITSON
}

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