Pleiotropic effects of SCZ-associated genes (Mäki-Marttunen et al. 2017)

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Accession:187615
Python and MATLAB scripts for studying the dual effects of SCZ-related genes on layer 5 pyramidal cell firing and sinoatrial node cell pacemaking properties. The study is based on two L5PC models (Hay et al. 2011, Almog & Korngreen 2014) and SANC models (Kharche et al. 2011, Severi et al. 2012).
Reference:
1 . Mäki-Marttunen T, Lines GT, Edwards AG, Tveito A, Dale AM, Einevoll GT, Andreassen OA (2017) Pleiotropic effects of schizophrenia-associated genetic variants in neuron firing and cardiac pacemaking revealed by computational modeling. Transl Psychiatry 7:5 [PubMed]
Citations  Citation Browser
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; Cardiac atrial cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow; Na/Ca exchanger; I_SERCA; Na/K pump; Kir;
Gap Junctions:
Receptor(s):
Gene(s): Nav1.1 SCN1A; Cav3.3 CACNA1I; Cav1.3 CACNA1D; Cav1.2 CACNA1C;
Transmitter(s):
Simulation Environment: NEURON; MATLAB; Python;
Model Concept(s): 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 A; I K; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow; Na/Ca exchanger; I_SERCA; Na/K pump; Kir;
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pleiotropy
almog
cells
BK.mod *
ca_h.mod
ca_r.mod
cad.mod *
epsp.mod *
ih.mod *
kfast.mod
kslow.mod
na.mod
SK.mod *
best.params *
calcifcurves.py
calcsteadystate.py
cc_run.hoc *
collectfig1.py
collectfig2.py
fig1_curves.mat
fig2_curves.mat
findDCshortthreshold.py
main.hoc *
model.hoc *
mosinit.hoc *
mutation_stuff.py
myrun.hoc *
mytools.py *
params.hoc *
runme.sh *
scalings.sav
                            
TITLE hyperpolarization-activated current (H-current) 

COMMENT
Based on Williams and Stuart J. Neurophysiol 83:3177,2000
ENDCOMMENT

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	SUFFIX iH
	USEION h READ eh WRITE ih VALENCE 1
	RANGE gbar, h_inf, tau, ih  
	GLOBAL t0,t1,off, slo, offt1, offt2, slot1, slot2
	GLOBAL q10, temp, tadj, vmin,vmax
	
}

UNITS {
	(mA) 	= (milliamp)
	(mV) 	= (millivolt)
	(molar)	= (1/liter)
	(mM) 	= (millimolar)
	(pS) = (picosiemens)
	(um) = (micron)

}

PARAMETER {
	v		(mV)
	
	celsius		(degC)
	eh	   (mV)     
	gbar	= 0.0	(pS/um2)

	off = -91       (mV)   		: V1/2 of activation	
	slo=6		(mV)	 	: slope of activation
	
	t0 = 2542.5883549	(ms) 	: parameters for time constant of activation    
	t1 = 11.40250855	(ms)     
	offt1 = 0		(mV)
	offt2 = 0		(mV)
	slot1 = 40.1606426		(mV)     
	slot2 = 16.1290323		(mV)
			
	temp = 21	(degC)		: original temp 
	q10  = 2.3			: temperature sensitivity
	vmin = -120 (mV)
	vmax = 100 (mV)     
	
}


ASSIGNED {
	ih		(mA/cm2)
        h_inf
        tau        (ms)
	tadj
	
}

STATE { h }


INITIAL {
	rates(v)
      	h = h_inf
}

BREAKPOINT { 
	SOLVE states METHOD cnexp
      	ih = (1e-4) * gbar * h * (v-eh)
}


DERIVATIVE states  { 

	rates(v) 
	h' = (h_inf-h)/tau  
}


PROCEDURE rates( v (mV)) {

	tadj= q10^((celsius-22)/10)
	h_inf = 1/(1+exp((v-off)/slo))	
        tau = 1/(tadj*(exp(-(v-offt1)/slot1)/t0+exp((v-offt2)/slot2)/t1))
}