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
                            
strdef ExperimentName, CellName,CellFileName,ApicalDendSectionName


//---------------------------------------------------------------------
// data to change in each model or execution-----------------------------
//-------------------------------------------------------------------------
CellName  =  "A140612.hoc"  
ExperimentName = "A140612cont.data"  
ApicalDendSectionName = "apic"  

celsius = 34 

NP = 37                        //num of parameters 

//----------------------------------------------------------------------------

// general parameters
objref SomaStimSec,DendStimSec
Vrest = -62				// resting potential in mV
sprint(CellFileName,"cells/%s",CellName)
cm_myelin = 0.04
g_pas_node = 0.02
v_init    = -62
Ek = -100
Ena = 60
Eca = 130

// This is rough initial parameter set. IT is overwritten by parameters loaded from best.params


//passive
ra  = 68.16690
rm  = 18017.30000
c_m  = 1.43870
epas_sim  = -31.40480
//gih
gih_end= 271.90500
gih_x2= 382.51900
gih_alpha=-0.08090
gih_start= 22.51460
ih_q10=2
//kslow
gkslow_start=2.03452
gkslow_alpha=-0.00986
gkslow_beta= 127.82800
//kfast
gka_start= 20.34520
gka_alpha= -0.00297
gka_beta= 320.43100
//na
gna_soma =128.14300
gna_api = 2.69229
dist_na = 687.53800
na_shift1 =-5.56301
na_shift2 =-4.52361
na_taum_scale=1
na_tauh_scale=1

//Ca
pcah_soma=1.33e-3
pcah_api=pcah_soma
dist_cah=600
cah_qm =2
ca_qh=2
cah_shift=0
cah_shifth=0

pcar_soma=0.27e-3
pcar_api=pcar_soma
dist_car=600
car_qh=1
car_qm=1
car_shift=0
car_shifth=0

//axon parameters
gkslow_node=1500
gka_node=1000
gna_node=30000
shift_na_act_axon=7
shift_na_inact_axon=3