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
Ca_HVA.mod *
Ca_LVAst.mod *
CaDynamics_E2.mod *
epsp.mod *
Ih.mod *
Im.mod *
K_Pst.mod *
K_Tst.mod *
Nap_Et2.mod
NaTa_t.mod
NaTs2_t.mod
SK_E2.mod *
SKv3_1.mod *
collectscalings.py
collectthresholddistalamps.py
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
                            
: SK-type calcium-activated potassium current
: Reference : Kohler et al. 1996

NEURON {
       SUFFIX SK_E2
       USEION k READ ek WRITE ik
       USEION ca READ cai
       RANGE gSK_E2bar, gSK_E2, ik, offc, zTau, sloc
}

UNITS {
      (mV) = (millivolt)
      (mA) = (milliamp)
      (mM) = (milli/liter)
}

PARAMETER {
          v            (mV)
          gSK_E2bar = .000001 (mho/cm2)
          zTau = 1              (ms)
          ek           (mV)
          cai          (mM)
          offc = 0.00043 (mM)
	  sloc = 4.8
}

ASSIGNED {
         zInf
         ik            (mA/cm2)
         gSK_E2	       (S/cm2)
}

STATE {
      z   FROM 0 TO 1
}

BREAKPOINT {
           SOLVE states METHOD cnexp
           gSK_E2  = gSK_E2bar * z
           ik   =  gSK_E2 * (v - ek)
}

DERIVATIVE states {
        rates(cai)
        z' = (zInf - z) / zTau
}

PROCEDURE rates(ca(mM)) {
          if(ca < 1e-7){
	              ca = ca + 1e-07
          }
          zInf = 1/(1 + (offc / ca)^sloc)
}

INITIAL {
        rates(cai)
        z = zInf
}

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