Layer V pyramidal cell functions and schizophrenia genetics (Mäki-Marttunen et al 2019)

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Accession:249463
Study on how GWAS-identified risk genes of shizophrenia affect excitability and integration of inputs in thick-tufted layer V pyramidal cells
Reference:
1 . Mäki-Marttunen T, Devor A, Phillips WA, Dale AM, Andreassen OA, Einevoll GT (2019) Computational modeling of genetic contributions to excitability and neural coding in layer V pyramidal cells: applications to schizophrenia pathology Front. Comput. Neurosci. 13:66
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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: Neocortex;
Cell Type(s):
Channel(s): I A; I M; I h; I K,Ca; I Calcium; I A, slow; I Na,t; I Na,p; I L high threshold; I T low threshold;
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Gene(s):
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON; Python;
Model Concept(s): Schizophrenia; Dendritic Action Potentials; Action Potential Initiation; Synaptic Integration;
Implementer(s): Maki-Marttunen, Tuomo [tuomo.maki-marttunen at tut.fi];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I M; I h; I K,Ca; I Calcium; I A, slow; Gaba; Glutamate;
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l5pc_scz
almog
cells
README.html
BK.mod *
ca_h.mod
ca_r.mod
cad.mod *
epsp.mod *
ih.mod *
kfast.mod
kslow.mod
na.mod
ProbAMPANMDA2.mod *
ProbUDFsyn2.mod *
SK.mod *
best.params *
calcifcurves2.py
calcifcurves2_comb_one.py
calcnspikesperburst.py
calcsteadystate.py
calcupdownresponses.py
cc_run.hoc *
coding.py
coding_comb.py
coding_nonprop_somaticI.py
coding_nonprop_somaticI_comb.py
collectifcurves2_comb_one.py
collectthresholddistalamps.py
combineppicoeffs_comb_one.py
drawfigcomb.py
drawnspikesperburst.py
findppicoeffs.py
findppicoeffs_merge.py
findppicoeffs_merge_comb_one.py
findthresholdbasalamps_coding.py
findthresholddistalamps.py
findthresholddistalamps_coding.py
findthresholddistalamps_comb.py
main.hoc *
model.hoc *
model_withsyns.hoc
mosinit.hoc *
mutation_stuff.py
myrun.hoc *
myrun_withsyns.hoc
mytools.py
params.hoc *
protocol.py
savebasalsynapselocations_coding.py
savesynapselocations_coding.py
scalemutations.py
scalings_cs.sav
setparams.py
synlocs450.0.sav
                            
:modified 1/7/2007 by Chris Deister for the GP neuron (to remove some of the background current that existed in Mercer 2007)

NEURON {
	SUFFIX sk
	USEION k READ ek WRITE ik
        USEION ca READ cai
        RANGE  gbar,gkahp,ik, inf,tau,g
        GLOBAL Cq10
}

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

PARAMETER {
	gbar = 0	(pS/um2)
        n = 4
        cai = 50.e-6	(mM)
        b0inv = 16.6666667	(ms)			:1/b0
	celsius = 37	(degC)
	offc = 0.04635023	(mM)                    :(b0/a0)^4
	sloc = 4.0
	Cq10 = 3
}

STATE {	w }

ASSIGNED {
	ik	(mA/cm2)
        g	(pS/um2)
        inf
        tau	(ms)
	a	(1/ms)
        v	(mV)
        ek	(mV)
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	g = gbar*w
	ik = (1e-4)* g*(v-ek)
}

INITIAL {
	rate(cai)
	w=inf
}

DERIVATIVE state {
	rate(cai)
	w' = (inf - w)/tau
}

PROCEDURE rate(cai (mM)) {
	LOCAL q10
	q10 = Cq10^((celsius - 22 (degC))/10 (degC) )
	tau = q10*b0inv/(1+(cai/offc)^sloc)
	inf = 1/(1+(offc/cai)^sloc)
}