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
                            
TITLE decay of internal calcium concentration
:
: Internal calcium concentration due to calcium currents and pump.
: Differential equations.
:
: Simple model of ATPase pump with 3 kinetic constants (Destexhe 92)
:     Cai + P <-> CaP -> Cao + P  (k1,k2,k3)
: A Michaelis-Menten approximation is assumed, which reduces the complexity
: of the system to 2 parameters: 
:       kt = <tot enzyme concentration> * k3  -> TIME CONSTANT OF THE PUMP
:	kd = k2/k1 (dissociation constant)    -> EQUILIBRIUM CALCIUM VALUE
: The values of these parameters are chosen assuming a high affinity of 
: the pump to calcium and a low transport capacity (cfr. Blaustein, 
: TINS, 11: 438, 1988, and references therein).  
:
: Units checked using "modlunit" -> factor 10000 needed in ca entry
:
: VERSION OF PUMP + DECAY (decay can be viewed as simplified buffering)
:
: All variables are range variables
:
: adopted from the lower model by AS 102199
:
: This mechanism was published in:  Destexhe, A. Babloyantz, A. and 
: Sejnowski, TJ.  Ionic mechanisms for intrinsic slow oscillations in
: thalamic relay neurons. Biophys. J. 65: 1538-1552, 1993)
:
: Written by Alain Destexhe, Salk Institute, Nov 12, 1992
:

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

NEURON {
	SUFFIX cad
	USEION ca READ ica, cai WRITE cai
	RANGE ca,depth,cainf,taur
}

UNITS {
	(molar) = (1/liter)			: moles do not appear in units
	(mM)	= (millimolar)
	(um)	= (micron)
	(mA)	= (milliamp)
	(msM)	= (ms mM)
	FARADAY = (faraday) (coulomb)
}


PARAMETER {
	depth	= .1	(um)		: depth of shell
	taur	= 80	(ms)		: rate of calcium removal, changed from 200 to 80 (H.Markram)
	cainf	= 100e-6(mM)
	cai		(mM)
	gamma = 1.0
}

STATE {
	ca		(mM) 
}

INITIAL {
	ca = cainf
}

ASSIGNED {
	ica		(mA/cm2)
	drive_channel	(mM/ms)
}
	
BREAKPOINT {
	SOLVE state METHOD cnexp
}

DERIVATIVE state { 

	drive_channel =  - (10000) * ica * gamma / (2 * FARADAY * depth)
	if (drive_channel <= 0.) { drive_channel = 0. }	: cannot pump inward

	ca' = drive_channel + (cainf-ca)/taur
	cai = ca
}