In silico hippocampal modeling for multi-target pharmacotherapy in schizophrenia (Sherif et al 2020)

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Accession:258738
"Using a hippocampal CA3 computer model with 1200 neurons, we examined the effects of alterations in NMDAR, HCN (Ih current), and GABAAR on information flow (measured with normalized transfer entropy), and in gamma activity in local field potential (LFP). We found that altering NMDARs, GABAAR, Ih, individually or in combination, modified information flow in an inverted-U shape manner, with information flow reduced at low and high levels of these parameters. Theta-gamma phase-amplitude coupling also had an inverted-U shape relationship with NMDAR augmentation. The strong information flow was associated with an intermediate level of synchrony, seen as an intermediate level of gamma activity in the LFP, and an intermediate level of pyramidal cell excitability"
Reference:
1 . Sherif MA, Neymotin SA, Lytton WW (2020) In silico hippocampal modeling for multi-target pharmacotherapy in schizophrenia. NPJ Schizophr 6:25 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; Hippocampus CA3 stratum oriens lacunosum-moleculare interneuron;
Channel(s): I h;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s): NR2A GRIN2A;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Schizophrenia;
Implementer(s): Sherif, Mohamed [mohamed.sherif.md at gmail.com];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; AMPA; NMDA; I h; Gaba; Glutamate;
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CA3modelCode_npjSchizophrenia_September2020--main
data
README.md
CA1ih.mod
CA1ika.mod *
CA1ikdr.mod *
CA1ina.mod *
cagk.mod *
caolmw.mod *
capr.mod *
expsynstdp.mod
Gfluctp.mod *
HCN1.mod *
HCN2.mod
IA.mod
icaolmw.mod *
icapr.mod *
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iholmw.mod *
ihpyrkop.mod *
ihstatic.mod *
infot.mod *
kahppr.mod *
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kapyrkop.mod *
kcaolmw.mod *
kcpr.mod *
kdrbwb.mod *
kdrolmkop.mod *
kdrpr.mod *
kdrpyrkop.mod *
km.mod
misc.mod *
MyExp2Syn.mod *
MyExp2SynAlpha.mod *
MyExp2SynBB.mod *
MyExp2SynNMDA.mod *
MyExp2SynNMDABB.mod *
nafbwb.mod *
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nafpr.mod *
nafpyrkop.mod *
samnutils.mod
sampen.mod
stats.mod
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analysisPlottingCode.py
aux_fun.inc *
batch.py
conf.py
declist.hoc *
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fig1sample.png
fig1simulationConfig.cfg
geom.py
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init.hoc
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misc.h
network.py
nqs.hoc *
nqs_utils.hoc *
nrnoc.hoc *
params.py
psd.py
pyinit.py
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run.py
runone.py
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xgetargs.hoc *
                            
: $Id: kdrpr.mod,v 1.1 2009/11/05 15:10:35 samn Exp $ 
COMMENT

//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//
// NOTICE OF COPYRIGHT AND OWNERSHIP OF SOFTWARE
//
// Copyright 2007, The University Of Pennsylvania
// 	School of Engineering & Applied Science.
//   All rights reserved.
//   For research use only; commercial use prohibited.
//   Distribution without permission of Maciej T. Lazarewicz not permitted.
//   mlazarew@seas.upenn.edu
//
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

ENDCOMMENT


NEURON {

	SUFFIX kdrpr
	USEION k WRITE ik
	RANGE gkdr, ik
}
	
UNITS {

	(mA) = (milliamp)
	(mV) = (millivolt)
	(mS) = (millisiemens)
}

PARAMETER {

    gkdr =  15 (mS/cm2)
    ek   = -75 (mV)
}
    
ASSIGNED {

    v       (mV)
    ik      (mA/cm2)
    ninf    (1)
    taun    (ms)
}

STATE { n }

INITIAL { 

    rates(v)
    n  = ninf
}

BREAKPOINT {

	SOLVE states METHOD cnexp
	
	ik = (1e-3) * gkdr * n * (v-ek)
}


DERIVATIVE states { 

    rates(v)
    n' = (ninf-n)/taun
}

PROCEDURE rates(v(mV)) { LOCAL a, b

    a = fun3(v,  -24.9, -0.016,   -5)
    b = fun1(v,  -40,    0.25,   -40)
    
    ninf = a/(a+b)
    taun = 1.0/(a+b)
}

INCLUDE "aux_fun.inc"

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