Ih tunes oscillations in an In Silico CA3 model (Neymotin et al. 2013)

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Accession:151282
" ... We investigated oscillatory control using a multiscale computer model of hippocampal CA3, where each cell class (pyramidal, basket, and oriens-lacunosum moleculare cells), contained type-appropriate isoforms of Ih. Our model demonstrated that modulation of pyramidal and basket Ih allows tuning theta and gamma oscillation frequency and amplitude. Pyramidal Ih also controlled cross-frequency coupling (CFC) and allowed shifting gamma generation towards particular phases of the theta cycle, effected via Ih’s ability to set pyramidal excitability. ..."
Reference:
1 . Neymotin SA, Hilscher MM, Moulin TC, Skolnick Y, Lazarewicz MT, Lytton WW (2013) Ih tunes theta/gamma oscillations and cross-frequency coupling in an in silico CA3 model. PLoS One 8:e76285 [PubMed]
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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 Na,t; I A; I K; I K,leak; I h; I K,Ca; I Sodium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA; Glutamate;
Gene(s): HCN1; HCN2;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Oscillations; Brain Rhythms; Conductance distributions; Multiscale;
Implementer(s): Lazarewicz, Maciej [mlazarew at gmu.edu]; Neymotin, Sam [Samuel.Neymotin at nki.rfmh.org];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; GabaA; AMPA; NMDA; Glutamate; I Na,t; I A; I K; I K,leak; I h; I K,Ca; I Sodium; I Potassium; Gaba; Glutamate;
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ca3ihdemo
readme.txt
CA3ih.mod
CA3ika.mod
CA3ikdr.mod
CA3ina.mod
caolmw.mod *
HCN1.mod
icaolmw.mod *
iholmw.mod
ihstatic.mod
kcaolmw.mod *
kdrbwb.mod *
misc.mod *
MyExp2SynBB.mod *
MyExp2SynNMDABB.mod *
nafbwb.mod *
stats.mod *
vecst.mod *
aux_fun.inc *
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
geom.py
grvec.hoc *
init.hoc
labels.hoc *
local.hoc *
misc.h *
network.py
nqs.hoc *
nrnoc.hoc *
params.py
pyinit.py *
pywrap.hoc
run.py
sim.py
simctrl.hoc *
stats.hoc *
syncode.hoc *
xgetargs.hoc *
                            
// $Id: pywrap.hoc,v 1.31 2012/08/04 03:19:13 samn Exp $ 

//* variables
declare("INITPYWRAP",0) // whether initialized properly

func initpywrap () { localobj pjnk
  INITPYWRAP=0
  if(2!=name_declared("p")){printf("initpywrap ERR0A: PythonObject p not found in python.hoc!\n") return 0}
  print p  
  pjnk=new PythonObject()
  if(!isojt(p,pjnk)){printf("initpywrap ERR0B: PythonObject p not found in python.hoc!\n")}
  if(!nrnpython("import numpy")) {printf("pypmtm ERR0C: could not import numpy python library!\n") return 0}
  INITPYWRAP=1
  return 1
}

initpywrap()

//** pypmtm(vec,samplingrate[,nw])
// this function calls python version of pmtm, runs multitaper power spectra, returns an nqs
obfunc pypmtm () { local sampr,spc,nw localobj vin,str,nqp,ptmp
  if(!INITPYWRAP) {printf("pypmtm ERR0A: python.hoc not initialized properly\n") return nil}
  if(!nrnpython("from mtspec import *")) {printf("pypmtm ERR0B: could not import mtspec python library!\n") return nil}  
  if(numarg()==0) {printf("pypmtm(vec,samplingrate)\n") return nil}
  vin=$o1 sampr=$2 str=new String()
  p.vjnk = vin.to_python()
  p.vjnk = p.numpy.array(p.vjnk)
  spc = 1.0 / sampr // "spacing"
  nw=4 if(numarg()>2) nw=$3
  sprint(str.s,"[Pxx,w]=mtspec(vjnk,%g,%d)",spc,nw)
  nrnpython(str.s)
  nqp=new NQS("f","pow")
  nqp.v.from_python(p.w)
  nqp.v[1].from_python(p.Pxx)
  return nqp
}

//** pypsd(vec,samplingrate[,NFFT])
// this function calls python version of psd (power-spectral density)
// returns an nqs with psd
obfunc pypsd () { local sampr,NFFT localobj v1,str,nqp
  if(!INITPYWRAP) {printf("pypsd ERR0A: python.hoc not initialized properly\n") return nil}
  if(!nrnpython("from matplotlib.mlab import psd")) {printf("pypsd ERR0B: could not import psd from matplotlib.mlab!\n") return nil}  
  // nrnpython("from matplotlib.mlab import window_none")
  if(numarg()==0) {printf("pypsd(vec,samplingrate)\n") return nil}
  v1=$o1 sampr=$2 str=new String() 
  {p.vjnk1=v1.to_python() p.vjnk1=p.numpy.array(p.vjnk1)}
  if(numarg()>2) NFFT=$3 else NFFT=v1.size
  if(sz%2==1) sz+=1
  sprint(str.s,"[Pxx,freqs]=psd(vjnk1,Fs=%g,NFFT=%d)",sampr,NFFT)
  nrnpython(str.s)
  nqp=new NQS("f","pow")
  nqp.v[0].from_python(p.freqs)
  nqp.v[1].from_python(p.Pxx)
  return nqp
}

//* nrnpsd(vector,samplingrate) - calculates PSD and returns as an NQS object
// uses NEURON spctrm function
obfunc nrnpsd () { local sampr localobj vec,nqp
  vec=$o1 sampr=$2
  nqp=new NQS("f","pow")
  nqp.v[1].spctrm(vec)
  nqp.v.indgen(0,sampr/2,(sampr/2)/nqp.v[1].size)
  nqp.v.resize(nqp.v[1].size)
  return nqp
}