Large scale model of the olfactory bulb (Yu et al., 2013)

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Accession:144570
The readme file currently contains links to the results for all the 72 odors investigated in the paper, and the movie showing the network activity during learning of odor k3-3 (an aliphatic ketone).
Reference:
1 . Yu Y, McTavish TS, Hines ML, Shepherd GM, Valenti C, Migliore M (2013) Sparse distributed representation of odors in a large-scale olfactory bulb circuit. PLoS Comput Biol 9:e1003014 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Channel/Receptor; Dendrite;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral cell; Olfactory bulb main interneuron granule MC cell;
Channel(s): I Na,t; I A; I K;
Gap Junctions:
Receptor(s): NMDA; Glutamate; Gaba;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Pattern Recognition; Activity Patterns; Bursting; Temporal Pattern Generation; Oscillations; Synchronization; Active Dendrites; Detailed Neuronal Models; Synaptic Plasticity; Action Potentials; Synaptic Integration; Unsupervised Learning; Olfaction;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu]; Migliore, Michele [Michele.Migliore at Yale.edu];
Search NeuronDB for information about:  Olfactory bulb main mitral cell; Olfactory bulb main interneuron granule MC cell; NMDA; Glutamate; Gaba; I Na,t; I A; I K; Gaba; Glutamate;
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YuEtAl2012
readme.html
ampanmda.mod
fi.mod
kamt.mod *
kdrmt.mod *
naxn.mod *
ThreshDetect.mod *
.hg_archival.txt
allsynhinton.hoc *
antest.ses *
clear.hoc *
connect.hoc
control.ses
default.hoc
granule.hoc *
hinton.hoc
init.hoc *
iterator.hoc *
lindgren.job
lptiter.hoc
mgrs.hoc
michele_movie.hoc
mitral.hoc
mosinit.hoc *
net.hoc
odors.txt
odors-forsim500-kensaku.txt
param.hoc
parinit.hoc
pattern.hoc
perfrun.hoc
record.hoc
show.hoc
showstim.hoc
showw.hoc
somesyn.hoc *
spike2file.hoc
spkdat2bin.hoc
split.hoc
start.hoc
start.ses *
stim-AB-rnd-500mt.hoc
stim-o11o12.hoc
stim-o14.hoc
stim-o26.hoc
stim-o26d1-mnoise5hz-gnoise-5s.hoc
stim-o5high-o6low.hoc
stim-odors-AB-seq.hoc
stim-pair.hoc
stim-seq-rnd.hoc
subset.hoc
subset_control.ses *
viewspikes.hoc
viewspikes1.hoc
weight_movie.hoc *
weightsave.hoc
                            
// assume show.hoc already loaded (via start.hoc).
// i.e sc_ is a ShowConnect instance

begintemplate RecordInfo
public gid, sec, x, record, yvec, tvec, name
objref vv, yvec, tvec, this
external Mitral, Granule, nmitral
strdef sec
proc init() {
	gid = $1
	sec = $s2
	x = $3
}

proc record() {localobj cell, s, pc
  pc = new ParallelContext()
  yvec = new Vector()
  tvec = new Vector()
  cell = pc.gid2cell(gid)
  s = new String()
  sprint(s.s, "%s.%s {yvec.record(&v(%g)) tvec.record(&t)}", cell, sec, x)
  execute(s.s, this)
}

obfunc name() {localobj s
  s = new String()
  if (gid < nmitral) {
	  sprint(s.s, "Mitral(%d).%s(%g)", gid, sec, x)
  }else{
	  sprint(s.s, "Granule(%d).%s(%g)", gid-nmitral, sec, x)
  }
  return s
}
endtemplate RecordInfo

objref recinfo
recinfo = new List(0)

// record soma voltage for arglist of mitral indices
proc rm() {local i
	for i=1, numarg() {
		sc_.msel.x[$i] = 1
		recinfo.append(new RecordInfo($i, "soma", 0.5))
	}
}

// record soma voltage for arglist of granule indices
proc rg() {local i
	for i=1, numarg() {
		sc_.gsel.x[$i] = 1
		recinfo.append(new RecordInfo($i+nmitral, "soma", 0.5))
	}
}

// record mitral secden voltage at positions given by arglist of granule
// indices. (first arg is mitral index). If mitral does not have a position
// at an indicated granule index, then that granule index arg is ignored

proc rmx() {local i, x  localobj sden
	return // not implemented yet
	sc_.msel.x[$1] = 1
	for i=2, numarg() {
		recinfo.append($1, sden.s, x)
	}
}

proc go() {local i
	sc_.create_subnet()
	for i=0, recinfo.count-1 {
		recinfo.o(i).record()
	}
	run()
	pfile("tplot.dat")
}

proc pfile() {local i, sz  localobj f
	f = new File()
	f.wopen($s1)
	sz = recinfo.o(0).tvec.size
	f.printf("nrow ncol\n")
	f.printf("%d %d\n", sz, recinfo.count + 1)
	f.printf("t\n")
	for i=0, recinfo.count-1 {
		f.printf("%s\n", recinfo.o(i).name().s)
	}
	for i=0, sz-1 {
		f.printf("%g", recinfo.o(0).tvec.x[i])
		for j=0, recinfo.count-1 {
			f.printf(" %g", recinfo.o(j).yvec.x[i])
		}
		f.printf("\n")
	}
}