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Motor cortex microcircuit simulation based on brain activity mapping (Chadderdon et al. 2014)

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Accession:146949
"... We developed a computational model based primarily on a unified set of brain activity mapping studies of mouse M1. The simulation consisted of 775 spiking neurons of 10 cell types with detailed population-to-population connectivity. Static analysis of connectivity with graph-theoretic tools revealed that the corticostriatal population showed strong centrality, suggesting that would provide a network hub. ... By demonstrating the effectiveness of combined static and dynamic analysis, our results show how static brain maps can be related to the results of brain activity mapping."
Reference:
1 . Chadderdon GL, Mohan A, Suter BA, Neymotin SA, Kerr CC, Francis JT, Shepherd GM, Lytton WW (2014) Motor cortex microcircuit simulation based on brain activity mapping. Neural Comput 26:1239-62 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex M1 L2/6 pyramidal intratelencephalic GLU cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Laminar Connectivity;
Implementer(s): Lytton, William [bill.lytton at downstate.edu]; Neymotin, Sam [Samuel.Neymotin at nki.rfmh.org]; Shepherd, Gordon MG [g-shepherd at northwestern.edu]; Chadderdon, George [gchadder3 at gmail.com]; Kerr, Cliff [cliffk at neurosim.downstate.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex M1 L2/6 pyramidal intratelencephalic GLU cell; GabaA; AMPA; NMDA; Gaba; Glutamate;
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src
README
infot.mod *
intf6.mod *
intfsw.mod *
matrix.mod
misc.mod *
nstim.mod *
staley.mod *
stats.mod *
vecst.mod *
boxes.hoc *
col.hoc
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
filtutils.hoc *
gcelldata.hoc
gmgs102.nqs
grvec.hoc *
infot.hoc *
init.hoc
intfsw.hoc *
labels.hoc *
load.py
local.hoc *
main.hoc
misc.h *
miscfuncs.py
network.hoc
neuroplot.py *
nload.hoc
nqs.hoc *
nqsnet.hoc
nrnoc.hoc *
params.hoc
run.hoc
samutils.hoc *
saveoutput.hoc
saveweights.hoc
setup.hoc *
simctrl.hoc *
spkts.hoc *
staley.hoc *
stats.hoc *
stdgui.hoc *
syncode.hoc *
updown.hoc *
wdmaps2.nqs
xgetargs.hoc *
                            
// $Id: nqsnet.hoc,v 1.65 2010/09/07 18:56:17 samn Exp $

print "Loading nqsnet..."

//      pre-id  post-id  pre#  post#   distance weight  syn-id   nc ptr  wt1 (eg AMPA+NMDA)
objref nq[2],sq[CTYPi][CTYPi],cp
obfunc mkcp0 () { localobj lo
  lo = new NQS("PRID","POID","STYP","PIJ","DIV","CONV","NSYN","NPRE")
  lo.useslist("PRID",CTYP) lo.useslist("POID",CTYP) lo.useslist("STYP",STYP)
  return lo
}

// CODE: PRID,POID,INCOL,COL1,COL2
obfunc mksp () { localobj lo
  lo=new NQS("CODE","PR","PO","DEL","WT0","WT1") // CODE==PRID(1),POID(2),COLA(3),COLB(4)
  lo.coddec("CODE")
  // lo.useslist("PRID",CTYP) lo.useslist("POID",CTYP) 
  return lo
}
sp=mksp()

//* Numbers and connectivity params

// layer return layer location with 'sublayer' defined by Inhib (+0.5) or other suffix
// E or I should be 1st letter of name, suffix letter will ideally dichotomize into late
// alphabet or early alphabet
func layer () { local x,in,la
  la=0
  if (sscanf(CTYP.o($1).s,"%c%d%c",&in,&x,&la)<2) {
  	x=-1
  	if (!strcmp(CTYP.o($1).s,"IRE")) x=7 // Thalamic reticular nucleus
  	if (!strcmp(CTYP.o($1).s,"TC")) x=8 // Thalamic relay nucleus
  	return x
  	}
  if (x==23) x=3 // layer 2/3
  if (in==73) x+=0.5 // ascii 73 is 'I'
  if (la>77) x+=0.2 // <='M'
  return x
}

//* routines
//** styp() sets synapse type based on presynaptic cell
func styp () { local pr,po
  pr=$1 po=$2
  if (pr==IN && po==IN) { return GA 
  } else if (pr==IN) { return IX
  } else if (pr==SU || pr==DP) { return EX
  } else if (pr==SM) { return AM
  } else if (strm(CTYP.o[pr].s,"^E")) { return EX
  } else if (strm(CTYP.o[pr].s,"^I")) { return IX
  } else printf("styp ERR %s->%s not classified",CTYP.object(pr).s,CTYP.object(po).s)
}

//** ellfld() place the cells inside an ellipse
// r for an ellipse = a*b/sqrt((a*sin(theta))^2 + (b*cos(theta))^2)
proc ellfld () { local a,b,ii,jj,p,seed localobj xv,yv,xo
  seed=239023229
  a=1 b=2
  p=allocvecs(xv,yv) vrsz(allcells*10,xv,yv)
  xv.setrnd(4,2*a,seed) yv.setrnd(4,2*b) xv.sub(a) yv.sub(b)
  jj=0
  for vtr2(&x,&y,xv,yv,&ii) {
    if (a*x^2+b*y^2<1) { ce.o(jj).xloc=x ce.o(jj).yloc=y jj+=1 }
    if (jj==ce.count) break
  }
  print ii,jj
  if (jj!=ce.count) print "Not filled"
  dealloc(p)
}

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