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

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"... 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."
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 V1 pyramidal corticothalamic L6 cell; Neocortex M1 pyramidal intratelencephalic L2-5 cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Laminar Connectivity;
Implementer(s): Lytton, William [billl at]; Neymotin, Sam [samn at]; Shepherd, Gordon MG [g-shepherd at]; Chadderdon, George [gchadder3 at]; Kerr, Cliff [cliffk at];
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex M1 pyramidal intratelencephalic L2-5 cell; GabaA; AMPA; NMDA; Gaba; Glutamate;
infot.mod *
intf6.mod *
intfsw.mod *
misc.mod *
nstim.mod *
staley.mod *
stats.mod *
vecst.mod *
boxes.hoc *
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
filtutils.hoc *
grvec.hoc *
infot.hoc *
intfsw.hoc *
labels.hoc *
local.hoc *
misc.h *
network.hoc *
nqs.hoc *
nrnoc.hoc *
samutils.hoc *
setup.hoc *
simctrl.hoc *
spkts.hoc *
staley.hoc *
stats.hoc *
stdgui.hoc *
syncode.hoc *
updown.hoc *
xgetargs.hoc *
// $Id: spkts.hoc,v 1.86 2010/07/10 02:32:11 samn Exp $

print "Loading spkts.hoc..."

// ancillary programs for handling vectors


//* transfer a file into a list of strings
// usage 'f2slist(list,file)'
proc f2slist() { local i
  if (! tmpfile.ropen($s2)) { print "Can't open ",$s2
    return }
  while (tmpfile.gets(temp_string_)>0) {
    sfunc.head(temp_string_,"\n",temp_string_) // chop
    tmpobj = new String(temp_string_)

//* spkts(attrnum[,flag,min,max]) graph spikes from the vectors

thresh = -20    // threshold for deciding which are spikes
burstlen = 1.4  // duration of spike or burst, don't accept another till after this time

proc spkts_call() {}// callback function stub
proc spkts () { local cnt, attrnum, ii, pstep, jj, num, time0, flag, min, max, tst
  revec(vec,vec1) // store times and indices respectively
  if (numarg()==0) { print "spkts(attrnum[,flag,min,max])\n\tflag 0: graph, flag 1: save vec1,vec to veclist, flag 2: save inds (vec1) and times (vec)" // infomercial
    return }
  panobj = GRV[attrnum]
  if (attrnum==0) { cnt=printlist.count() } else { cnt = panobj.llist.count() }
  pstep = panobj.printStep
  if (numarg()>1) { flag = $2 } else { flag = 0 }
  if (numarg()>2) { min = $3 } else { min = 0 }
  if (numarg()>3) { max = $4 } else { max = cnt-1 }
  if (flag==0){
  for ii=min,max {
    if (attrnum==0) { 
      if (panobj.printStep==-2) tvec = printlist.object(ii).tvec
      if (panobj.printStep==-1) tvec = panobj.tvec
    } else {
      panobj.rv_readvec(ii,vrtmp)  // pick up vector from file
      if (panobj.printStep<0) tvec = panobj.tvec
    if (panobj.printStep>=0) { // make a tvec
      if (!isobj(tvec,"Vector")) { print "ERR0 spkts(): tvec not a vector" return }

    if (panobj.printStep<0) { // a tvec
      tst = vec.max
    } else {
      tst = pstep*vrtmp.size()         // calc the tst
  if (flag==1) { savevec(vec1) savevec(vec) }
  if (flag<=0) {
    vec1.mark(graphItem,vec,"O",panobj.line)  // graph all the times

// spkts1(tvec,vec,timev,indexv,index)
proc spkts1 () { local ind,tm,ix
  ind=tm=allocvecs(2) tm+=1
  spkts_call()  // place to reset thresh or do other manipulations
  mso[tm].xing($o2,$o1,thresh) // times
  if (numarg()==5) {
    mso[ind].resize(mso[tm].size)  // scratch vector stores index
    $o3.append(mso[tm])     // add the times for this to end of vec
    $o4.append(mso[ind])  // add same index for each spk to end of vec1
  } else {

//* parse_spkts()
// pull the vec and vec1 files from spkts apart and put in alloc'ed vectors
func parse_spkts () { local p,q
  p=allocvecs(vec1.max+2) q=p+1
  for (ii=0;ii<=vec1.max;ii+=1) {
    q += 1
  return p+1

proc line_spkts () { local ii,min,max,xmax,skip
  skip = $1
  if (numarg()==3) { min=$2 max=$3 } else {
    min = int(graphItem.size(3)+1) max = int(graphItem.size(4)) }
  xmax = graphItem.size(2)
  for (ii=min;ii<max;ii=ii+skip) {

burst_maxfreq = 30
calc_ave = 0

//** calcspkts(flag,index)
// run after spkts() so vec contains the times, vec1 contains the
// indices
proc calcspkts () { local ii,jj,flag,index,p1,p2,mn,mx
  p1 = allocvecs(2,1000) p2 = p1+1
  if (numarg()==0) {
    print "To be run after spkts(). \
Assumes times in vec, indices in vec1. \
calcspkts(flag,min,max)\nflags:\t1\tspk times\n\t2\tspk freq \
\t3\tburst times\n\t4\tburst freq\nset calc_ave to get averages for freqs"
  // vec contains the times, vec1 contains the indices
  flag = $1
  mn = $2
  if (numarg()==3) { mx=$3 } else { mx=mn }
  for index=mn,mx {
    if (flag==1) {  
      printf("SPKS for #%d: ",index)
      for jj=0,mso[p1].size()-1 {printf("%g ",mso[p1].x[jj])}
    } else if (flag==2) {  
      printf("FREQ for #%d: ",index)
      for jj=0,mso[p1].size()-2 { 
        pushvec(mso[p2],1000./(mso[p1].x[jj+1]-mso[p1].x[jj])) }
      if (calc_ave) { print mso[p2].mean } else { vlk(mso[p2]) }
    } else if (flag==3) {  
      printf("BTIMES for #%d: ",index)
      burst_time = mso[p1].x[0]
      for jj=1,mso[p1].size()-1 {
        if (1000./(mso[p1].x[jj]-burst_time) < burst_maxfreq) {
          printf("%g ",burst_time)
          burst_time = mso[p1].x[jj]
    } else if (flag==4) {  
      printf("BFREQ for #%d: ",index)
      burst_time = mso[p1].x[0]
      for jj=1,mso[p1].size()-1 {
        // should keep track of spike times in case of very long bursts
        if (1000./(mso[p1].x[jj]-burst_time) < burst_maxfreq) {
          burst_time = mso[p1].x[jj]
      if (calc_ave) { print mso[p2].mean } else { mso[p2].printf }

func rvwheres () { local ii
  if ($1!=0) {
    for ii=0,panobjl.object($1).llist.count()-1 {
      if (sfunc.substr(panobjl.object($1).llist.object(ii).name,$s2)==0) {
        return ii }
    errorMsg("String not found in rvwheres.")
  return -2

supind = 0
//* spkhist assume spk times in vec 
// allows superimposing of graphs
// spkhist(bin_size)
proc spkhist () { local ii,jj,min,max,diff
  if (numarg()==0) { print "spkhist(bin_size)" return }
  if (numarg()==3) { min=$2 max=$3 } else { min=0 max=tstop }
  diff = max-min
  vec0.fill(0) vec1.fill(0)
  for (ii=min;ii<int(diff/$1);ii=ii+1) {
    vec0.x[jj+0] = ii*$1
    vec0.x[jj+1] = ii*$1
    vec0.x[jj+2] = (ii+1)*$1
    vec0.x[jj+3] = (ii+1)*$1
    vec1.x[jj+0] = 0
    vec1.x[jj+1] = vrtmp.x[ii]
    vec1.x[jj+2] = vrtmp.x[ii]
    vec1.x[jj+3] = 0
  if (panobj.super==0) {
  } else { graphItem = panobjl.object(panobj.remote).glist.object(supind) 
    supind = supind+1 }
  sprint(temp_string_,"Hist: %s %d",panobj.filename,$1)

//** truncvec (vec1,margin) 
// truncate a thresholded time vector so that only one time is given for each spike
// vec1 has thresholded times, margin is duration of a spike
proc truncvec () { local a,ii,num,marg,time0 localobj vs
  marg = $2
  num=0 time0=-1e3
  for ii=0,$o1.size()-1 {
    if ($o1.x[ii] > time0+marg) { 
      vs.x[ii] = $o1.x[ii]
      time0 = $o1.x[ii]

//** redundkeep(vec) keeps sequential redundent entries
// destructive
proc redundkeep () { local x,ii
  x = $o1.x[0]
  for ii=1,$o1.size-1 {
    if ($o1.x[ii]!=x) { $o1.x[ii-1]=-1e20 x=$o1.x[ii] }

//** after running spkall can see which cells are responsible for spks
// assumes spk times in vec, spk identities in vec1
// uses ind and vec0
proc whichspked () { local ii
  ind.indvwhere(vec,"()",$1,$2) // a range
  vec0 = vec1.ind(ind)
  ind = vec.ind(ind)
  for ii=0,ind.size()-1 { printf("%d %g\n",vec0.x[ii],ind.x[ii]) }

// firebtwn(ind,time,min,max) list of cells that fire between times min and max
proc firebtwn () { local ii,p1,p2,p3
  p1 = allocvecs(3) p2=p1+1 p3=p2+1
  mso[p1].index($o1,mso[p3]) // indices
  mso[p2].index($o2,mso[p3]) // times
  printf("%d hits\n",mso[p3].size)
  for vtr2(&x,&y,mso[p1],mso[p2]) {
      printf("%4d::%6.2f ",x,y)
      if ((ii+1)%5==0) { print "" }
  print ""
//  dealloc(p2) // to save the indexes

// elimind(ind,time,min,max) take out cells with nums between min,max
// destructive
proc elimind () { local ii,p1
  p1 = allocvecs(1)
  vecelim($o1,mso[p1]) vecelim($o2,mso[p1])

// index/time graph
// tigr(ind,vec,size,marker)
proc tigr () { local sz
  if (numarg()==0) { print "tigr(Yvec,Xvec,marker size,marker type)" 
    print "Marker types: \"o\",t,s,O,T,S,+ (circ, tri, square; CAP is filled)"
    return }
  if (numarg()>2) { sz=$3 } else { sz=6 }
  if (numarg()>3) { temp_string_=$s4 } else { temp_string_="O" }

//* p2nqs(#,panobj,nqs) -- copy an entry into an nqs
proc p2nqs () { local x,a localobj v1,q,p
  x=$1 p=$o2 q=$o3

//** spkboth() determines how many cells spike in 2 time periods
proc spkboth () { local a,t1,t2,t3,t4,s1,s2,s3 localobj v1,v2,v3,o
  o=$o1 t1=$2 t2=$3 t3=$4 t4=$5
  o.verbose=0"time","()",t1,t2) v1.redundout(o.getcol("ind"))"time","()",t3,t4) v2.redundout(o.getcol("ind"))
  s1=v1.size s2=v2.size s3=v3.size
  printf("P1: %d, P2: %d, Both: %d (%d%%, %d%%)\n",s1,s2,s3,s3/s1*100,s3/s2*100)

//returns NQS containing ID,Type,SpikeT
//doesn't check if cell is dead or alive, assumes input is valid
//$o1 = spike vitem
//$o1 = spike vitem, $2 == skipI
//$o1 = time vec , $o2 = id vec
obfunc SpikeNQS(){ local idx,skipI localobj vec,tvec,nq
  if(ce==nil) return nil
    vec = $o1.vec tvec = $o1.tvec
  } else if(numarg()==2){
    if(argtype(1)==1 && argtype(2)==1){
      tvec=$o1 vec=$o2
    } else {
      vec = $o1.vec tvec=$o1.tvec skipI=$2
  } else {
    printf("SpikeNQS ERRA: invalid args!\n")
    return nil
  nq = new NQS("ID","Type","SpikeT")
    for idx=0,2 { nq.v[idx].resize(vec.size) nq.v[idx].resize(0) }
    for idx=0,vec.size-1 {
      if(ice(ce.o(vec.x(idx)).type)) continue
  } else {
    for idx=0,vec.size-1 nq.v[1].x(idx)=ce.o(vec.x(idx)).type
  return nq

//returns NQS with refractory % of cell types vs time -- assumes all cells of a type
//have the same refractory period
//$o1 = nqs from SpikeNQS, $2 = dt, optional, $3=skip inhib cells, optional
obfunc refracNQ () { local ct,tt,dt,s,skipI,dotypes localobj snq,nr,vid
  snq=$o1  nr=new NQS("Type","t","r")  ct=0
  if(numarg()>1)dt=$2 else dt=0.25
  if(numarg()>2)skipI=$3 else skipI=1
  if(numarg()>3)dotypes=$4 else dotypes=0
    for ctt(&ct) if(skipI && !ice(ct)) {
        vid=snq.getcol("ID")//after select, so will use output
      } else {
  return nr

//returns nqs with % of cells of each type that have activated by time=t
obfunc PActNQS () { local tinc,winsz,idx,ct,tt,tm,spks,cells,spksE,spksI,nE,nI,cellsE,cellsI\
                   localobj nqt,va,vspk,snq
  //time start,end,cell type,activated:0-1,spikes,cells:abs,cells:0-1
  nqt=new NQS("ts","te","ct","act","spks","cells","cellsn")
  if(numarg()>1)tinc=$2 else tinc=0.25
  if(numarg()>2)winsz=$3 else winsz=0.5
  va=new Vector(CTYPi+1)//keep track of % of cells of a type that have spiked
  {vspk=new Vector(allcells) vspk.fill(0)}//keep track of which cells have spiked
  snq.tog("DB") tm=snq.getcol("SpikeT").max
  for(tt=0;tt<tm;tt+=tinc) {
    for ctt(&ct) {
      if(("Type",ct,"SpikeT","[]",tt,tt+winsz))) {
        for vtr(&idx,snq.getcol("ID"))vspk.x(idx)=1 
        if(ice(ct)) spksI+=spks else spksE+=spks
      va.x(ct) = vspk.sum(ix[ct],ixe[ct]) / numc[ct]
      if(spks>0) cells=snq.out.getcol("ID").uniq else cells=0
      if(ice(ct)) {
      } else {
  return nqt

//$o1=nqs from PActNQS , gets peaks & intervals of cell activity levels,
//ct == -1 for E cells, ct == -2 for I cells
obfunc GetPeakNQ () { local idx,ct localobj vi,nqp,vc,nqpo,nqin
  nqin=$o1 nqin.tog("DB") vc=new Vector(nqin.size(-1)) nqin.getcol("ct").uniq(vc)
  nqpo=new NQS("ct","ts","x","y","dx","dy")
  for vtr(&ct,vc) {"ct",ct) vi=nqin.getcol("spks")
    nqp=new NQS("ct","ts","x","y") 
    for idx=1,vi.size-2 {
      if(vi.x(idx)>vi.x(idx-1) && vi.x(idx)>vi.x(idx+1)) {
    nqp.resize("dx") nqp.resize("dy")
  return nqpo

// returns list containing spike times for each cell
// $o1 == raster vitem
obfunc spikelist () { local idx localobj ls,vec,tvec
  vec=$o1.vec tvec=$o1.tvec
  ls=new List()
  for idx=0,allcells-1 ls.append(new Vector())
  for idx=0,vec.size-1 ls.o(vec.x(idx)).append(tvec.x(idx))
  return ls

// plot a single cell's spike times
// $o1 == snq, $2 == cell id, $3 == color, $4 == size, $5==drawR
proc plotcellst () { local cid,st,clr,a,sz,drawR localobj snq,vt,vx,vy
  snq=$o1 cid=$2 clr=$3 sz=$4
  if(numarg()>4)drawR=$5 else drawR=0
  for vtr(&st,vt) vx.append(st) vy.append(cid)
  if(drawR) for vtr(&st,vt) drline(st+.05,cid,st+ce.o(cid).refrac,cid,g,1,1)

//draw fancier raster
//$o1=nqs from SpikeNQS, $2==draw refractory periods, $3==skip inhib cells
proc drawrastw () { local idx,skipI,drawR,maxID,a,c,sz,drlt localobj snq,vx,vy,vtype,vc,vtu
  a=allocvecs(vx,vy) drlt=drlflush drlflush=0
  vc=new Vector(CTYP.count+1) vc.fill(0)
  snq=$o1 snq.tog("DB") maxID=snq.v[0].max//max ID
  vtype=new Vector() vtype.copy(snq.v[1])//Type
  if(numarg()>1)drawR=$2 else drawR=0
  if(numarg()>2)skipI=$3 else skipI=0
  if(numarg()>3)sz=$4 else sz=2
  vtu=new Vector(vtype.size) vtype.uniq(vtu)
  for vtr(&idx,vtu) if(!skipI || !ice(idx)) {
    for idx=0,maxID if(!ice(ce.o(idx).type)) {
  } else {
    for idx=0,maxID {
  dealloc(a) drlflush=drlt  

// plot inhib cells in rast
// $o1 == snq, $2==color, $3==size
proc plotIrast () { local idx,clr,sz localobj xo,snq
  snq=$o1 clr=$2 sz=$3 idx=0
  for ltr(xo,ce,&idx) if(ice(xo.type)) plotcellst(snq,idx,clr,sz)

//simple coefficient of variation of interspike interval synch measure from tiesinga03.pdf
//$o1 = spike nqs from SpikeNQS()
//$2 = interval time
//$3 = slide time
//$4 = skip inhib cells [optional] default == 1
obfunc CVPNQS(){ local idx,startt,endt,midt,N,intt,slidet,ct,skipI,CVp localobj snq,cvpnq,vs,vi,vu
  snq=$o1 intt=$2 slidet=$3 if(numarg()>3)skipI=$4 else skipI=1
  vs=new Vector(allcells*2) vi=new Vector(allcells*2)
  vs.resize(0) vi.resize(0) snq.verbose=0
  cvpnq=new NQS("Type","startt","endt","midt","sync","N","CVp","sync2")
  startt=0 endt=intt midt=intt/2
  vu=new Vector(allcells)
    if(endt>=tmax_INTF) endt=tmax_INTF
    if( ("SpikeT",">=",startt,"SpikeT","<",endt)) > 2 ){
      snq.out.getcol("ID").uniq(vu) N=vu.size //# of active cells
      vs.copy(snq.out.getcol("SpikeT")) //spike times
      vs.sort //sort spike times to make ISI for all active cells
      for idx=0,vs.size-2 vi.append(vs.x(idx+1)-vs.x(idx))
    } else {
    for ctt(&ct) {
      if(skipI && ice(ct)) continue
      if( ("Type",ct,"SpikeT",">=",startt,"SpikeT","<",endt)) > 2 ){
        snq.out.getcol("ID").uniq(vu) N=vu.size //# of active cells
        vs.copy(snq.out.getcol("SpikeT")) //spike times
        vs.sort //sort spike times to make ISI for all active cells
        for idx=0,vs.size-2 vi.append(vs.x(idx+1)-vs.x(idx))
      } else {
  return cvpnq

//return spike frequency NQS
//$o1=spike nqs from SpikeNQS()
//$2=interval [optional]
//$3=just do types with interval [optional]
//$4=skipI [optional] default==1
//$5=stop time [optional]
//$6=start time [optional]
//$7=slide time [optional]
obfunc FreqNQS(){ local idx,startt,endt,intt,ct,dotypes,starttime,stoptime,sp,slidet,skipI\
                 localobj fnq,snq
  snq=$o1 intt=$2
  if(numarg()>2) dotypes=$3 else dotypes=0
  if(numarg()>3) skipI=$4 else skipI=1
  if(numarg()>4) stoptime=$5 else stoptime=tstop
  if(numarg()>5) starttime=$6 else starttime=0
  if(numarg()>6) slidet=$7 else slidet=intt
    fnq=new NQS("ID","Type","Freq","StartT","EndT")
    intt=$2 startt=starttime endt=startt+intt
      //check length of interval, make sure it's within time bounds of run
      if(endt >= stoptime) endt = stoptime
      for idx=0,allcells-1{
        if(skipI && ice(ce.o(idx).type))continue,"ID",idx,"SpikeT",">=",startt,"SpikeT","<",endt)
  } else {
    fnq=new NQS("Type","Freq","StartT","EndT")
    intt=$2 startt=starttime endt=startt+intt
      //check length of interval, make sure it's within time bounds of run
      if(endt >= stoptime) endt = stoptime
      for ctt(&ct) { 
        if(skipI && ice(ct))continue,"Type",ct,"SpikeT",">=",startt,"SpikeT","<",endt)
  return fnq

func binfindtidx () { local done,val,idx,m,lo,hi,t localobj vv
  vv=$o1 t=$2
  lo=0  hi=vv.size-1  m=int(vv.size/2) done=0
      hi=m m=int((hi+lo)/2.0)
    } else if(vv.x(m)<t){
      lo=m m=int((hi+lo)/2.0)
    if(hi==m || lo==m) return m

obfunc estconmat () { local t1,t2,idx,jdx,kdx,del,st1,st2,tdx,df localobj ls,emat,vs1,vs2,vp
  ls=$o1 del=$2  emat=new List()
  for idx=0,ls.count-1 emat.append(new Vector(ls.count))
  return emat

// geteff -- get efficiency of $1 to $2 connections
// $1 == type 1 (from)
// $2 == type 2 (to)
// $o3 == ls from spikelist
// returns vector with access by index
obfunc geteff () { local idx,jdx,kdx,ldx,ty1,ty2,tot,cnt,tt,del,fctr,cntonce\
              localobj vt,vpo,vdel,vm,vt2,vtmp,ls,vid
  ty1=$1  ty2=$2  ls=$o3 
  if(numarg()>3) fctr=$4 else fctr=2
  if(numarg()>4) cntonce=$5 else cntonce=0
  vpo=new Vector(allcells)
  vdel=new Vector(allcells)
  vm=new Vector(allcells)
  vtmp=new Vector(allcells)
  for idx=ix[ty1],ixe[ty1]{
    if(!ls.o(idx).size) continue
    for jdx=0,vpo.size-1 if(ce.o(vpo.x(jdx)).type==ty2) tot+=1
    if(!tot) continue
    for jdx=0,vt.size-1 { // go thru spikes
      for kdx=0,vpo.size-1{ // go thru outputs
        if(ce.o(vpo.x(kdx)).type!=ty2) continue
        for ldx=0,vt2.size-1{ // check spiketimes of each output
          if(vt2.x(ldx) >= tt+del && vt2.x(ldx) <= tt+fctr*del){ // within range?
            cnt += 1
            if(cntonce) break // only count once? then break
    if(vtmp.size) vm.x(idx)=vtmp.mean
  return vm

// get efficiency of excitatory connections between populations in a given path
// specified by $o1 , i.e. $o1 = new Vector(layer4,layer2,layer5,layer6,layer4)
// $o2 == ls , from spikelist(...)
// $3 == delay fctr for geteff
// returned as NQS
obfunc getpatheffnq () { local fctr,cntonce localobj vpath,nqp,ve,ls
  if(numarg()>3) nqp=$o4 else nqp=new NQS("ID","from","to","e")
  if(numarg()>4) cntonce=$5 else cntonce=0
  for idx=0,vpath.size-2 {
    printf("eff from %s to %s: ",CTYP.o(vpath.x(idx)).s,CTYP.o(vpath.x(idx+1)).s)
    for jdx=ix[vpath.x(idx)],ixe[vpath.x(idx)]{
  return nqp

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]

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