Reinforcement learning of targeted movement (Chadderdon et al. 2012)

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Accession:144538
"Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint “forearm” to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. ..."
Reference:
1 . Chadderdon GL, Neymotin SA, Kerr CC, Lytton WW (2012) Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex PLoS ONE 2012 7(10):e47251
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 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): Dopamine; Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Simplified Models; Synaptic Plasticity; Long-term Synaptic Plasticity; Reinforcement Learning; Reward-modulated STDP;
Implementer(s): Neymotin, Sam [samn at neurosim.downstate.edu]; Chadderdon, George [gchadder3 at gmail.com];
Search NeuronDB for information about:  GabaA; AMPA; NMDA; Dopamine; Gaba; Glutamate;
/
arm1d
README
drspk.mod *
infot.mod *
intf6_.mod *
intfsw.mod *
misc.mod *
nstim.mod *
stats.mod *
updown.mod *
vecst.mod *
arm.hoc
basestdp.hoc
col.hoc *
colors.hoc *
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
filtutils.hoc *
geom.hoc
grvec.hoc *
hinton.hoc *
infot.hoc *
init.hoc
intfsw.hoc *
labels.hoc *
local.hoc *
misc.h *
mosinit.hoc
network.hoc
nload.hoc
nqs.hoc *
nqsnet.hoc *
nrnoc.hoc *
params.hoc
run.hoc
samutils.hoc *
sense.hoc *
setup.hoc *
sim.hoc
simctrl.hoc *
stats.hoc *
stim.hoc
syncode.hoc *
units.hoc *
xgetargs.hoc *
                            
// $Id: intfsw.hoc,v 1.76 2011/10/21 00:37:00 samn Exp $ 
// load_file("intfsw.hoc")

print "Loading intfsw.hoc..."

{load_file("nqs.hoc")}
{load_file("drline.hoc")}
{load_file("boxes.hoc")}

//////////////////////////////////////////////////////////////////////////////////////
//                               some usage 
//
//  adj=AdjList() //creates adjacency list used by other functions, it is global obj
//                //that other functions use internally
//
//  this is a variable, users can define their own, but it's not needed for hoc code:
//  subs = 640/numc[SU] //# btwn 0 and 1 specifying % of cells to use in computation
//  of path length and/or clustering coefficient, it can be passed into the functions
//  
//  this type of sequence gets excitatory path length for net:
//  vd=GetNetEXL(-1,subs) // -1 means get full path lengths of ALL distances
//  vd.gzmean // this will give you path length value for net
//
//  this type of sequence gets excitatory cell clustering coefficient for net:
//  vc=GetNetEXCC(ix[DP],ixe[SU],subs) //excitatory (DP,SU) cell clustering coefficient
//  vc.gzmean // this will give you clustering coefficient value for net
//
//
//////////////////////////////////////////////////////////////////////////////////////

{declare("adj",nil,"vd",nil,"vc",nil,"allcells",0,"div","d[1][1]")}
sprint(tstr,"o[%d]",CTYPi+1)
{declare("nxadjg",nil,"vhistg",tstr,"vhistgd",tstr,"intfswb","nil")}
{declare("divnq",nil,"convnq",nil,"intfswbfl",1,"getactive",1,"loadednetworkx",0)}
{install_intfsw()}

obfunc AdjTab () { local idx,jdx localobj adj,vid
  if (verbose) printf("generating adjacency matrix")
  adj=new List()
  for idx=0,allcells-1 adj.append(new Vector(allcells))
  for idx=0,allcells-1{
    if(verbose && idx%100==0)printf(".")
    vid=GetDiv(idx)
    for jdx=0,vid.size-1 adj.o(idx).x(vid.x(jdx))=1
  }
  if (verbose) printf("\n")
  return adj
}

//* AdjList - get list of adjacency lists
//[optional] $1 = startid
//[optional] $2 = endid
//[optional] $3 = skip inhib cells from list
//[optional] $o4 = CE list - default uses global ce
obfunc AdjList () { local idx,jdx,startid,endid,ct,dv,skipinhib localobj adj,vid,vtmp,CE
  if (verbose) printf("generating adjacency list")
  if (numarg()>0) startid=$1 else startid=0
  if (numarg()>1) endid=$2 else endid=allcells-1
  if (numarg()>2) skipinhib=$3 else skipinhib=0
  if (numarg()>3) CE=$o4 else CE=ce
  adj=new List()
  for idx=0,CE.count-1 adj.append(new Vector(CE.o(idx).getdvi))
  CE.o(0).adjlist(adj,startid,endid,skipinhib)
  return adj
}

//** adjstrg() -- get a string representation of adjacency list for use with dot
obfunc adjstrg () { local i,j localobj str,lc
  lc=new List()
  lc.append(new String("blue"))
  lc.append(new String("red"))
  str=new String2()
  str.s="digraph G {"
  for i=0,adj.count-1{ 
    for j=0,adj.o(i).size-1{
      sprint(str.t,"%d -> %d [color=%s];\n",i,adj.o(i).x(j),lc.o(ice(ce.o(i).type)).s)
      strcat(str.s,str.t)
    }
    sprint(str.t,"%d [color=%s];\n",i,lc.o(ice(ce.o(i).type)).s)
    strcat(str.s,str.t)
  }
  strcat(str.s,"}\n")
  return str
}

//** net2txtf(path) -- save net to text file representation
func net2txtf () { local jdx,idx,syns localobj F,vid
  F = new File()
  F.wopen($s1)
  if(!F.isopen){
    printf("couldn't open for saving\n")
    return 0
  }
  syns = 0
  for idx=0,ce.count-1 syns += ce.o(idx).getdvi
  F.printf("%d\n",ce.count)//# of cells  
  F.printf("%d\n",syns)//# of synapses
  F.printf("%d\n",ecells)
  F.printf("%d\n",icells)
  for idx=0,ce.count-1{
    if(ice(ce.o(idx).type)) F.printf("I ") else F.printf("E ")
    F.printf("%g %g %g\n",ce.o(idx).xloc,ce.o(idx).yloc,ce.o(idx).zloc)
  }
  vid=new Vector(allcells)
  vid.resize(0)
  for idx=0,ce.count-1{
    ce.o(idx).getdvi(vid)
    for jdx=0,vid.size-1{
      if(ice(ce.o(idx).type)) F.printf("I ") else F.printf("E ")
      F.printf("%d %d\n",idx,vid.x(jdx))
    }
  }
  F.close
  return 1
}

//write net to pajek .net file , can also be used in GUESS graph visualization program
//$s1=output file path, $o2=vector of cell types to add to output file
func writepajek () { local idx,jdx,ty,ndx localobj fp,vid,vdel,lc,vty,nqc
  fp=new File() vid=new Vector(allcells) vdel=new Vector(allcells)
  lc=new List() lc.append(new String("Red")) lc.append(new String("Blue")) vty=$o2
  fp.wopen($s1)
  if(!fp.isopen())return 0
  fp.printf("*Vertices %d\r\n",allcells)
  for idx=0,allcells-1{
    ty=ce.o(idx).type if(!vty.contains(ty))continue
    fp.printf("%d \"%s%d\" ic %s\r\n",idx+1,CTYP.o(ty).s,idx,lc.o(ice(ty)).s)
  }
  fp.printf("*Arcslist\r\n")  
  for idx=0,allcells-1 {
    ce.o(idx).getdvi(vid,vdel) ty=ce.o(idx).type
    if(!vty.contains(ty))continue

    fp.printf("%d ",idx+1)
    for ndx=0,vid.size/2 {
      jdx=vid.x(ndx)
      if(!vty.contains(ce.o(jdx).type))continue
      fp.printf("%d ",jdx+1)
    }
    fp.printf("1 c %s",lc.o(ice(ty)).s)
    fp.printf("\r\n")

    fp.printf("%d ",idx+1)
    for ndx=1+vid.size/2,vid.size-1 {
      jdx=vid.x(ndx)
      if(!vty.contains(ce.o(jdx).type))continue
      fp.printf("%d ",jdx+1)
    }
//    for vtr(&jdx,vid) {
//      if(!vty.contains(ce.o(jdx).type))continue
//      fp.printf("%d ",jdx+1)
//      fp.printf("%d %d 1 c %s\r\n",idx+1,jdx+1,lc.o(ice(ty)).s)
//    }
    fp.printf("1 c %s",lc.o(ice(ty)).s)
    fp.printf("\r\n")
  }
  fp.close()
  return 1
}



/////////////////////////////////////////////////////////////////////////
//get path existence/distance vector ==
// vector with:
//   d==0==no path between cell $1 and cell index
//               and
//   d>0==a path exists between cell $1 and cell index of distance d
//
// $1 = cell id to start search from
// $2 = minimum id of destination
// $3 = maximum id of destination
// $4 = max distance to search
obfunc GetPathEV () { local idx,myid,idist,startid,endid,maxdist localobj vd,vcheck,vtmp
  if(adj==nil)adj=AdjList()  
  myid=$1  
  if(numarg()>1)startid=$2 else startid=0
  if(numarg()>2)endid=$3 else endid=allcells-1
  if(numarg()>3)maxdist=$4 else maxdist=-1
  vd=new Vector(allcells)
  GetPathEV_intfsw(adj,vd,myid,startid,endid,maxdist)
  return vd
}

//check if network is fully connected == any cell has a path
//to any other cell
//can use speedup/efficiency improvements
func FullyConnected () { local idx localobj vd
  for idx=0,allcells-1{
    if(idx%100==0)printf("checking path from cell %d to others\n",idx)
    vd=GetPathEV(idx)
    if(vd.count(0)>1){
      printf("cell %d not fully connected to other cells, only has path to %d cells\n",idx,allcells-vd.count(0))
      return 0
    }
  }
  return 1
}

//approximate path length formula
//N=# of vertices
//$1=# of 1st degree neighbors
//$2=# of 2nd degree neighbors
func ApproxL () { local z1,z2,N
  N=$1  z1=$2 z2=$3
  return log(N/z1)/log(z2/z1)+1
}

//get approximate path length by first getting # of
//1st & 2nd degree neighbors
func GetApproxL () { local z1,z2,i,subsamp localobj lvnn,vtmp
  if(numarg()>0)subsamp=$1 else subsamp=1
  if(adj==nil) if(numc[DP]) adj=AdjList(ix[DP],ixe[SU]) else adj=AdjList()
  lvnn=new List()
  for i=0,1{
    vtmp=GetNumNeighbors(i+1,ix[DP],ixe[SU],1,adj,subsamp)
    lvnn.append(vtmp)
  }
  {z1=lvnn.o(0).gzmean(ix[DP],ixe[SU]) printf("z1=%g\n",z1)}
  {z2=lvnn.o(1).gzmean(ix[DP],ixe[SU]) printf("z2=%g\n",z2)}
  return ApproxL((1-killDP)*numc[DP]+(1-killSU)*numc[SU],z1,z2)
}

//returns vector of size allcells containing avg dist from that cell
//to all other cells it is connected to
obfunc GetNetL () { local from,gzm,sid,eid localobj vdist,vtmp
  if(numarg()>0)sid=$1 else sid=0
  if(numarg()>1)eid=$2 else eid=allcells-1
  vdist=new Vector(allcells) vtmp=new Vector(allcells)
  adj=AdjList(sid,eid) //make sure initialized properly in face of prup,killp,etc.
  printf("searching from id: ")
  for from=sid,eid{
    if(verbose && from%100==0)printf("%d...",from)
    if(ce.o(from).flag("dead"))continue
    vtmp=GetPathEV(from,sid,eid)
    if((gzm=vtmp.gzmean)>0){
      vdist.x(from)=gzm
    }
  }
  printf("\n")
  return vdist
}

// ** GetNetEXLSubPops -- get path length between excitatory subpopulations
// returns Vector of size allcells, to see path length do Vector.gzmean
// $1 == from population
// $2 == to population
// $3 == subsamp [default == 1, optional]
// $4 == take into account self-loop-length [default == 0, optional]
obfunc GetNetEXLSubPops () { local subsampi,from,selfl localobj vd,vstart,vend
  from=$1 to=$2
  if(numarg()>2) subsamp=$3 else subsamp=1
  if(numarg()>3) selfl=$4 else selfl=0
  if(adj==nil) adj=AdjList(0,allcells-1,1)//get adjacency list
  {vstart=new Vector(allcells) vend=new Vector(allcells) vd=new Vector(allcells)}
  for i=ix[from],ixe[from] vstart.x(i)=1
  for i=ix[to],ixe[to] vend.x(i)=1
  GetPathSubPop_intfsw(adj,vd,vstart,vend,subsamp,selfl)
  printf("exl path from sub pop %s to %s = %g\n",CTYP.o(from).s,CTYP.o(to).s,vd.gzmean)
  return vd
}

//returns vector of size allcells containing avg dist from that cell
//to all other excitatory(E) cells it is connected to
//only travels paths through E cells
//$1 == max dist , default == -1, to search all distances
//$2 == subsamp -- only use subsamp% of cells
//$3 == first turn off sub-pop to sub-pop [optional] default == -1
obfunc GetNetEXL () { local from,gzm,maxdist,subsamp localobj vdist,rdm,vuse
  if(numarg()>0)maxdist=$1 else maxdist=-1
  if(numarg()>1)subsamp=$2 else subsamp=1
  if(adj==nil)adj=AdjList(0,allcells-1,1) //make sure initialized properly in face of prup,killp,etc.
  vdist=new Vector(adj.count)
  GetPathR_intfsw(adj,vdist,0,adj.count-1,-1,subsamp)
  return vdist
}

//import networkx python library
func initnetworkx () {
  if(loadednetworkx) return 1
  if(!nrnpython("import networkx")) {
    printf("initnetworkx ERRA: couldn't import networkx python library!\n")
    return 0
  }
  loadednetworkx=1
  return 1
}

//get a PythonObject containing adjacency list adj, with variable name = $s1, $2==skip I cells
obfunc NXAdjG () { local idx,jdx,skipI localobj str,py  
  if(!initnetworkx()) return nil
  str=new String()
  sprint(str.s,"%s=networkx.XDiGraph()",$s1)
  py=new PythonObject()
  if(!nrnpython(str.s)){
    printf("NXAdjG ERRA: Couldn't evaluate %s in python!\n",str.s)
    return nil
  }
  if(numarg()>1)skipI=$2 else skipI=1
  for idx=0,allcells-1 if(!skipI || !ice(ce.o(idx).type)) {
    sprint(str.s,"%s.add_node(%d)",$s1,idx)
    if(!nrnpython(str.s)){
      printf("NXAdjG ERRB: Couldn't add node %d to %s\n",idx,$s1)
      return nil
    }
  }
//  if(!adj)adj=AdjList(0,allcells-1,skipI)
//  for idx=0,adj.count-1 for jdx=0,adj.o(idx).count-1 {
//    sprint(str.s,
//  }
  return py
}

func tyfunc () { return ce.o($1).type }

//get between-ness centrality of all E cells, in output NQS
obfunc GetNetECent () { localobj vcent,centnq
  if(adj==nil)adj=AdjList(0,allcells-1,1)
  vcent=new Vector(adj.count) vcent.fill(0)
  GetCentrality_intfsw(adj,vcent)
  centnq=new NQS("id","type","C")
  centnq.v[0].indgen(0,adj.count-1,1)
  centnq.v[1].copy(centnq.v[0])
  centnq.v[1].apply("tyfunc")
  centnq.v[2].copy(vcent)
  return centnq
}

//gets vector with loop/return path-lengths to each excitatory cell
// out.x(idx)=0 means no such path found to cell idx
obfunc GetNetELoop () { local idx localobj vdist,vloop,vf,vto
  vdist=new Vector(1) vloop=new Vector(allcells) vf=new Vector(1) vto=new Vector(1)
  if(adj==nil)adj=AdjList(0,allcells-1,1)//make sure initialized properly in face of prup,killp,etc.
  for idx=0,allcells-1 {
    if(ice(ce.o(idx).type)) {
      vloop.x(idx)=0
      continue
    }
    vf.x(0)=vto.x(0)=idx
    GetPairDist_intfsw(adj,vdist,vf,vto)
    vloop.x(idx)=vdist.x(0)
  }
  return vloop
}

// ** wirenq -- get wiring nqs, preid, postid, delay, wt1, wt2
// iff numarg()>0 $1 == only store info on excitatory connections
obfunc wirenq () { local ii,jj,exonly localobj vid,vdel,vprob,vw1,vw2,nq,vpl
  if(numarg()>0) exonly=$1 else exonly=0
  {vid=new Vector() vdel=new Vector() vprob=new Vector() vw1=new Vector() vw2=new Vector()}
  nq=new NQS("preid","poid","del","wt1","wt2")
  if(exonly){
    for ii=0,allcells-1{
     if(ice(ce.o(ii))) continue
     ce.o(ii).getdvi(1,vid,vdel,vprob,vw1,vw2)
     for jj=0,vid.size-1{
       if(ice(ce.o[vid.x(jj)])) continue
       nq.append(ii,vid.x(jj),vdel.x(jj),vw1.x(jj),vw2.x(jj))
     }
    }
  } else {
    for ii=0,allcells-1{
      ce.o(ii).getdvi(1,vid,vdel,vprob,vw1,vw2)
      for jj=0,vid.size-1{
        if(ice(ce.o[vid.x(jj)])){
          vw1.mul(-1)
          vw2.mul(-1)
        } 
        nq.append(ii,vid.x(jj),vdel.x(jj),vw1.x(jj),vw2.x(jj))
      }
    }
  }
  return nq
}

// ** GetNetWEXL() -- get weighted network excitatory path length
// uses directed weighted graph where distance between nodes is == delay/weight
// done for AMPA,NMDA or BOTH -- $1 == ampa flag, $2 == nmda flag
// $o3 == wirenq , [optional]
// $4 == flip order of preid, poid (convergence instead of divergence lengths) [optional]
obfunc GetNetWEXL () { local ampa,nmda,edgef,flip\
                      localobj vid,vdel,vprob,vw1,vw2,nq,vpl,vs,vpre,vpo
  if(numarg()>0) ampa=$1 else ampa=1
  if(numarg()>1) nmda=$2 else nmda=1
  if(numarg()>2) nq=$o3 else nq = wirenq(1)
  if(numarg()>3) flip=$4 else flip=0
  vpl=new Vector(allcells)
  vdel=new Vector()
  if(flip){ // flip pre and po
    vpre=nq.getcol("poid")
    vpo=nq.getcol("preid")
  } else {
    vpre=nq.getcol("preid")
    vpo=nq.getcol("poid")
  }
  nq.getcol("del",vdel)
  if(ampa && nmda){
    vs=new Vector()
    vs.copy(nq.getcol("wt1"))
    vs.add(nq.getcol("wt2"))
    GetWPath_intfsw(vpre,vpo,vs,vdel,vpl)
  } else if(ampa){
    GetWPath_intfsw(vpre,vpo,nq.getcol("wt1"),vdel,vpl)
  } else if(nmda){
    GetWPath_intfsw(vpre,vpo,nq.getcol("wt2"),vdel,vpl)
  } else { 
    if(numarg()<=2)nqsdel(nq)
    return nil
  }
  if(numarg()<=2)nqsdel(nq)
  return vpl
}

// ** GetNetWL() -- get weighted network path length, takes inhibitory contributions as
// weight/delay , and excitatory contributions as delay/weight
// only uses AMPA/GABAA or NMDA/GABAB
obfunc GetNetWL () { local ampagabaa localobj vid,vdel,vprob,vw1,vw2,nq,vpl
  if(numarg()>0) ampagabaa=$1 else ampagabaa=1
  nq = wirenq(0)
  vpl=new Vector(nq.size)
  if(ampagabaa){
    GetWPath_intfsw(nq.getcol("preid"),nq.getcol("poid"),nq.getcol("wt1"),nq.getcol("del"),vpl)
  } else {
    GetWPath_intfsw(nq.getcol("preid"),nq.getcol("poid"),nq.getcol("wt2"),nq.getcol("del"),vpl)
  }
  return vpl
}


// ** GetNetEXCCSubPops -- get clustering coefficient between excitatory subpopulations
// returns Vector of size allcells, to see path length do Vector.gzmean
// $1 == from population
// $2 == to population
// $3 == subsamp [default == 1, optional]
obfunc GetNetEXCCSubPops () { local subsampi,from localobj vd,vstart,vend
  from=$1 to=$2
  if(numarg()>2) subsamp=$3 else subsamp=1
  if(adj==nil) adj=AdjList(0,allcells-1,1)//get adjacency list
  {vstart=new Vector(allcells) vend=new Vector(allcells) vd=new Vector(allcells)}
  for i=ix[from],ixe[from] vstart.x(i)=1
  for i=ix[to],ixe[to] vend.x(i)=1
  GetCCSubPop_intfsw(adj,vd,vstart,vend,subsamp)
  printf("excc from sub pop %s to %s = %g\n",CTYP.o(from).s,CTYP.o(to).s,vd.nnmean)
  return vd
}

//get clustering coefficient vector for excitatory cells
//usage: vcc = GetNetEXCC()
//vcc.x(i) is clustering coefficient of cell i (must be >= 0.0 && <= 1.0)
//otherwise there was a problem...
//vcc.mean(ix[DP],ixe[SU]) is clustering coefficient of excitatory cells for entire network
obfunc GetNetEXCC () { local idx,sid,eid,subsamp localobj vcc,vuse
  if(adj==nil)adj=AdjList(0,allcells-1,1)
  if(numarg()>0)sid=$1 else sid=0
  if(numarg()>1)eid=$2 else eid=adj.count-1
  if(numarg()>2)subsamp=$3 else subsamp=1
  vcc=new Vector(adj.count)
  GetCCR_intfsw(adj,vcc,sid,eid,subsamp)
  return vcc
}

//returns vector of size allcells containing num of neighbors <= $1 distance away
//for each cell
obfunc GetNumNeighbors () { local maxdist,startid,endid,exact,subsamp,sead localobj vdist,vtmp,vuse,rdm
  maxdist=$1
  if(numarg()>1)startid=$2 else startid=ix[DP]
  if(numarg()>2)endid=$3 else endid=ixe[SU]
  if(numarg()>3)exact=$4 else exact=0
  if(numarg()>4)adj=$o5 else if(adj==nil) adj=AdjList()//make sure initialized properly in face of prup,killp,etc.
  if(numarg()>5)subsamp=$6 else subsamp=1
  vdist=new Vector(allcells) vtmp=new Vector(allcells)
  printf("searching from id: ")
  CountNeighborsR_intfsw(adj,vdist,startid,endid,maxdist,subsamp)
  return vdist
}

//returns vector of size allcells containing # of recurrent connections terminating on cell
//i in out.x(i)
//$1 == from type, -1 means from all E cells, -2 means all I cells, as a vec from all types in vec
//$2 == thru type, -1 means thru all E cells, -2 means all I cells, as a vec thru all types in vec
obfunc GetRecurVec () { local from,thru,ct localobj vRC,vfrom,vthru,vtmp
  vRC=new Vector(allcells) vfrom=new Vector(allcells) vthru=new Vector(allcells)
  vRC.fill(0) 
  if(adj==nil)adj=AdjList()
  if(numarg()>0) {
    if(argtype(1)==0) {
      if($1>=0) {
        vfrom.fill(1,ix[$1],ixe[$1]) //from only a specific type
      } else if($1==-1) { // E cells
        for ctt(&ct) if(!ice(ct)) vfrom.fill(1,ix[ct],ixe[ct])
      } else for ctt(&ct) if(ice(ct)) vfrom.fill(1,ix[ct],ixe[ct]) // I cells
    } else {
      for vtr(&from,$o1) vfrom.fill(1,ix[from],ixe[from]) //from a bunch of types
    }
  } else vfrom.fill(1)
  if(numarg()>1) {
    if(argtype(1)==0) {
      if($1>=0) {
        vthru.fill(1,ix[$2],ixe[$2])
      } else if($1==-1) { // E cells
        for ctt(&ct) if(!ice(ct)) vthru.fill(1,ix[ct],ixe[ct])
      } else for ctt(&ct) if(ice(ct)) vthru.fill(1,ix[ct],ixe[ct]) // I cells
    } else {
      for vtr(&thru,$o1) vthru.fill(1,ix[thru],ixe[thru]) //thru a bunch of types
    }
  } else vthru.fill(1)
  GetRecurCount_intfsw(adj,vRC,vfrom,vthru)
  return vRC
}

//* DivNQS([cell list]) - gets NQS with # of outputs of a given type from each cell
obfunc DivNQS () { local a,idx,x,flag localobj nq,vc,vd,vo,vty,st,CE,vcnt,xo
  if(numarg()>0)CE=$o1 else CE=ce
  st=new String2()
  nq=new NQS("id","type")
  a=allocvecs(vc,vd,vty,vo,vcnt,CTYPi+1)
  vrsz(0,vc,vd,vo,vty) vcnt.resize(CTYPi)
  for ltr(xo,CE) vcnt.x(xo.type)+=1
  for x=0,CTYPi-1 if(vcnt.x(x)) {
    {sprint(st.s,"to%s",CTYP.o(x).s) nq.resize(st.s) vty.append(x)} // vty -- type vec
  }
  nq.clear(CE.count) // make big enough
  flag=getactive+0.2
  for idx=0,CE.count-1 {
    CE.o(idx).getdvi(flag,vc) // picks up for all existing (CTYP) cell types
    vo.index(vc,vty) // only take the ones for the relevant types
    revec(vd,idx,CE.o(idx).type) vd.append(vo) // put in the id and type values for the postcell
    nq.append(vd)
  }
  dealloc(a)
  return nq
}

//* ConvNQS([cell list]) - gets NQS with # of inputs of a given type onto each cell
obfunc ConvNQS () { local a,idx,x,flag localobj nq,vc,vd,vo,vty,st,CE,vcnt,xo
  if(numarg()>0)CE=$o1 else CE=ce
  st=new String2()
  nq=new NQS("id","type")
  a=allocvecs(vc,vd,vty,vo,vcnt,CTYPi+1)
  vrsz(0,vc,vd,vty) vcnt.resize(CTYPi)
  for ltr(xo,CE) vcnt.x(xo.type)+=1
  for x=0,CTYPi-1 if(vcnt.x(x)) {
    {sprint(st.s,"f%s",CTYP.o(x).s) nq.resize(st.s) vty.append(x)} // vty -- type vec
  }
  nq.clear(CE.count) // make big enough
  flag=getactive+0.2
  for idx=0,CE.count-1 {
    CE.o(idx).getconv(flag,vc) // picks up for all possible cell types
    vo.index(vc,vty) // only take the ones for the relevant types
    revec(vd,idx,CE.o(idx).type) vd.append(vo) // put in the id and type values for the postcell
    nq.append(vd)
  }
  dealloc(a)
  return nq
}

//display conv hists in graphs
proc ShowConvHists () { local from,to,jj,ii,num localobj vt,vt2,mystr,o,xo,yo
  mystr=new String()       hflg=2      ers=0
  if(numarg()<1 && convnq!=nil)nqsdel(convnq)
  if(convnq==nil) convnq=ConvNQS()
  convnq.verbose=0
  num=0
  for ctt(&to) num+=1 // count the active cells
  if (intfswbfl) {
    for ltr(yo,boxerl) if (strm(yo.name,"CONV")) o=yo
    if (o!=nil) { // reuse this box
      if (o.size!=num) {printf("ERR: wrong # of graphs in tray: %d %d\n",o.size,num) return}
      for ltr(xo,o.gl) xo.erase_all
    } else o=mktray("CONV",num)
    for ctt(&to,&ii) vhistg[to]=o.gl.o(ii)
  } else for ctt(&to) {
    if(vhistg[to]==nil || numarg()<1) vhistg[to]=new Graph() else vhistg[to].erase_all
  }  
  for ctt(&to) {
    sprint(mystr.s,"conv hist onto %s",CTYP.o(to).s)
    vhistg[to].color(to)
    vhistg[to].label(0.35,0.95,mystr.s)
    for ctt(&from,&ii){
      if(!div[from][to]) continue
      clr=from
      if(convnq.select("type",to)){
        sprint(mystr.s,"f%s",CTYP.o(from).s)
        vt=convnq.getcol(mystr.s)
        sprint(mystr.s,"from %s avg=%g",CTYP.o(from).s,vt.mean)
        if (vt.min==vt.max) {
          vhistg[to].mark(vt.min,0,"S",10,clr,4)
        } else {
          hist(vhistg[to],vt)
        }
        vhistg[to].color(clr)
        vhistg[to].label(0.5,0.88-0.05*ii,mystr.s)
      }
    }
    vhistg[to].exec_menu("View = plot")
  }  
  convnq.verbose=1
}

//display div hists in graphs -- skips inhibitory cells for now...
proc ShowDivHists () { local from,to,ii,jj,num,rows,cols localobj vt,mystr,o,xo,yo
  mystr=new String()      hflg=2      ers=0
  if(numarg()<1 && divnq!=nil)nqsdel(divnq)
  if(divnq==nil) divnq=DivNQS()
  divnq.verbose=0
  num=0
  for ctt(&from) num+=1 // count the active cells
  if (intfswbfl) {
    for ltr(yo,boxerl) if (strm(yo.name,"DIV")) o=yo
    if (o!=nil) { // reuse this box
      if (o.size!=num) {printf("ERR: wrong # of graphs in tray: %d %d\n",o.size,num) return}
       for ltr(xo,o.gl) xo.erase_all
   } else o=mktray("DIV",num)
    for ctt(&from,&ii) vhistgd[from]=o.gl.o(ii)
  } else for ctt(&from) {
    if(vhistgd[from]==nil || numarg()<1) vhistgd[from]=new Graph() else vhistgd[from].erase_all
  }  
  for ctt(&from,&jj) {
    sprint(mystr.s,"div hist from %s",CTYP.o(from).s)
    vhistgd[from].color(from)
    vhistgd[from].label(0.35,0.95,mystr.s)
    for ctt(&to,&ii){
      if(!div[from][to]) continue
      clr=to
      if(divnq.select("type",from)){
        sprint(mystr.s,"to%s",CTYP.o(to).s)
        vt=divnq.getcol(mystr.s)
        sprint(mystr.s,"to %s avg=%g",CTYP.o(to).s,vt.mean)
        if(vt.min==vt.max){
          vhistgd[from].mark(vt.min,0,"S",10,clr,4)
        } else {
          hist(vhistgd[from],vt)
        }
        vhistgd[from].color(clr)
        vhistgd[from].label(0.5,0.88-0.05*ii,mystr.s)
      }
    }
    vhistgd[from].exec_menu("View = plot")
  }  
  divnq.verbose=1
}

//get index of GetCellNQ arg which column is needed, $s1=colname
func getcellnqcolid () { localobj str
  str=new String()
  str.s=$s1
  if(!strcmp($s1,"wexl")){
    return 1
  } else if(!strcmp($s1,"snq")) {
    return 2
  } else if(!strcmp($s1,"fnq")) {
    return 3
  } else if(!strcmp($s1,"C")) {
    return 4
  } else if(!strcmp($s1,"exl")) {
    return 5
  } else if(!strcmp($s1,"excc")) {
    return 6
  } else if(!strcmp($s1,"conv") || strm($s1,"f")) {
    return 7
  } else if(!strcmp($s1,"div") || strm($s1,"to")) {
    return 8
  } else if(!strcmp($s1,"blk")) {
    return 9
  }
  return 0
}

func ifunc () { return ice(ce.o($1).type) }
//get nqs with cell properties including: centrality, exl, excc, div to all types, conv to all types
//$1=do wexl,$2=do snq,$3=do fnq,$4=do C,$5=do exl,$6=do excc,$7=do convnq,$8=do div,$9=do block
obfunc GetCellNQ () { local i,id,n,doexl,doexcc,doconv,doC,dodiv,doblk\
                     localobj nq,nqt,vv,snq,fnq
  nq=new NQS("id","type") adj=nil
  nq.v[0].indgen(0,allcells-1,1)  nq.v[1].copy(nq.v[0]) nq.v[1].apply("tyfunc")
  if(numarg()>3)doC=$4 else doC=1
  if(numarg()>4)doexl=$5 else doexl=1
  if(numarg()>5)doexcc=$6 else doexcc=1
  if(numarg()>6)doconv=$7 else doconv=1
  if(numarg()>7)dodiv=$8 else dodiv=1
  if(numarg()>8)doblk=$9 else doblk=1
  if(doC){
    if (verbose) printf("getting centrality nq\n") nqt=GetNetECent() 
    nq.resize("C") nq.v[nq.m-1].copy(nqt.v[nqt.m-1]) nqsdel(nqt)
  }
  if(numarg()>0) if($1) {
    {if (verbose) printf("getting wexl\n")
      vv=GetNetWEXL()  nq.resize("wexl") nq.v[nq.m-1].copy(vv)}
  }
  if(doexl){
    {if (verbose) printf("getting exl\n")
      vv=GetNetEXL()  nq.resize("exl") nq.v[nq.m-1].copy(vv)}
  }
  if(doexcc){
    {if (verbose) printf("getting excc\n")
      vv=GetNetEXCC() nq.resize("excc") nq.v[nq.m-1].copy(vv)}
  }
  if(doconv){
    if (verbose) printf("getting convnq\n") nqt=ConvNQS()
    for i=2,nqt.m-1 {
      nq.resize(nqt.s[i].s) nq.v[nq.m-1].copy(nqt.v[i])
    }
    nqsdel(nqt)
  }
  if(dodiv){
    if (verbose) printf("getting divnq\n") nqt=DivNQS()
    for i=2,nqt.m-1 {
      nq.resize(nqt.s[i].s) nq.v[nq.m-1].copy(nqt.v[i])
    }
    nqsdel(nqt)
  }
  {nq.resize("inhib") nq.pad() nq.v[nq.m-1].copy(nq.v[0]) nq.v[nq.m-1].apply("ifunc")}
  if(numarg()>1) if($2) {
    if (verbose) printf("getting spike counts\n")
    vv=printlist.o(0).vec    nq.resize("spikes") nq.pad() nq.v[nq.m-1].fill(0)
    for vtr(&i,vv) nq.v[nq.m-1].x(i)+=1
  }
  if(doblk){
    nq.resize("block") nq.pad() for i=1,allcells-1 nq.v[nq.m-1].x(i)=ce.o(i).spkcnt(i,i,2)
  }
  if(numarg()>2) if($3 && name_declared("FreqNQS")) {
    if (verbose) printf("getting FreqNQS\n")
    snq=SpikeNQS(printlist.o(0))
    fnq=FreqNQS(snq,20,0,0)
    for i=0,allcells-1 if((n=fnq.select("ID",i))) {
      if(n>0){
        nq.v[nq.m-1].x(i)=fnq.getcol("Freq").mean
      } else {
        nq.v[nq.m-1].x(i)=fnq.getcol("Freq").x(0)
      }
    }
  }
  if(snq!=nil)nqsdel(snq)
  if(fnq!=nil)nqsdel(fnq)
  return nq
}

//get nqs with rand value for each cell, $1==seed
obfunc GetRandCellNQ () { local i localobj nq,rd
  nq=new NQS("id","type","rand")
  rd=new Random()
  rd.ACG($1)
  for i=0,allcells-1 nq.append(i,ce.o(i).type,rd.normal(0,1))
  return nq
}

// from ShowDivHists()
proc prdiv () { local from,to,jj,ii,num,rows,cols localobj vt,mystr,o,xo,yo
  if (numarg()==1) o=$o1 else o=divnq
  if (o==nil) o=divnq=DivNQS()
  o.verbose=0
  for ctt(&from,&jj) { printf("\ndiv from %s: ",CTYP.o(from).s)
    if (o.select("type",from)) for ctt(&to,&ii) {
      vt=o.getcol(CTYP.o(to).s)
      printf("  to %s avg=%02.3f +- %02.3f",CTYP.o(to).s,vt.mean,vt.stdev) 
  }}
  print ""
  o.verbose=1
}
proc prconv () { local from,to,jj,ii,num,rows,cols localobj vt,mystr,o,xo,yo
  if (numarg()==1) o=$o1 else o=convnq
  if (o==nil) o=convnq=ConvNQS()
  o.verbose=0
  for ctt(&to,&jj) { printf("\nconv to %s: ",CTYP.o(to).s)
    if (o.select("type",to)) for ctt(&from,&ii) {
      vt=o.getcol(CTYP.o(from).s)
      printf("  from %s avg=%02.3f +- %02.3f",CTYP.o(from).s,vt.mean,vt.stdev) 
  }}
  print ""
  o.verbose=1
}

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