Prosthetic electrostimulation for information flow repair in a neocortical simulation (Kerr 2012)

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Accession:141505
This model is an extension of a model (<a href="http://senselab.med.yale.edu/ModelDB/ShowModel.asp?model=138379">138379</a>) recently published in Frontiers in Computational Neuroscience. This model consists of 4700 event-driven, rule-based neurons, wired according to anatomical data, and driven by both white-noise synaptic inputs and a sensory signal recorded from a rat thalamus. Its purpose is to explore the effects of cortical damage, along with the repair of this damage via a neuroprosthesis.
Reference:
1 . Kerr CC, Neymotin SA, Chadderdon GL, Fietkiewicz CT, Francis JT, Lytton WW (2012) Electrostimulation as a prosthesis for repair of information flow in a computer model of neocortex IEEE Transactions on Neural Systems & Rehabilitation Engineering 20(2):153-60 [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 V1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell;
Channel(s): I Chloride; I Sodium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA; Gaba;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Deep brain stimulation; Information transfer; Brain Rhythms;
Implementer(s): Lytton, William [billl at neurosim.downstate.edu]; Neymotin, Sam [samn at neurosim.downstate.edu]; Kerr, Cliff [cliffk at neurosim.downstate.edu];
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex V1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 interneuron basket PV cell; GabaA; AMPA; NMDA; Gaba; I Chloride; I Sodium; I Potassium; Gaba; Glutamate;
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neuroprosthesis
README
infot.mod *
intf6_.mod *
intfsw.mod *
misc.mod *
nstim.mod *
staley.mod *
stats.mod *
vecst.mod *
batch.hoc
boxes.hoc
bsmart.py
col.hoc
comparecausality.py
comparerasters.py
declist.hoc
decmat.hoc *
decnqs.hoc *
decvec.hoc
default.hoc *
drline.hoc *
filtutils.hoc
flexinput.hoc
grvec.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
pyhoc.py
ratlfp.dat *
run.hoc
runsim
setup.hoc *
simctrl.hoc *
spkts.hoc *
staley.hoc *
stats.hoc *
stdgui.hoc *
syncode.hoc *
updown.hoc *
xgetargs.hoc *
                            
// $Id: decmat.hoc,v 1.78 2011/07/11 05:58:31 samn Exp $ 
 
print "Loading decmat.hoc..."
 
//** mtriavg(mat,[mask]) - get average of elements in upper triangular part of matrix $o1
// mask is of same size as mat, has 0 for entries to skip
func mtriavg () { local i,j,s,c localobj mm,msk
  mm=$o1 s=c=0
  if(numarg()>1) { msk=$o2
    for i=0,mm.nrow-1 for j=i+1,mm.ncol-1 if(msk.x(i,j)) {
      s+=mm.x[i][j]
      c+=1
    }    
  } else {
    for i=0,mm.nrow-1 for j=i+1,mm.ncol-1 {
      s+=mm.x[i][j]
      c+=1
    }
  }
  if(c>0) return s/c else return 0
}

//** mltristd(mat,[mask]) - get stdev of elements in upper triangular part of matrix $o1
// mask is of same size as mat, has 0 for entries to skip
func mtristd () { local i,j,s,c,s2,tm localobj mm,msk
  mm=$o1 s=s2=c=0
  if(numarg()>1) { msk=$o2
    for i=0,mm.nrow-1 for j=i+1,mm.ncol-1 if(msk.x(i,j)) {
      s+=mm.x[i][j]
      s2+=mm.x[i][j]^2
      c+=1
    }
  } else {
    for i=0,mm.nrow-1 for j=i+1,mm.ncol-1 {
      s+=mm.x[i][j]
      s2+=mm.x[i][j]^2
      c+=1
    }
  }
  if(c>0) return sqrt(s2/c - (s/c)^2) else return 0
}

//** mltristd(mat,[mask]) - get std-error of elements in upper triangular part of matrix $o1
// mask is of same size as mat, has 0 for entries to skip
func mtristderr () { local i,j,s,c,s2,tm localobj mm,msk
  mm=$o1 s=s2=c=0
  if(numarg()>0) {
    msk=$o2
    for i=0,mm.nrow-1 for j=i+1,mm.ncol-1 if(msk.x(i,j)) {
      s+=mm.x[i][j]
      s2+=mm.x[i][j]^2
      c+=1
    }
  } else {
    for i=0,mm.nrow-1 for j=i+1,mm.ncol-1 {
      s+=mm.x[i][j]
      s2+=mm.x[i][j]^2
      c+=1
    }
  }
  if(c>0) return sqrt(s2/c - (s/c)^2)/sqrt(c) else return 0
}

//** vi2mi(ind[,COLS]) take index from vector and print out matrix indices using COLS 
obfunc vi2mi () { local x,co,r,c
  x=$1
  if (argtype(2)==0) co=$2 else co=COLS
  r=int(x/COLS) c=x%COLS
  if (verbose) print r,c
  return new Union(r,c)
}

//** symmclean(vec[,COLS]) remove redundant entries from vector representing a symm matrix
proc vimiclean() {print "Use symmclean() statt vimiclean()"}
func symmclean () { local ix,dg,cols,ii,n,flag localobj v1
  v1=$o1 
  if (argtype(2)==0) cols=$2 else cols=COLS
  if (argtype(3)==0) flag=$3 else flag=0 // flag gets rid of the diagonal as well
  for ii=0,v1.size-1 { ix=v1.x[ii]
    dg=(n=int(ix/(cols+1)))*(cols+1)
    if (ix<dg || ix>=dg+(cols-n)) v1.x[ii]=-1
    if (flag && ix==dg) v1.x[ii]=-1
  }
  v1.where(">",-1)
  return v1.size
}

//** msqdif(m1,m2) - get matrix with elements squared difference of m1-m2
obfunc msqdif () { local i,j localobj m1,m2,md
  m1=$o1 m2=$o2
  md=new Matrix(m1.nrow,m1.ncol)
  for i=0,m1.nrow-1 for j=0,m1.ncol-1 md.x[i][j]=(m1.x[i][j]-m2.x[i][j])^2
  return md
}

//** mthresh(mat,th) - get matrix with mat elements thresholded : values < t set to 0, >= t to 1
obfunc mthresh () { local i,j,t localobj mi,mo
  mi=$o1 t=$2
  mo=new Matrix(mi.nrow,mi.ncol)
  for i=0,mo.nrow-1 for j=0,mo.ncol-1 if(mi.x[i][j]>=t) mo.x[i][j]=1 else mo.x[i][j]=0
  return mo
}

//** mdif(m1,m2) - get matrix with elements difference of m1-m2
obfunc mdif () { local i,j localobj m1,m2,md
  m1=$o1 m2=$o2
  md=new Matrix(m1.nrow,m1.ncol)
  for i=0,m1.nrow-1 for j=0,m1.ncol-1 md.x[i][j]=(m1.x[i][j]-m2.x[i][j])
  return md
}

//** getttmat(nqs,[column-name]) - uses NQS $o1 to make time-time correlation matrix
//optional $s2 , otherwise default column-name = 'vc'.
//column $s2 must be .odec with Vector objects
obfunc getttmat () { local i,j,inc,szm localobj mc,nq,v1,v2,str,lc
  {nq=$o1    str=new String()}
  if(numarg()>1)str.s=$s2 else str.s="vc"
  {szm=nq.v.size()  mc=new Matrix(szm,szm)  lc=new List()}
  for i=0,szm-1 lc.append(nq.get(str.s,i).o)
  for i=0,szm-1 {
    mc.x(i,i)=1
    v1=lc.o(i) 
    for j=i+1,szm-1 {
      v2=lc.o(j) 
      mc.x(i,j)=mc.x(j,i)=v1.pcorrel(v2)
    }
  }
  return mc
}

//** svmat(matrix,path,[writesz,binary]) - save a matrix to file as ascii, each row on new line
//$o1==matrix, $s2==file path -- will overwrite!! , $3 = optional == 1 to include nrows,ncols
// writesz = write rows,cols . binary - use binary output format, this will write using vwrite
// and first two elements of written vector will have rows,cols (so writesz arg is ignored)
func svmat () { local pr,bin,a localobj m,f,myv1,myv2,mt
  {m=$o1 a=allocvecs(myv1,myv2) f=new File() f.wopen($s2)}
  if(!f.isopen()) {
    printf("svmat ERRA: couldnt open output file %s\n",$s2)
    return 0
  }
  if(numarg()>2)pr=$3 else pr=0
  if(numarg()>3)bin=$4 else bin=0
  if(bin) {
    mt=$o1.transpose()
    mt.to_vector(myv1)
    myv2.append($o1.ncol,$o1.nrow)
    myv2.append(myv1)
    myv2.vwrite(f)
  } else {
    if(pr) m.fprint(f) else m.fprint(0,f)
  }
  {f.close() dealloc(a)}
  return 1
}

//obfunc rdmat () { local pr localobj m,f
// m=$o1
// f=new File()
// f.wopen($s2)
// if(!f.isopen()) {
//   printf("svmat ERRA: couldnt open output file %s\n",$s2)
//   return 0
// }
// if(numarg()>2)pr=$3 else pr=0
// if(pr) m.fprint(f) else m.fprint(0,f)
// f.close()
// return 1
//}

//** matimagesc - display a matrix ($o1) in matlab using matimgsc program
// or a text file $s1 , $2 = min scale value , $3 = max scale value, $4 optional
// binary input flag
func matimagesc () { local x,binflag localobj str
  if(numarg()>3) binflag=$4 else binflag=1
  str=new String2()
  if(argtype(1)==2) {
    str.s=$s1
  } else {
    str.s="__tmp__mat__ml__.txt"
    if(!svmat($o1,str.s,1,binflag)) return 0
  }
  sprint(str.t,"/usr/site/nrniv/local/matlab/matimgsc %s %g %g %d",str.s,$2,$3,binflag)
  x = system(str.t)
  return x
}

//** pyimagesc - display a matrix ($o1) in python's matplotlib or a text file $s1
//opt:[$2=min scaling for colors, $3=max scaling for colors, [$s4=title,$s5=xlabel,$s6=ylabel]
func pyimagesc () { local i,minc,maxc localobj str,cmd,strout,strt,strl,fp
  str=new String2()
  strout=new String()//collect stdout from script
  if(argtype(1)==2) {
    str.s=$s1
  } else {
    str.s="__tmp__mat__py__.txt"
    if(!svmat($o1,str.s)) return 0
  }
  if(numarg()>1)minc=$2 else minc=-1
  if(numarg()>2)maxc=$3 else maxc=1  
  if(numarg()>3) { //write title,xlabel,ylabel for pyimgsc.py
    {strl=new String() strl.s="__tmp__str__py__.txt"    fp=new File()}
    fp.wopen(strl.s)
    if(!fp.isopen()){
      printf("pyimagesc ERRB: couldnt save tmp file %s\n",strl.s)
      return 0
    }
    for i=4,numarg() fp.printf("%s\n",$si)
    fp.close()
    sprint(str.t,"/u/samn/python/pyimgsc.py %s %g %g %s",str.s,minc,maxc,strl.s)
  } else {
    sprint(str.t,"/u/samn/python/pyimgsc.py %s %g %g",str.s,minc,maxc)
  }
  return system(str.t,strout.s)
}

//** matgcspks(vec1,vec2,samplingrate,pathin1,pathin2,pathout,pid])
// this function calls /usr/site/nrniv/local/matlab/callmatgcspks to send a signal to
// /usr/site/nrniv/local/matlab/matgcspks and run MZD's granger causality on spike trains
// this function returns an NQS with 1 row containing output
// vec1,vec2 are binned spike trains (spikes per time)
// returns a vector containing vec1->vec2,  vec2->vec1 granger causality
obfunc matgcspks () { local sampr,pid localobj vspks1,vspks2,fpin1,fpin2,fpout,str,vop,strin,strout
  if(numarg()==0) {printf("matgcspks(vec1,vec2,samplingrate)\nvec1,2 are binned spike trains\n") return nil}
  vspks1=$o1 vspks2=$o2 sampr=$3 vop=new Vector(2)
  fpin1=new File() fpin2=new File() fpout=new File() str=new String() strin=new String2() strout=new String()  
  {strin.s=$s4 strin.t=$s5 strout.s=$s6 pid=$7}
  {fpin1.wopen(strin.s) fpin2.wopen(strin.t)}
  if(!fpin1.isopen()) {printf("matgcspks ERRA: couldn't open %s for writing\n",strin.s)  return nil}
  if(!fpin2.isopen()) {printf("matgcspks ERRA: couldn't open %s for writing\n",strin.t)  return nil}
  {vspks1.vwrite(fpin1)  fpin1.close() vspks2.vwrite(fpin2)  fpin2.close()}
  sprint(str.s,"/usr/site/nrniv/local/matlab/callmatgcspks %d",pid)
  {printf("%s\n",str.s) system(str.s)}
  fpout.ropen(strout.s)
  while(!fpout.isopen()){
    printf("matgcspks ERRB: couldn't open %s for reading\n",strout.s)
    fpout.ropen(strout.s)
  }
  vop.vread(fpout)
  return vop
}

//** matspecgram(vec,samplingrate,maxfrequency,fftwinsz,[,dodraw,mincolor,maxcolor])
// if fftwinsz <= 0, matspecgram will pick a WINDOW size for STFT
obfunc matspecgram () { local a,sampr,maxfreq,dodraw,rows,cols,x,y,minc,maxc,fftwinsz\
                       localobj vin,fpin,fpout,str,vop,vof,nqo,strin,strout,vtmp,strd
  vin=$o1 sampr=$2 maxfreq=$3 fftwinsz=$4 fpin=new File() fpout=new File()
  str=new String() strin=new String() strout=new String() strd=new String()
  a=allocvecs(vtmp,vop,vof)  if(numarg()>4)dodraw=$5 else dodraw=1  
  if(!fpin.mktemp || !fpout.mktemp) {
    print "matspecgram ERR0: couldn't make temp files!"
    {dealloc(a) return nil}
  }  
  {strin.s=fpin.getname strout.s=fpout.getname strd.s="/usr/site/nrniv/local/matlab" fpin.wopen(strin.s)}
  if(!fpin.isopen()){printf("matspecgram ERRA: couldn't open %s for writing\n",strin.s) dealloc(a) return nil}
  {vin.vwrite(fpin)  fpin.close()}
  if(dodraw && numarg()>=7) {
    sprint(str.s,"%s/matspecgram %s %g %g %d %d %s %g %g",strd.s,strin.s,sampr,maxfreq,fftwinsz,dodraw,strout.s,$6,$7)
  } else {
    sprint(str.s,"%s/matspecgram %s %g %g %d %d %s",strd.s,strin.s,sampr,maxfreq,fftwinsz,dodraw,strout.s)
  }
  print str.s
  system(str.s)
  fpout.ropen(strout.s) 
  if(!fpout.isopen()){printf("matspecgram ERRB: couldn't open %s for reading\n",strout.s) dealloc(a) return nil}
  {vop.vread(fpout) vof.vread(fpout)}  
  {nqo=new NQS("f","pow")  nqo.odec("pow")}
  {rows=vof.size() cols=vop.size()/rows x=0}
  for y=0,rows-1 { vtmp.resize(0)
    vtmp.copy(vop,x,x+cols-1)
    nqo.append(vof.x(y),vtmp)
    x+=cols
  }
  {fpin.unlink() fpout.unlink()}
  {dealloc(a) return nqo}
}

//** matmodind(vec,samplingrate,lohz1,lohz2,hihz1,hihz2)
// this function calls /usr/site/nrniv/local/matlab/matmodindex to run Canolty's modulation index with Matlab
// returns an NQS with 1 row containing output
obfunc matmodind () { local a,sampr,lohz1,lohz2,hihz1,hihz2\
                       localobj vin,fpin,fpout,str,vop,nqo,strin,strout
  if(numarg()==0) {printf("matmodind(vec,samplingrate,lohz1,lohz2,hihz1,hihz2)\n") return nil}
  vin=$o1 sampr=$2 lohz1=$3 lohz2=$4 hihz1=$5 hihz2=$6
  fpin=new File() fpout=new File() str=new String() strin=new String() strout=new String()
  a=allocvecs(vop)
  if(!fpin.mktemp || !fpout.mktemp) {
    print "matmodind ERR0: couldn't make temp files!"
    {dealloc(a) return nil}
  }
  {strin.s=fpin.getname strout.s=fpout.getname}
  {fpin.wopen(strin.s)}
  if(!fpin.isopen()) {printf("matmodind ERRA: couldn't open %s for writing\n",strin.s) dealloc(a) return nil}
  {vin.vwrite(fpin)  fpin.close()}
  sprint(str.s,"/usr/site/nrniv/local/matlab/matmodindex %s %g %g %g %g %g %s",strin.s,sampr,lohz1,lohz2,hihz1,hihz2,strout.s)
  print str.s
  system(str.s)
  fpout.ropen(strout.s) 
  if(!fpout.isopen()){printf("matmodind ERRB: couldn't open %s for reading\n",strout.s) dealloc(a) return nil}
  {vop.vread(fpout) nqo=new NQS("modind","phase","lohz1","lohz2","hihz1","hihz2")}
  nqo.append(vop.x(0),vop.x(1),lohz1,lohz2,hihz1,hihz2)
  {dealloc(a) fpin.unlink() fpout.unlink()}
  return nqo
}

//** matpmtm(vec,samplingrate)
// this function calls /usr/site/nrniv/local/matlab/matpmtm to run multitaper power spectra using matlab, returns an nqs
obfunc matpmtm () { local a,sampr,rows,cols,x,y\
                       localobj vin,fpin,fpout,str,vop,vof,nqo,strin,strout
  if(numarg()==0) {printf("%s\n","matpmtm(vec,samplingrate)") return nil}
  vin=$o1 sampr=$2 fpin=new File() fpout=new File() str=new String() strin=new String() strout=new String()
  a=allocvecs(vop,vof)  
  if(!fpin.mktemp || !fpout.mktemp) {
    print "matpmtm ERR0: couldn't make temp files!"
    {dealloc(a) return nil}
  }
  {strin.s=fpin.getname strout.s=fpout.getname}
  {fpin.wopen(strin.s)}
  if(!fpin.isopen()) {printf("matpmtm ERRA: couldn't open %s for writing\n",strin.s) dealloc(a) return nil}
  {vin.vwrite(fpin)  fpin.close()}
  sprint(str.s,"/usr/site/nrniv/local/matlab/matpmtm %s %g %s",strin.s,sampr,strout.s)
  print str.s
  system(str.s)
  fpout.ropen(strout.s) 
  if(!fpout.isopen()){printf("matpmtm ERRB: couldn't open %s for reading\n",strout.s) dealloc(a) return nil}
  {vop.vread(fpout) vof.vread(fpout) nqo=new NQS("f","pow")}
  {nqo.v[0].copy(vof) nqo.v[1].copy(vop) dealloc(a) fpin.unlink() fpout.unlink()}
  return nqo
}

//** matfftpow(vec,samplingrate,maxfrequency,[dodraw,dosmooth,smoothwindowsz])
// this function calls /usr/site/nrniv/local/matlab/matfftpow to run power spectra using matlab, returns an nqs
// dosmooth controls whether to smooth output, is OFF by default
// smoothwindowsz controls size of running average smoothing of power spectra output
obfunc matfftpow () { local a,sampr,maxfreq,dodraw,rows,cols,x,y,dosmooth\
                       localobj vin,fpin,fpout,str,vop,vof,nqo,strin,strout
  if(numarg()==0) {printf("%s\n","matfftpow(vec,samplingrate,maxfrequency,[dodraw,dosmooth,smoothwindowsz])") return nil}
  vin=$o1 sampr=$2 maxfreq=$3 fpin=new File() fpout=new File() str=new String() strin=new String() strout=new String()
  a=allocvecs(vop,vof)  if(numarg()>3)dodraw=$4 else dodraw=1
  if(numarg()>4)dosmooth=$5 else dosmooth=0
  if(!fpin.mktemp || !fpout.mktemp) {
    print "matfftpow ERR0: couldn't make temp files!"
    {dealloc(a) return nil}
  }
  {strin.s=fpin.getname strout.s=fpout.getname}
  {fpin.wopen(strin.s)}
  if(!fpin.isopen()) {printf("matfftpow ERRA: couldn't open %s for writing\n",strin.s) dealloc(a) return nil}
  {vin.vwrite(fpin)  fpin.close()}
  if(numarg()>5) {
    sprint(str.s,"/usr/site/nrniv/local/matlab/matfftpow %s %g %d %d %s %d %d",strin.s,sampr,maxfreq,dodraw,strout.s,dosmooth,$6)
  } else sprint(str.s,"/usr/site/nrniv/local/matlab/matfftpow %s %g %d %d %s %d",strin.s,sampr,maxfreq,dodraw,strout.s,dosmooth)
  print str.s
  system(str.s)
  fpout.ropen(strout.s) 
  if(!fpout.isopen()){printf("matfftpow ERRB: couldn't open %s for reading\n",strout.s) dealloc(a) return nil}
  {vop.vread(fpout) vof.vread(fpout) nqo=new NQS("f","pow")}
  {nqo.v[0].copy(vof) nqo.v[1].copy(vop) dealloc(a) fpin.unlink() fpout.unlink()}
  return nqo
}

//** mathilbert(vec,samplingrate,minfrequency,maxfrequency)
obfunc mathilbert () { local a,sampr,minfreq,maxfreq\
                       localobj vin,fp,str,vfilt,vph,vamp,nqo,strin,strout
  vin=$o1 sampr=$2 minfreq=$3 maxfreq=$4 fp=new File() str=new String() strin=new String() strout=new String()
  a=allocvecs(vfilt,vph,vamp) 
  {sprint(strin.s,"__tmp__mat__hilbert__input__vec__.vec")  sprint(strout.s,"__tmp__mat__hilbert_output__vec__.vec")}
  {fp.wopen(strin.s)}
  if(!fp.isopen()) {
    printf("mathilbert ERRA: couldn't open %s for writing\n",strin.s)
    dealloc(a)
    return nil
  }
  {vin.vwrite(fp)  fp.close()}
  sprint(str.s,"/usr/site/nrniv/local/matlab/mathilbert %s %g %g %g %s",strin.s,sampr,minfreq,maxfreq,strout.s)
  print str.s
  system(str.s)
  fp.ropen(strout.s) 
  if(!fp.isopen()) {
    printf("mathilbert ERRB: couldn't open %s for reading\n",strout.s)
    dealloc(a)
    return nil
  }
  {vfilt.vread(fp) vph.vread(fp) vamp.vread(fp) nqo=new NQS("filt","phase","amp","t")}
  {nqo.v[0].copy(vfilt) nqo.v[1].copy(vph) nqo.v[2].copy(vamp)}
  {nqo.v[3].indgen(0,1e3*nqo.v[2].size/sampr,1e3/sampr)  nqo.v[3].resize(nqo.v[2].size)}
  dealloc(a)
  return nqo
}

//** matprincomp(input Matrix object)
// returns list with : eigenvectors as Vector, scores as Vector, eigenvalues as Vector, scores as Matrix
// scores has same size as $o1, eigenvectors is $o1.ncols^2, eigenvalues is $o1.ncols
// input matrix has rows as observations and columns as dimensions
obfunc matprincomp () { local i,j,k localobj mcin,fp,str,strin,strout,lsout,vcoeff,vscore,vlat,mscore
  mcin=$o1 fp=new File() str=new String() strin=new String() strout=new String() lsout=new List()
  {vcoeff=new Vector() vscore=new Vector() vlat=new Vector()}
  {sprint(strin.s,"__tmp__mat__princomp__input__mat__.txt")  sprint(strout.s,"__tmp__mat__princomp_output__vec__.vec")}
  if(!svmat(mcin,strin.s,1)) {
    printf("matprincomp ERRA: couldn't open %s for writing\n",strin.s)
    return nil
  }
  sprint(str.s,"/usr/site/nrniv/local/matlab/matprincomp %s %s",strin.s,strout.s)
  print str.s
  system(str.s)
  fp.ropen(strout.s) 
  if(!fp.isopen()) {
    printf("matprincomp ERRB: couldn't open %s for reading\n",strout.s)
    return nil
  }
  {vcoeff.vread(fp) vscore.vread(fp) vlat.vread(fp) fp.close()}
  mscore=new Matrix(mcin.nrow,mcin.ncol)
  mscore.from_vector(vscore) //reads it in in column major order
  {lsout.append(vcoeff) lsout.append(vscore) lsout.append(vlat) lsout.append(mscore)}
  return lsout
}

//** matmin(mat) - return min element of mat
func matmin () { local i,j,me,tmp localobj m
  m=$o1 
  me=m.getrow(0).min()
  for i=1,m.nrow-1 if((tmp=m.getrow(i).min)<me) me=tmp
  return me
}

//** matmax(mat) - return max element of mat
func matmax () { local i,j,me,tmp localobj m
  m=$o1 
  me=m.getrow(0).max()
  for i=1,m.nrow-1 if((tmp=m.getrow(i).max)>me) me=tmp
  return me
}

//** mlk(mat) - use vlk to print rows of matrix
// a matrix will have it's lower/smaller rows printed first:
//    1 2 3 
//    4 5 6 
//    7 8 9 
proc mlk () { local i localobj m
  m=$o1
  for i=0,m.nrow-1 vlk(m.getrow(i))
}

//** mateq(mat1,mat2) - return 1 iff matrix row Vectors are eq, 0 otherwise
func mateq () { local i localobj m1,m2
  m1=$o1 m2=$o2
  if(m1.nrow!=m2.nrow || m1.ncol!=m2.ncol) return 0
  for i=0,m1.nrow-1 if(m1.getrow(i).eq(m2.getrow(i))==0) return 0
  return 1
}

//** matavg - return average value in Matrix $o1
func matavg () { local i,s localobj m
  m=$o1
  if(m.nrow<1 || m.ncol<1) {
    printf("matavg ERRA: empty matrix!\n")
    return 0
  }
  s=0
  for i=0,m.nrow-1 s += m.getrow(i).sum()
  return s/(m.nrow*m.ncol)
}

//** avgmat(list of Matrix) - return Matrix that has its elements avg of elements in $o1 List
obfunc avgmat () { local sz,i localobj ma
  sz=$o1.count
  if(sz<1) return nil
  ma=new Matrix($o1.o(0).nrow,$o1.o(0).ncol)
  for i=0,sz-1 ma.add($o1.o(i))
  ma.muls(1.0/sz)
  return ma
}

//** stdmat(list of Matrix) - return Matrix that has its elements stdev of elements in $o1 List
obfunc stdmat () {  local sz,i,j,k localobj ms,ma
  sz=$o1.count
  if(sz<1) return nil
  ma=new Matrix($o1.o(0).nrow,$o1.o(0).ncol)
  ms=new Matrix($o1.o(0).nrow,$o1.o(0).ncol)
  for i=0,sz-1 for j=0,ma.nrow-1 for k=0,ma.ncol-1 {
    ms.x(j,k) += $o1.o(i).x(j,k)^2
    ma.x(j,k) += $o1.o(i).x(j,k)
  }
  ma.muls(1.0/sz)
  ms.muls(1.0/sz)  
  for j=0,ma.nrow-1 for k=0,ma.ncol-1 {
    ms.x(j,k) -= ma.x(j,k)^2
    if(ms.x(j,k) > 1e-9) ms.x(j,k) = sqrt(ms.x(j,k)) else ms.x(j,k) = 0
  }
  return ms
}

//** chgmat(list of before Matrices, list of after Matrices) - returns change in each entry in units of std-dev
obfunc chgmat () { local szbef,szaft,i,j,k localobj lbef,laft,mavg,mstd,lchg,mchg,mt
  lbef=$o1 laft=$o2
  szbef=lbef.count szaft=laft.count
  lchg=new List()
  mavg=avgmat(lbef)
  mstd=stdmat(lbef)
  mchg=new Matrix(mavg.nrow,mavg.ncol)
  for i=0,szaft-1 {
    mt=laft.o(i)
    for j=0,mt.nrow-1 for k=0,mt.ncol-1 {
      if(mstd.x(j,k)>1e-9) {
        mchg.x(j,k) += ( mt.x(j,k) - mavg.x(j,k) ) / mstd.x(j,k)
      } else if(szbef==1) {
        mchg.x(j,k) += ( mt.x(j,k) - mavg.x(j,k) ) 
      }
    }
  }
  return mchg
}

//** getlv(rows,cols) - make a List of Vectors as 2D array
//$1 == # of rows (vectors), $2 == # of cols (size of vectors)
obfunc getlv () { local idx,rows,cols localobj ls
  ls=new List()
  rows=$1 cols=$2
  for idx=0,rows-1 ls.append(new Vector(cols))
  return ls
}

//** vec2mat(vec,rows) - get a matrix from a vec -- row major order
obfunc vec2mat () { local i,j,k,rows,cols localobj vin,mout
  vin=$o1 rows=$2 cols=vin.size/rows mout=new Matrix(rows,cols) k=0
  for i=0,rows-1 for j=0,cols-1 {
    mout.x(i,j)=vin.x(k)
    k+=1
  }
  return mout
}

//** mat2vec(mat) - get a vec from a matrix -- row major order 
obfunc mat2vec () { local i,j,k,rows,cols localobj mat,vout
  mat=$o1 rows=mat.nrow cols=mat.ncol i=j=k=0 vout=new Vector(rows*cols)
  for i=0,rows-1 for j=0,cols-1 {
    vout.x(k)=mat.x(i,j)
    k+=1
  }
  return vout
}
//** mltmed(mat) - get median values from lower-triangular portion - lower triang. means smaller rows
// this matrix printed as (with printf or mlk):
//    1 2 3 
//    4 5 6 
//    7 8 9 
// will have mltmed of 3, since uses 2,3,6 from bottom of matrix to get median
func mltmed () { local i,j,a localobj m,vo
  a=allocvecs(vo) m=$o1
  for i=0,m.nrow-1 for j=i+1,m.ncol-1 vo.append(m.x(i,j))
  return vo.median()
}
//** mzerout(mat) - zero out everything >= diagonal
// a matrix printed as (with printf or mlk):
//    1 2 3 
//    4 5 6 
//    7 8 9 
// will end up as:
//    0 2 3 
//    0 0 6 
//    0 0 0 
proc mzerout () { local i,j,a localobj m,vo
  a=allocvecs(vo) m=$o1
  for i=0,m.nrow-1 for j=0,i m.x(i,j)=0
}
//** matsqsymm(matrix) - return 1 iff matrix is square and symmetric
func matsqsymm () { local i,j localobj mc
  mc=$o1  if(mc.nrow!=mc.ncol) return 0
  for i=0,mc.nrow-1 for j=i+1,mc.ncol-1 if(mc.x(i,j)!=mc.x(j,i)) return 0
  return 1
}
//** getsubmat(matrix,startx,endx,starty,endy) - copy subsection of matrix
// and return in new output matrix
obfunc getsubmat () { local x,y,startx,endx,starty,endy localobj m1,msub
  m1=$o1
  startx=$2 endx=$3 starty=$4 endy=$5
  msub=new Matrix(endy-starty+1,endx-startx+1)
  for y=starty,endy for x=startx,endx msub.x(y-starty,x-startx)=m1.x(y,x)
  return msub
}

Kerr CC, Neymotin SA, Chadderdon GL, Fietkiewicz CT, Francis JT, Lytton WW (2012) Electrostimulation as a prosthesis for repair of information flow in a computer model of neocortex IEEE Transactions on Neural Systems & Rehabilitation Engineering 20(2):153-60[PubMed]

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