NEURON interfaces to MySQL and the SPUD feature extraction algorithm (Neymotin et al. 2008)

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Accession:97868
See the readme.txt for information on setting up this interface to a MySQL server from the NEURON simulator. Note the SPUD feature extraction algorithm includes its own readme in the spud directory.
Reference:
1 . Neymotin S, Uhlrich DJ, Manning KA, Lytton WW (2008) Data mining of time-domain features from neural extracellular field data Applic. of Comput. Intel. in Bioinf. and Biomed.: Current Trends and Open Problems 151:119-140
Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Lytton, William [billl at neurosim.downstate.edu]; Neymotin, Sam [samn at neurosim.downstate.edu];
Files displayed below are from the implementation
// $Id: decnqs.hoc,v 1.30 2009/08/28 19:08:39 billl Exp $

load_file("nqs.hoc")
objref nq[10],pq[10]

//** prl2nqs(NQS[,min,max,nointerp]) -- transfer printlist to NQS
proc rename () {}
// eg proc rename () { sprint($s1,"P%d",objnum($s1)) }
proc prl2nqs () { local tstep localobj st
  st=new String2()
  if (!isassigned($o1)) $o1=new NQS() else $o1.resize(0)
  if (numarg()>=2) min=$2 else min=0
  if (numarg()>=3) max=$3 else max=printlist.count-1
  if (numarg()>=4) interp=$4 else interp=0 // no interp when looking at spk times
  if (interp) $o1.resize(max-min+2)
  if (interp) {
    tstep=0.1 // 0.1 ms step size for interpolation
    $o1.s[0].s="time"
    $o1.v[0].indgen(0,printlist.object(0).tvec.max,tstep)
    for ii=min,max {
      XO=printlist.object(ii)
      $o1.s[ii+1-min].s = XO.var
      rename($o1.s[ii+1-min].s)
      $o1.v[ii+1-min].resize($o1.v.size)
      $o1.v[ii+1-min].interpolate($o1.v[0],XO.tvec,XO.vec)
    }
  } else {
    for ii=min,max {
      XO=printlist.object(ii)
      st.s=XO.name
      sprint(st.t,"%s-time",XO.name)
      rename(st.s) rename(st.t)
      $o1.resize(st.s,st.t)
      $o1.setcols(XO.vec,XO.tvec)
    }
  }
}

//** pvp2nqs(NQS) -- transfer grvec data file to NQS
proc pvp2nqs () { local tstep,tv1,v1
  if (! read_vfile(1,$s1)) { printf("Can't open %s\n",$s1) return }
  if (numarg()>=3) min=$3 else min=0
  if (numarg()>=4) max=$4 else max=panobj.llist.count-1
  if (numarg()>=5) interp=$5 // no interp when looking at spk times
  if (interp) $o2.resize(max-min+2) else $o2.resize(2*(max-min+1))
  if (interp) {
    tv1=v1=allocvecs(2)  v1+=1
    tstep=0.1 // 0.1 ms step size for interpolation
    $o2.s[0].s="time"
    for ii=min,max {
      XO=panobj.llist.object(ii)
      $o2.s[ii+1-min].s = XO.name
      rename($o2.s[ii-min+1].s)
      panobj.tmpfile.seek(XO.loc)
      mso[tv1].vread(panobj.tmpfile)
      mso[v1].vread(panobj.tmpfile) // or use rv_readvec
      if (ii-min==0) $o2.v[0].indgen(0,mso[tv1].max,tstep)
      $o2.v[ii+1-min].resize($o2.v.size)
      $o2.v[ii+1-min].interpolate($o2.v[0],mso[tv1],mso[v1])
    }
    dealloc(tv1)
  } else for ii=min,max {
    XO=panobj.llist.object(ii)
    $o2.s[2*(ii-min)].s = XO.name
    rename($o2.s[2*(ii-min)].s)
    sprint($o2.s[2*(ii-min)].s,"%s-time",$o2.s[2*(ii-min)].s)
    $o2.s[2*(ii-min)+1].s = XO.name
    rename($o2.s[2*(ii-min)+1].s)
    panobj.tmpfile.seek(XO.loc)
    $o2.v[2*(ii-min)].vread(panobj.tmpfile)
    $o2.v[2*(ii-min)+1].vread(panobj.tmpfile)
  }
}

//** veclist2nqs(nqs[,STR1,STR2,...])
proc veclist2nqs () { local flag,i
  if (numarg()==0) {printf("veclist2nqs(nqs[,STR1,STR2,...])\n") return}
  $o1.resize(veclist.count)
  if (numarg()==1+$o1.m) flag=1 else flag=0
  for ltr(XO,veclist) {
    $o1.v[i1].copy(XO)
    if (flag) {i=i1+2 $o1.s[i1].s=$si} else {sprint(tstr,"v%d",i1) $o1.s[i1].s=tstr}
  }
  $o1.cpout()
}

// fudup(vec[,nq,#CUTS,LOGCUT,MIN]) -- use updown() to find spikes
// LOC(0) PEAK(1) WIDTH(2) BASE(3) HEIGHT(4) START(5) SLICES(6) SHARP(7) INDEX(8) FILE(9) NESTED(10)
// other options
pos_fudup=1 // set to 1 to move whole curve up above 0
maxp_fudup=0.95 // draw top sample at 95% of max 
minp_fudup=0.05 // draw bottom sample at 5% of max
over_fudup=1    // turn over and try again if nothing found
allover_fudup=0 // turn over and add these locs (not debugged)
verbose_fudup=0 // give messages, can also turn on DEBUG_VECST for messages from updown()
obfunc fudup () { local a,i,ii,npts,logflag,min,x,sz localobj bq,cq,v1,v2,v3,bb,tl,v5,eq
  if (verbose_fudup) printf("MAXTIME appears to be %g (dt=%g)\n",$o1.size*dt,dt)
  logflag=0  npts=10 // n sample locations by default
  bq=new NQS("LOC","PEAK","WIDTH","BASE","HEIGHT","START","SLICES","SHARP","INDEX","FILE","NESTED") 
  i=2
  if (argtype(i)==1) {i+=1 if ($o2==nil) {cq=new NQS() $o2=cq} else cq=$o2} else cq=new NQS()
  if (cq.m!=11) { cq.resize(0) 
  cq.resize("LOC","PEAK","WIDTH","BASE","HEIGHT","START","SLICES","SHARP","INDEX","FILE","NESTED")}
  if (argtype(i)==0){ npts=$i i+=1
    if (argtype(i)==0){ logflag=$i i+=1
      if (argtype(i)==1) { v5=$oi i+=1
        if (npts!=v5.size) printf("Correcting npts from %d to %d\n",npts,npts=v5.size)
        if (v5.ismono(1)) v5.reverse
        if (! v5.ismono(-1)) {printf("fudup: final arg (%s) must be monotonic\n",v5) return}
      }
    }
  }
  bq.listvecs(bb)
  bq.pad(5000)
  eq=new NQS(-2,npts) a=allocvecs(v1,v2,v3)
  tl=eq.vl
  eq.clear(2e4) vrsz(2e4,v1,v2,v3)
  v1.copy($o1)
  if (pos_fudup) {
    min=v1.min
    v1.sub(min) // make it uniformly positive
  } else min=0
  if (numarg()>4) v2.copy(v5) else {
    v2.indgen(2,2+npts-1,1)   // sampling at npts points, start at 2 to avoid log(1)=0
    if (logflag) v2.log() // log sampling
    v2.scale(-maxp_fudup*v1.max,-minp_fudup*v1.max) v2.mul(-1)
  }
  v1.updown(v2,tl,bb)
  if (pos_fudup) { bq.v[1].add(min) bq.v[3].add(min) }
  cq.append(bq)
  sz=bq.size(1)
  if (allover_fudup) { // do it upside down as well
    v1.mul(-1) // v2 will be upside-down
    if (pos_fudup) {min=v1.min v1.sub(min)}
    if (0) {  // can't see a rationale to recalc sampling points
      v2.indgen(2,2+npts-1,1)   // sampling at npts points
      if (logflag) v2.log() // log sampling
      v2.scale(-0.95*v1.max,-0.05*v1.max) v2.mul(-1)
    }
    v1.updown(v2,tl,bb)
    bq.v[8].add(sz) bq.v[4].mul(-1) // turn HEIGHT upside down
    cq.append(bq)
  } else if (over_fudup && sz==0) { // turn it over an try again
    print "fudup() checking upside-down"
    v1.mul(-1) // v2 will be upside-down
    v1.updown(v2,tl,bb)
  } 
  for case(&x,0,2,5) cq.v[x].mul(dt)
  nqsdel(bq,eq)
  dealloc(a)
  return cq
}

//** listsort(LIST[,START,REV]) sorts list of strings numerically
// optional start gives a regexp to start at
proc listsort () { local x,rev localobj nq,st,xo
  if (numarg()==0) { 
    print "listsort(LIST[,RXP,REV]) numerically, optional RXP starts after there" return}
  if (numarg()==3) if ($3) rev=-1 else rev=0
  nq=new NQS("STR","NUM") nq.strdec("STR")
  st=new String()
  for ltr(xo,$o1) {
    if (numarg()>=2) sfunc.tail(xo.s,$s2,st.s) else st.s=xo.s
    if (sscanf(st.s,"%g",&x)!=1) print "listsort ERR: num not found in ",st.s
    nq.append(xo.s,x)
  } 
  nq.sort("NUM",rev)
  $o1.remove_all
  for nq.qt(st.s,"STR") $o1.append(new String(st.s))
}

// stat(VEC) print stats for the vector
// stat(VEC1,VEC2) append stats of VEC1 on VEC2
// stat(VEC1,NQS) append stats of VEC1 on NQS (create if necessary)
proc stat () { local sz
  sz=$o1.size
  if (sz<=1) {printf("decnqs::stat() WARN: %s size %d\n",$o1,$o1.size) return}
  if (numarg()==1 && sz>1) {
    printf("Sz:%d\tmax=%g; min=%g; mean=%g; stdev=%g\n",$o1.size,$o1.max,$o1.min,$o1.mean,$o1.stdev)
  } else {
    if (!isassigned($o2)) { $o2=new NQS("SIZE","MAX","MIN","MEAN","STDEV")
    } else if (isobj($o2,"NQS")) { 
      if ($o2.m!=5) {$o2.resize(0) $o2.resize("SIZE","MAX","MIN","MEAN","STDEV")}
    } else if (isobj($o2,"Vector")) revec($o2)
    if (sz>2) {$o2.append($o1.size,$o1.max,$o1.min,$o1.mean,$o1.stdev) // .append for Vector or NQS
    } else   $o2.append($o1.size,$o1.max,$o1.min,$o1.min,0) // no sdev
  }
}

//* fil2nqs(FILE,NQS) reads lines of file and places all numbers in NQS
func fil2nqs () { local a,n localobj v1
  $o2.clear
  a=allocvecs(v1)
  tmpfile.ropen($s1)
  for (n=1;tmpfile.gets(tstr)!=-1;n+=1) {
    if (n%1e3==0) printf("%d ",n)
    parsenums(tstr,v1)
    if (v1.size!=$o2.m) {
      printf("Wrong size at line %d (%d)  ",n,v1.size)  vlk(v1)
      return
    }
    $o2.append(v1)
  }
  dealloc(a)
  return $o2.size(1)
}

//** plnqs(file,NQS) reads output of txt2num.pl
// format ascii 'rows cols' then binary contents
proc plnqs () { local a,rows,cols localobj v1,v2
  a=allocvecs(v1,v2)
  tmpfile.ropen($s1)
  tmpfile.gets(tstr)
  sscanf(tstr,"%d %d",&rows,&cols)
  printf("%s: %d rows x %d cols\n",$s1,rows,cols)
  v1.fread(tmpfile,rows*cols) // could now use .transpose
  v2.indgen(0,rows*cols,cols)
  $o2.resize(cols,rows)
  for ii=0,cols-1 {
    v2.add(ii)
    $o2.v[ii].index(v1,v2)
  }
  dealloc(a)
}
    
// DEST=maxem(SRC,MIN,WIDTH) -- keep looking for maxima till get down to min
obfunc maxem () { local a,min,wid,ii,ix,beg,end localobj v1,aq
  a=allocvecs(v1)
  aq=new NQS("max","loc") aq.clear(v1.size/2)
  v1.copy($o1)
  min=$2 wid=$3
  while(v1.max>min) {
   aq.append(v1.max,ix=v1.max_ind)
   beg=ix-wid if (beg<0) beg=0
   end=ix+wid if (end>=v1.size) end=v1.size-1
   for ii=beg,end v1.x[ii]=-1e9
  }
  dealloc(a)
  return aq
}

// nqo=percl(nq,"COLA", ..) generates NQS of percentile values (10..90) for these cols
// nqo=percl(nq,min,max,step,"COLA", ..) -- eg percl(nq,50,70,5,"COLA","COLB")
obfunc percl () {  local i,ii,a,p localobj v1,v2,v3,aq,xo
  a=allocvecs(v1,v2,v3)
  aq=new NQS(numarg())
  if (argtype(2)==0) {
    v3.indgen($2,$3,$4) 
    aq.resize(aq.size(1)-3)
    i=5 j=4 // start at arg i and aq col #j
  } else {
    v3.indgen(10,90,10)
    i=2 j=1
  }
  aq.setcol(0,"PERCL",v3)
  for (;i<=numarg();i+=1) {
    $o1.getcol($si,v1)
    v1.sort()
    v2.resize(0)
    for vtr(&ii,v3) {ii/=100 v2.append(v1.x[round(ii*v1.size)])}
    aq.setcol(i-j,$si,v2)
  }
  dealloc(a)
  return aq
}

// pqunq(NQS) returns columns of sorted nique values corresponding to the arg
// NB: does not produce a rectangular array
obfunc pqunq () { local a localobj v1,v2,aq
  aq=new NQS()
  a=allocvecs(v1,v2,1e5)
  aq.sethdrs($o1)
  aq.resize(-2) 
  for ii=0,aq.m-1 {
    $o1.getcol(ii,v1)
    v1.sort 
    v2.redundout(v1)
    aq.v[ii].copy(v2)
  }
  dealloc(a)
  return aq
}

//** aa=seqind(ind) -- find beginning and end of sequential indices with 
obfunc seqind () { local a,n,skip,ii,x,last localobj vi,oq
  vi=$o1
  if (numarg()>=2) skip=$2+1 else skip=1
  if (numarg()>=3) oq=$o3
  if (!isassigned(oq)) {oq=new NQS() if (numarg()>=3) $o3=oq}
  if (oq.m!=3) { oq.resize(0) oq.resize("beg","end","diff") }
  oq.clear()
  n=last=0
  for ii=1,vi.size(1)-1 {
    if (vi.x[ii]-vi.x[ii-1]>skip) {
      if (n>0) oq.append(vi.x[last],vi.x[ii-1],0)
      last=ii
      n=0
    } else n+=1
  }
  if (n>0) oq.append(vi.x[last],vi.x[ii-1],0)
  oq.pad()
  oq.calc("<diff>.copy(<end>.c.sub(<beg>))")
  return oq
}

//** list_transpose
proc list_transpose () { localobj aq,mat,xo,inlist,outlist
  aq=new NQS() inlist=$o1 outlist=$o2
  if (!isojt(outlist,inlist)) {outlist=new List() $o2=outlist}
  for ltr(xo,inlist) aq.resize("",xo)
  mat=aq.tomat(1) // transpose
  aq.frmat(mat)
  outlist.remove_all
  aq.listvecs(outlist)
  delnqs(aq)
}

//* Sam's additions -- moved from nqs_utils.hoc
//get row of Vectors
//$o1 = nqs
//$2 = row number
//$s3 - $snumarg() - name of cols to get values for
//returns list with associated Vectors
obfunc getobjrow(){ local i,rowid localobj nq,vt,ls
  nq=$o1 rowid=$2
  ls=new List()
  vt=new Vector()
  for(i=3;i<=numarg();i+=1){
    nq.get($si,rowid,vt)
    ls.append(vt)
  }
  return ls
}

//get column of objects as Vector using oform
//$o1 = nqs
//$s2 = col name
//$3=iff==1 return list of Vectors in column, else return vector of oform of each row in column
obfunc getobjcol(){ local idx,getl localobj nq,vt,vt2,ls
  nq=$o1
  if(numarg()>2) getl=$3 else getl=0
  if(getl){
    ls=new List()
    vt=new Vector()
    for idx=0,nq.size-1{
      nq.get($s2,idx,vt)
      ls.append(vt)
    }
    return ls
  } else {
    vt=new Vector(nq.size)
    vt.resize(0)
    vt2=new Vector()
    for idx=0,nq.size-1{
      nq.get($s2,idx,vt2)
      vt.append(oform(vt2))
    }
    return vt
  }
}

//get correlation between 2 columns of an NQS
//$o1=nqs
//$s2=column name
//$s3=column name
//$4=pearson correlation iff == 1 (default), otherwise spearman
func nqcor(){ local pc localobj nq1,v1,v2
  if(numarg()>3) pc=$4 else pc=1
  nq1=$o1
  v1=nq1.getcol($s2)  v2=nq1.getcol($s3)
  if (pc) return v1.pcorrel(v2) else return v1.scorrel(v2)
}

//func nqgrslice(){ local startidx,endidx localobj nq,vtmp
//  nq=$o1 startidx=$2 endidx=$3
//  vtmp=new Vector($3-$2+1)
//  gg(
//}

func MIN(){ if($1<$2)return $1 else return $2 }

//get correlation matrix/nqs of all columns to all columns
//$o1 = NQS
//$2 = num columns 0 - NQS.m
//$3 = start row/index
//$4 = end row/index
//$5 = index increment
//$6 = window size , iff <= 0, do full columns against each other
obfunc nqcolcor(){ local startidx,endidx,inct,wint,c1,c2,ncol localobj vhr,vhl,nqc,nqf
 if(numarg()<1){
   printf("nqcolcor usage: \n\t$o1 = NQS\
                           \n\t$2 = num columns 0 - NQS.m\
                           \n\t$3 = start row/index\
                           \n\t$4 = end row/index\
                           \n\t$5 = index increment\
                           \n\t$6 = window size , iff <= 0, do full columns against each other\n")
   return nil
 }
 nqf=$o1
 if(numarg()>1) ncol=$2 else ncol=nqf.m
 if(numarg()>2) startidx=$3 else startidx=0
 if(numarg()>3) endidx=$4 else endidx=nqf.size
 if(numarg()>4) inct=$5 else inct=50*2//50ms
 if(numarg()>5) wint=$6 else wint=100*2//50ms

 vhr=new Vector(wint) vhl=new Vector(wint)

 if(wint<=0){ //full column cross-correlation
   nqc=new NQS("ID0","ID1","cor") 
   for c1=0,ncol-1{
     for c2=c1+1,ncol-1{
       nqc.append(c1,c2,nqf.v[c1].pcorrel(nqf.v[c2]))
     }
   }
 } else { //cross correlation using slices of column
   nqc=new NQS("ID0","ID1","start","end","cor") 
   for c1=0,ncol-1{
     for c2=c1+1,ncol-1{
       for(startidx=0;startidx<endidx;startidx+=inct){
         vhl.copy(nqf.v[c1],startidx,MIN(startidx+wint,endidx-1))
         vhr.copy(nqf.v[c2],startidx,MIN(startidx+wint,endidx-1))
         nqc.append(c1,c2,startidx,startidx+wint,vhl.pcorrel(vhr))
       }
     }
   }
 }

 return nqc
}

 
//read wmf ascii file (just skips header and calls rdcol)
//$s1 = wmf file path
//$2 = # of columns
// obfunc rdwmf(){ local idx,jdx,hdrlines localobj nq,myf,myftmp,strf,str,strtmp,lcols
// myf=new File() myftmp=new File() strf=new StringFunctions() str=new String() lcols=new List()
// strtmp=new String() hdrlines=6
// myf.ropen($s1)
// if(!myf.is_open()){
//  printf("rdwmf ERRA: couldn't open wmf file %s for read\n",$s1)
//  return nil
// }
// for idx=0,hdrlines-1{
//  if(myf.gets(str.s)==-1){
//    printf("rdwmf ERRB: corrupt header\n")
//    return nil
//  } else if(idx==2){
//    jdx=strf.tail(str.s,"",strtmp.s)            
//  }
// }
// myf.close()
// return nq
// }

//draw regression line
//$o1 = nqs, $s2 = column 1, $s3 = column 2
// or
//$o1 = Vector 1 , $o2 = Vector 2
//returns vo
obfunc drawregline(){ local x0,y0,x1,y1,gvtmp,r localobj vo,nq,v1,v2,vx,vy,str
  vo=new Vector(5)
  if(numarg()==3){
    nq = $o1
    v1=new Vector()  v2=new Vector()
    nq.getcol($s2,v1)
    nq.getcol($s3,v2)
  } else {
    v1=$o1 v2=$o2
  }
  v1.vstats(v2,vo)
  x0 = v2.min
  y0 = x0*vo.x(0)+vo.x(1)
  x1 = v2.max
  y1 = x1*vo.x(0)+vo.x(1)
  vx=new Vector(2)
  vx.x(0)=x0
  vx.x(1)=x1
  vy=new Vector(2)
  vy.x(0)=y0
  vy.x(1)=y1
  gvtmp=gvmarkflag
  gvmarkflag=0
  gg(vy,vx)
  gvmarkflag=gvtmp
  str=new String()
  r=v1.pcorrel(v2)
  if(name_declared("rpval_stats")){
    sprint(str.s,"r = %.2f, p = %g, N = %d",r,rpval_stats(v1.size,r),v1.size)
    g.label(0,0,str.s)
  }
  return vo
}

// select from a vector handled as a matrix -- see matrix.mod
halfmat=0
obfunc mindsel () { local a,x,r,c localobj vm,vi,oq
  vm=$o1 
  a=allocvecs(vi)
  if (numarg()==4) vi.indvwhere(vm,$s2,$3,$4) else vi.indvwhere(vm,$s2,$3)
  oq=new NQS("row","col","val") 
  oq.clear(vi.size)
  for vtr(&x,vi) {
    r=int(x/COLS) c=x-r*COLS
    if (!halfmat || c>r) oq.append(r,c,vm.x[x])
  }
  dealloc(a)
  print oq.size(1)
  return oq
}

//* return row $2 of nqs $o1 
obfunc nqrow () { local row,col localobj vout,nq
  nq=$o1
  row=$2
  vout=new Vector(nq.m)
  for col=0,nq.m-1 vout.x(col)=nq.v[col].x(row)
  return vout
}

//* find row $o2 (vector) in $o1 (nqs) and return index
//  if not there return -1
func nqfindrow () { local idx,jdx,sz localobj nq,vf,vrow
  nq=$o1  vf=$o2
  sz=nq.size(-1)
  for idx=0,sz-1 {
    vrow = nqrow(nq,idx)
    if(vrow.eq(vf)) return idx
  }
  return -1
}

//* nquniq(NQS) -- return a new NQS with unique rows in $o1
obfunc nquniq () { local sz,idx,outrow,jdx localobj nqin,nqout,vrow
  nqin=$o1
  nqout=new NQS()
  for idx=0,nqin.m-1{
    nqout.resize(nqin.s[idx].s)
    nqout.v[nqout.m-1].resize(nqin.v[idx].size)
  }
  sz=nqin.size(-1)
  jdx=0
  outrow=0
  for idx=0,sz-1{
    vrow=nqrow(nqin,idx)
    if(nqfindrow(nqout,vrow)==-1){
      for jdx=0,nqin.m-1 nqout.v[jdx].x(outrow) = vrow.x(jdx)
      outrow += 1
    }
  }
  for idx=0,nqout.m-1 nqout.v[idx].resize(outrow)
  return nqout
}

Neymotin S, Uhlrich DJ, Manning KA, Lytton WW (2008) Data mining of time-domain features from neural extracellular field data Applic. of Comput. Intel. in Bioinf. and Biomed.: Current Trends and Open Problems 151:119-140

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