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: run.hoc,v 1.53 2010/09/19 19:29:07 samn Exp $

print "Loading run.hoc..."

objref wf1,wf2,wrec
{sprint(tstr,"o[%d]",numcols)}
{declare("vit",tstr,"nqLFP",tstr)}

{method("global")}
{cvode.atol(1e-3)}
{cvode.condition_order(1)} // irrelevant to acells?
{declare("sepflds",1)} // whether to record separate fields for each layer @@@ CK: Yes, please do!

proc b () { time() a() }
{load_file("spkts.hoc")}
objref snq,fnq,anq,cvnq

//** draw lines between cell subpopulations
proc rasterlines () { localobj o
  g=graphItem
  for ct=0,CTYPi-1 if(col.numc[ct]) {
    drline(0,col.ixe[ct],mytstop,col.ixe[ct],g,2,6)
    // o=mdl2view(g,0,ix[ii]+numc[ii]/10)
    o=mdl2view(g,0.9,col.ix[ct]+col.numc[ct]/4)
    g.label(0.9,o.x[3],CTYP.o(ct).s)
  }
  g.flush
}
//** calls rasterlines, making sure g is set first
proc grlines () { 
  {g=Graph[$1] rasterlines()}
}

proc a () { local sh,sv
  if(g==nil)gg()
  if (!isobj(aa,"Graph")) aa=g else g=aa
  if (aa.view_count==0) aa=g
  sv=gnum gnum=ojtnum(g)
  graphItem=g
  sh=0 grv_.super=1 g.erase_all
  grv_.gveraseflag=0  grv_.gvmarkflag=grv_.super=1 // gnum=0
  gv(0,1+sh,2) // gv(1,3+sh,2) gv(2,2+sh,2)
  grv_.gvmarkflag=grv_.super=0
  gnum=sv
  rasterlines()
}


//** init - called @ start of run
proc init () { 
  initMisc1()
  vseed_stats(392426)
  finitialize() 
  cvode.re_init()
}

//** initrr - for doing a rerun - not used right now
proc initrr () { 
  col.intf.global_init()
  NStim[0].global_init()
  vseed_stats(392426)
}

//** setMemb - nothing here
proc setMemb () {}

//** initMisc1 -- @@@ CK: replaced with version Sam sent me on 2011feb11
proc initMisc1 () {
  col.intf.global_init()
  jrtm_INTF6=500
  for i=0,numcols-1 col[i].cstim.initrands()
}

objref ww // global ww for post processing
{wwht_INTF6=1 wwwid_INTF6=100}
//** wrecon - setup LFP recording, one LFP for each COLUMN
proc wrecon () { local cdx,ii,x,ct,cnt localobj tl,vm
  tl=new List()
  for cdx=0,numcols-1 {
    {nqsdel(nqLFP[cdx])}
    if(sepflds) nqLFP[cdx]=new NQS("E2","E4","E5","E6","LFP") else {nqLFP[cdx]=new NQS(1) nqLFP[cdx].s[0].s="LFP"}
    {nqLFP[cdx].v.resize(tstop/vdt_INTF6) nqLFP[cdx].pad()}
    for ii=0,nqLFP[cdx].m-1 tl.append(nqLFP[cdx].v[ii])
  }
  {vm=new Vector(CTYPi) vm.x(E2)=0 vm.x(E4)=1 vm.x(E5R)=vm.x(E5B)=2 vm.x(E6)=3}
  col.intf.initwrec(tl)
  for x=0,numcols-1 {
    for case(&ct,E2,E4,E5R,E5B,E6) {
      for ii=col[x].ix[ct],col[x].ixe[ct] {
        if(sepflds) {
          col[x].ce.o(ii).wrc(vm.x(ct)+x*5)
          col[x].ce.o(ii).wrc(4+x*5)
        } else col[x].ce.o(ii).wrc(x)
      }
    }
  }
}

//** wrecoff - turn off LFP recording
proc wrecoff () { local ct
  for ctt(&ct) for ixt(ct) XO.wrec(0)
}

//** finishMisc - called @ end of run()
func finishMisc () { local ii localobj co
  for ltr(XO,printlist) if (isassigned(XO.o)) if (XO.o.fflag) XO.o.fini
  // if(0) panobj.pvplist(ofile,params,100) //dont save printlist for now
  col.intf.global_fini
  for ltr(co,lcol) co.intf.spkstats2(1)
  print "TMAX: ",tmax_INTF6
  return 1
}

//** snapsv() save after printlist items min-max to fixed dt
proc snapsv () { local a,vdt,min,max localobj v1,o
  grv_.bst(3,3)
  vdt=0.2 
  a=allocvecs(v1)
  v1.resize(tstop/vdt)
  for ltr(o,printlist) { 
    if (o.code!=3) continue
    v1.snap(o.vec,o.tvec,vdt)
    o.vec.copy(v1)
    o.pstep=vdt
    o.tvflag=0
  }
  if (numarg()==0) grv_.pvall()
  dealloc(a)
}

proc exeruncall () { for ltr(XO,printlist) if (XO.code==3) XO.tvflag=1 }
proc pvout2 () { snapsv(1) }

//printlist=new List()
if(printlist==nil)printlist=new List()
objref p
p=printlist
proc prlclr () { localobj ce,col,intf
  for ltr(XO,printlist) {
    if (isassigned(XO.o)) if (XO.o.fflag) XO.o.recclr
  }
  //  for ltr(XO,ce) XO.wrc(-1)
  for ltr(col,lcol) {
    {ce=col.ce intf=ce.o(0)}
    for ii=0,ce.count-1 ce.o(ii).wrc(-1)
    intf.wwfree(0)
  }
  printlist.remove_all
}

//** prl(recv,recs[,lvextra]) - setup recording in printlist
//$1  = whether to record any cell voltages, default off
//$2  = whether to record spike times, default on
//$o3 = extra cells to record. lv.o(0)=cell,lv.o(1)=param to record,etc.,optional
proc prl () { local a,x,cidx,ii,jj,offst,y,recv,recs,max localobj xo,lvextra,co,ce
  if(numarg()>0) recv=$1 else recv=0
  if(numarg()>1) recs=$2 else recs=1
  if(numarg()>2) lvextra=$o3 else lvextra=nil
  {offst=0 prlclr()}
  for ltr(co,lcol,&ii) {
    {ce=co.ce intf=co.intf}
    if (recs) { sprint(tstr,"%s_SPKS",co.name)
      if (intf.flag("jcn")) { // for use with jitcon()
        printlist.append((vit[ii]=new vitem(tstr,2e6,1)))
        intf.jitrec(vit[ii].vec,vit[ii].tvec)
      } else {
        intf.jitrec() // clear jit recording
        for ltr(xo,ce,&y) {
          if (y==0) vit[ii]=new_printlist_nc(xo, xo.id, tstr) else {
            new_printlist_nc2(vit[ii], xo, xo.id)        }
        }
      }
    }
    npacsz=20
    if (recv && ce.count>0) for x=0,CTYPi-1 {
      if (co.numc[x]>2) max=2 else max=co.numc[x]-1
      for jj=0,max {
        XO=ce.object(co.ix[x]+jj)
        XO.recclr
        new_printlist_ac(XO,"V",  CTYP.o(x).s,XO.id)
        // new_printlist_ac(XO,"VGB",  CTYP.o(x).s,XO.id)
        // new_printlist_ac(XO,"VGA",  CTYP.o(x).s,XO.id)
        // new_printlist_ac(XO,"AHP",  CTYP.o(x).s,XO.id)
        //      printlist.o(printlist.count-1).code=3 // use code 3 for snapping
        // XO=ce.object(ixe[x]-jj-1)
        // XO.recclr
        // new_printlist_ac(XO,"V",  CTYP.object(x).s,XO.id)
      }
    }
    if(lvextra!=nil){
      for(jj=0;jj<lvextra.count;jj+=2){ XO=lvextra.o(jj)
        new_printlist_ac(XO,lvextra.o(jj+1).s,CTYP.object(ctyp(XO.id)).s,XO.id)
      }
    }
  }
  wrecon()
}

obfunc md5 () { localobj aq
  batch_flag=1
  if (numarg()>0) tstr=$s1 else tstr="aa"
  aq=new NQS("t","i")   aq.scpflag=1 aq.setcols(p.o(0).tvec,p.o(0).vec)
  aq.sort("i") aq.sort("t") aq.listvecs()
  prveclist(tstr,aq.vl)
  sprint(tstr,"md5sum %s",tstr) system(tstr)
  batch_flag=0
  return aq
}

//** rub() -- multi-run with saving to veclist
// saves vspks(1), SM(2), SU(2), IN(2)
proc rub () { local ii localobj so
  so=new String()
  clrveclist()
  for ii=0,9 {
    sprint(so.s,"%d",ii)
    shuffle(vspks)
    savevec(vspks)
    time()
    savevec(p.object(0).vec,p.object(0).tvec)
    savevec(p.object(1).vec,p.object(1).tvec)
    savevec(p.object(2).vec,p.object(2).tvec)
  }
}

//** spri(#) puts up graph of just one class
// 0->SM 1->SU 2->IN
// map 0,1,2 onto 1,3,5 ii*2+1
proc spri () { local ii,a,jj
  a=allocvecs(1)  ge(0)
  for ii=0,9 { jj=7*ii+$1*2+1
    mso[a].copy(veclist.object(jj))
    mso[a].add(1.5*ii*(mso[a].max-mso[a].min)-mso[a].min)
    mso[a].mark(g,veclist.object(jj+1),"O",4,cg(ii))
  }
}
//** sprj(#) puts up SM,SU,IN for 1 run (cp a() above)
proc sprj () { local ii,jj
  jj=7*$1+1
  for ii=0,2 veclist.object(jj+ii*2).mark(g,veclist.object(jj+ii*2+1),"O",2,cg(ii))
}
 
flddur=celdur=1000
splshhsz=0.4
objref slicepictypes
slicepictypes=new Vector()
{slicepictypes.append(0,3,2)}
stopoq_INTF6=1

proc rer () { 
  intf.resetall
  prl()
  shock()
  srun()
}

proc turnoff () { local cel0,cel1,off
  cel0=$1 cel1=$2
  if (argtype(3)==0) off=$3 else off=0
  ind.indgen(ix[cel0],ixe[cel0],1) vec.indgen(ix[cel1],ixe[cel1],1) 
  intf.turnoff(ind,vec,off)
}

//** turn off intralaminar connections
proc intralamoff () { local ct
  for ctt(&ct) if(numc[ct] && div[ct][ct][0]) turnoff(ct,ct)
}

//** turn on intralaminar connections
proc intralamon () { local ct
  for ctt(&ct) if(numc[ct] && div[ct][ct][0]) turnoff(ct,ct,1)
}

//get CVPNQS
proc getcvnq () {
  if(cvnq!=nil)nqsdel(cvnq)
  if(numarg()==0) cvnq=CVPNQS(snq,1,1,0)
  if(numarg()==1) cvnq=CVPNQS(snq,$1,1,0)
  if(numarg()==2) cvnq=CVPNQS(snq,$1,$2,0)
  if(numarg()==3) cvnq=CVPNQS(snq,$1,$2,$3)
}
//get PActNQS
proc getanq () {
  if(anq!=nil)nqsdel(anq)
  if(numarg()==0) {
    anq=PActNQS(snq)
  } else if(numarg()==1) {
    anq=PActNQS(snq,$1) 
  } else if(numarg()==2) {
    anq=PActNQS(snq,$1,$2) 
  }
}
//get SpikeNQS
proc getsnq () {
  if(snq!=nil)nqsdel(snq)
  snq=SpikeNQS(printlist.o(0),0)
}
//get SpikeNQS,FreqNQS
proc getsfnq () {
  getsnq()
  if(fnq!=nil)nqsdel(fnq)
  fnq=FreqNQS(snq,20,1,0)
}
//display & print average vals of snq,fnq
proc dispfnq () { local ct
  fnq.verbose=0
  for ctt(&ct) {
    fnq.select("Type",ct,"StartT","<=",tmax_INTF6)
    printf("%s mean F = %g Hz\n",CTYP.o(ct).s,fnq.getcol("Freq").mean)
    fnq.gr("Freq","EndT",0,clr,1)
    clr+=1
  }
}
//draw a black box showing stim duration
proc dispsgrdur () {
  if(g==nil)gg()
  drline(0,0,0,$1,g,1,4)
  drline(sgrdur,0,sgrdur,$1,g,1,4)
  drline(0,$1,sgrdur,$1,g,1,4)
  drline(0,0,sgrdur,0,g,1,4)
}
//draw $2 cell type in $3 color from PActNQS $o1
proc dispPActNQ () { local ct,color localobj anq,str  
  anq=$o1 ct=$2 color=$3 str=new String() str.s="act"
  if(numarg()>3)str.s=$s4
  anq.select("ct",ct)
  gvmarkflag=0
  anq.gr(str.s,"ts",0,color,9)
  gvmarkflag=1
  anq.gr(str.s,"ts",0,color,10)
  gvmarkflag=0
}
//get nqs with prumat info
obfunc getprnq () { local prty,poty localobj prnq
  prnq=new NQS("prty","poty","pr")
  for ctt(&prty) for ctt(&poty) if(prumat[prty][poty]!=0) prnq.append(prty,poty,prumat[prty][poty])
  return prnq
}
//get nqs with sprmat info
obfunc getsprnq () { local prty,poty localobj sprnq
  sprnq=new NQS("prty","poty","spr")
  for ctt(&prty) for ctt(&poty) if(sprmat[prty][poty]!=0) sprnq.append(prty,poty,sprmat[prty][poty])
  return sprnq
}

//rerun sim from nqs -- use :
// objref nqn
//nqn=new NQS("/u/samn/vcortex/data/08nov7_dodviptbatch_NORMUNIFNEGEXPDVFIXED_S0_399_eg2p15_update.nqs")
//rernqs(nqn,rowid)
proc rernqs () { local s,tm,ix,w localobj iq,wmnq
  iq=$o1 ix=$2 // ix will be row num in the NQS
  w=iq.fi("wght")
  s=iq.get("s",ix).x setdviPT=iq.get("setdviPT",ix).x tm=iq.get("tmax",ix).x 
  EGain=iq.get("EGain",ix).x IGain=iq.get("IGain",ix).x sgrdur=iq.get("sgrdur",ix).x
  if(iq.fi("vsgrpp")!=-1)vsgrpp=iq.get("vsgrpp",ix).o
  if(iq.fi("vsgrsidx")!=-1)vsgrsidx=iq.get("vsgrsidx",ix).o
  if(iq.fi("wght")!=-1){
    wmnq=iq.get("wght",ix).o setwt(wmnq)
  } else {
    setwt()
  }
  setdvi(s)
  stim()
  print "\nSim should run out to tmax=",tm
  time()
}

//* function calls
prl(1,1)

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]

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Dura-Bernal S, Neymotin SA, Kerr CC, Sivagnanam S, Majumdar A, Francis JT, Lytton WW (2017) Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis. IBM Journal of Research and Development (Computational Neuroscience special issue) 61(2/3):6:1-6:14 [Journal]

   Motor system model with reinforcement learning drives virtual arm (Dura-Bernal et al 2017) [Model]

Dura-Bernal S, Zhou X, Neymotin SA, Przekwas A, Francis JT, Lytton WW (2015) Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm. Front Neurorobot 9:13 [Journal] [PubMed]

   Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015) [Model]

Kerr CC, Van Albada SJ, Neymotin SA, Chadderdon GL, Robinson PA, Lytton WW (2013) Cortical information flow in Parkinson's disease: a composite network-field model. Front Comput Neurosci 7:39:1-14 [Journal] [PubMed]

   Composite spiking network/neural field model of Parkinsons (Kerr et al 2013) [Model]

Neymotin SA, Chadderdon GL, Kerr CC, Francis JT, Lytton WW (2013) Reinforcement learning of 2-joint virtual arm reaching in a computer model of sensorimotor cortex Neural Computation 25(12):3263-93 [Journal] [PubMed]

   Sensorimotor cortex reinforcement learning of 2-joint virtual arm reaching (Neymotin et al. 2013) [Model]

Neymotin SA, Dura-Bernal S, Lakatos P, Sanger TD, Lytton WW (2016) Multitarget Multiscale Simulation for Pharmacological Treatment of Dystonia in Motor Cortex. Front Pharmacol 7:157 [Journal] [PubMed]

   Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016) [Model]

Neymotin SA, Lee H, Park E, Fenton AA, Lytton WW (2011) Emergence of physiological oscillation frequencies in a computer model of neocortex. Front Comput Neurosci 5:19-75 [Journal] [PubMed]

   Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011) [Model]

Rowan MS, Neymotin SA, Lytton WW (2014) Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Front Comput Neurosci 8:39 [Journal] [PubMed]

   Electrostimulation to reduce synaptic scaling driven progression of Alzheimers (Rowan et al. 2014) [Model]

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