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: nrnoc.hoc,v 1.74 2007/11/20 07:51:52 billl Exp $

print "Loading nrnoc.hoc..."

proc nrnoc () {}

// Users should not edit nrnoc.hoc or default.hoc.  Any local 
// changes to these files should be made in local.hoc.

// key '*&*' is picked up by to indicate command for emacs
proc elisp () { printf("*&* %s\n",$s1) }
// if (not exists(simname)) { strdef simname, output_file, datestr, comment }

// Simctrl.hoc will automatically load stdgraph.hoc which automatically
// loads stdrun.hoc
strdef temp_string_, user_string_  // needed for simctrl
/* Global variable default values.  NOTE that stdrun.hoc, stdgraph.hoc
and simctrl.hoc all contain variable definitions and thus default.hoc
should be loaded after these files */
{load_file("default.hoc")}      /* Load default.hoc */

/* Allows arrays of strings */
objref hoc_obj_[2]
{load_file("stdgui.hoc")} // don't want to encounter other String tempate defs
{load_file("simctrl.hoc")}

proc run () {
  running_ = 1
  stdinit()
  continueRun(tstop)
  finish()
}

proc continueRun () { local rt, rtstart, ts
  if (numarg()==1) ts=$1 else ts=t+1e3
  realtime = 0  rt = screen_update_invl  rtstart = startsw()
  eventcount=0
  eventslow=1
  stoprun = 0
  if (using_cvode_) {
    if (cvode.use_local_dt || (cvode.current_method()%10) == 0) {
      cvode.solve(ts)
      flushPlot()
      realtime = startsw() - rtstart
      return
    }
  } else {
    ts -= dt/2
  }
  while (t<ts && stoprun==0) {
    step()
    realtime = startsw() - rtstart
    if (realtime >= rt) {
      //                        if (!stdrun_quiet) fastflushPlot()
      screen_update()
      //really compute for at least screen_update_invl
      realtime = startsw() - rtstart
      rt = realtime + screen_update_invl
    }
  }
  if (using_cvode_ && stoprun == 0) { // handle the "tstop" event
    step() // so all recordings take place at tstop
  }
  flushPlot()
  realtime = startsw() - rtstart
}

proc stdinit() {
        cvode_simgraph()
        realtime = 0
        setdt()
        init()
        initPlot()
}

proc init () {
  cvode_simgraph()
  initMech()
  initMisc1()

  // Initialize state vars then calculate currents
  // If user hand-set v in initMisc1() then v_init should be > 1000,
  // else all compartments will be set to v_init
  if (v_init < 1000) {
    finitialize(v_init)
  } else {
    finitialize()
  }

  // Set ca pump and leak channel for steady state
  setMemb()

  initMisc2()
  if (cvode_active()) cvode.re_init() else fcurrent()
  frecord_init()
}

// Initialization of mechanism variables
// NOTE: if any changes are made to the NEURON block of any local mod
// file, the user must add the necessary inits to initMisc1()
proc initMech () { 
  forall {
    if ((!ismembrane("pas")) && (!ismembrane("Passive"))) { 
      // Allow for either pas or Passive mod file usage
      // errorMsg("passive not inserted") 
    }

    if (ismembrane("na_ion")) { 
      nai = na_init
      nai0_na_ion = na_init
    }
    
    if (ismembrane("k_ion")) {
      ki = k_init
      ki0_k_ion = k_init
    }
    
    if (ismembrane("ca_ion")) { 
      cai = ca_init
      cai0_ca_ion = ca_init
    }
  }
}

//* setMemb complex -- multiple names for passive mech
//** declarations
iterator scase() { local i
  for i = 1, numarg() { temp_string_ = $si iterator_statement }}
objref paslist,pasvars[3],XO
double pasvals[2],x[1]
paslist = new List()
for ii=0,2 pasvars[ii]= new String()
for scase("fastpas","pas","Pass","Passive") paslist.append(new String(temp_string_))

//** getval(),setval() -- return/set the hoc value of a string
func retval () { return getval($s1) }
func getval () { 
  sprint(temp_string2_,"x=%s",$s1)
  execute(temp_string2_)
  return x
}
proc setval () { 
  sprint(temp_string2_,"%s=%g",$s1,$2)
  execute(temp_string2_)
}

//** findpas()
// assumes that we are starting in a live section since looks for pass mech there
qx_=0
proc findpas () {
  for ii=0,paslist.count-1 {
    XO=paslist.object(ii)
    if (ismembrane(XO.s)) {
      // print XO.s,"found"
      pasvars[2].s=XO.s
      sprint(pasvars[0].s,"g_%s(qx_)",XO.s)
      for scase("e","erev","XXXX") {  // look for the proper prefix
        sprint(temp_string_,"%s_%s",temp_string_,XO.s)
        if (name_declared(temp_string_)==1) break
      }
      if (name_declared(temp_string_)==0) { // not found
        printf("SetMemb() in nrnoc.hoc: Can't find proper 'erev' prefix for %s\n",XO.s)
      } else {
        sprint(pasvars[1].s,"%s(qx_)",temp_string_)
      }
    }
  }
}

proc setMemb () {
  if (!secp()) return
  findpas() // assume that passive name is the same in all sections
  forall for (qx_,0) {  // will eventually want 'for (x)' to handle all the segments
    if (ismembrane(pasvars[2].s)) {
        for ii=0,1 pasvals[ii]=getval(pasvars[ii].s)
        setmemb2()
        for ii=0,1 setval(pasvars[ii].s,pasvals[ii])
    }
  }
}

// secp() determine whether any sections exist
func secp () { local n
  n=0
  forall n+=1
  if (n>0) return 1 else return 0
}

func setother () {return 0} // callback stub
proc setmemb2 () { local iSum, ii, epas, gpas
  if (!secp()) return
  gpas=pasvals[0] epas=pasvals[1]
  // Setup steady state voltage using leak channel
  iSum = 0.0
  if (ismembrane("na_ion")) { iSum += ina(qx_) }
  if (ismembrane("k_ion"))  { iSum += ik(qx_)  }
  if (ismembrane("ca_ion")) { iSum += ica(qx_) }
  iSum += setother()

  if (iSum == 0) {        // Passive cmp so set e_pas = v
    epas = v
  } else {
    if (gpas > 0) {    // Assume g set by user, calc e
      epas = v + iSum/gpas

    } else {            // Assume e set by user, calc g
      if (epas != v) {
        gpas = iSum/(epas - v)
      } else { gpas=0 }
    }
    if (gpas < 0) errorMsg("bad g", gpas)
    if (epas < -100 || epas > 0) {
      printf(".")
      // printf("%s erev: %g %g %g\n",secname(),e_pas,ina,ik)
    }
  }
  pasvals[0]=gpas pasvals[1]=epas
}

proc finish () {
  /* Called following completion of continueRun() */

finishMisc()

if (graph_flag == 1) {
  if (iv_flag == 1) {
    flushPlot()
    doEvents()
  } else {
    graphmode(-1)
    plt(-1)
  }
}

if (print_flag == 1) {
  wopen("")
}
}

/*------------------------------------------------------------
User definable GRAPHICS and PRINTING routines
------------------------------------------------------------*/

proc outputData() {
  // Default procedure - if outputData() doesn't exist in the run file

  if (graph_flag == 1) {
    if (iv_flag == 1) {
      Plot()
      rt = stopsw()
      if (rt > realtime) {
        realtime = rt
        fastflushPlot()
        doNotify()
        if (realtime == 2 && eventcount > 50) {
          eventslow = int(eventcount/50) + 1
        }
        eventcount = 0
      }else{
        eventcount = eventcount + 1
        if ((eventcount%eventslow) == 0) {
          doEvents()
        }
      }

    } else {
      graph(t)
    }
  }

  if (print_flag == 1) { 
    if (t%printStep <= printStep) { printOut() }
  }
}

proc printOut() {
  /* Default procedure - if printOut() doesn't exist in the run file */
}

proc initGraph() {
  /* Default procedure - if initGraph() doesn't exist in the run file */

graph()
}

proc initPrint() {
  /* Default procedure - if initPrint() doesn't exist in the run file */

wopen(output_file)
}

/*------------------------------------------------------------
User definable BATCH RUN routines
------------------------------------------------------------*/

proc nextrun() {
  // Called from finishmisc() following completion of batch in an autorun
  wopen("")   
  runnum = runnum + 1
  sprint(output_file,"data/b%s.%02d", datestr, runnum)
}                       

// commands for emacs
proc update_runnum() { 
  runnum = $1
  sprint(output_file,"data/%s.%02d", datestr, runnum)
  print "^&^ (progn (sim-index-revert)(setq sim-runnum ",runnum,"))" }
proc nrn_write_index() { printf("&INDEX& %s\n",$s1) }
proc nrn_update () { elisp("nrn-update") }
proc nrn_message () { printf("!&! %s\n",$s1) } 

/*------------------------------------------------------------
User definable INITIALIZATION and FINISH routines
------------------------------------------------------------*/

// Default procedure - if initMisc1() doesn't exist in the run file 
// Initializations performed prior to finitialize() 
// This should contain point process inits and inits for any changes 
//        made to the NEURON block of any local mod file 
proc initMisc1() { }

// Default procedure - if initMisc2() doesn't exist in the run file 
// Initializations performed after finitialize() 
proc initMisc2() { }

// Default procedure - if finishMisc() doesn't exist in the run file 
proc finishMisc() { }

/*------------------------------------------------------------
Miscellaneous routines
------------------------------------------------------------*/

proc errorMsg() {
  /* Print warning, assumes arg1 is string and arg2 if present is a
  variable value */

sectionname(section)

if (numarg() == 0) {
  printf("ERROR in errorMsg(): Needs at least 1 argument.\n")
} else if (numarg() == 1) {
  printf("ERROR: %s in section %s.\n", $s1, section)
} else {
  printf("ERROR: %s in section %s (var=%g).\n", $s1, section, $2)
}
}

proc clear() {
  /* Clear non-interviews plot window */
plt(-3)
}

func mod() { local x, y
  /* Mod function for non-integers */

x=$1
y=$2

return (x/y - int(x/y))
}

proc whatSection() { print secname() }

proc print_pp_location() { local x //arg1 must be a point process
   x = $o1.get_loc()
   sectionname(temp_string_)
   printf("%s located at %s(%g)\n", $o1, temp_string_, x)
   pop_section()
}

//* set method with method()
proc method () { local prc
  if (numarg()==0) {
    if (cvode_active() && cvode_local()) { printf("\tlocal atol=%g\n",cvode.atol)
    } else if (cvode_active()) { printf("\tglobal atol=%g\n",cvode.atol)
    } else if (secondorder==2) { printf("\tCrank-Nicholson dt=%g\n",dt)
    } else if (secondorder==0) { printf("\timplicit dt=%g\n",dt)
    } else { printf("\tMethod unrecognized\n") }
    return
  }
  if (numarg()==2) prc = $2 else prc=0
  finitialize()
  if (strcmp($s1,"global")==0) {
    cvode_active(1)
    cvode.condition_order(2)
    if (prc) cvode.atol(prc)
  } else if (strcmp($s1,"local")==0) {
    cvode_local(1)
    cvode.condition_order(2)
    if (prc) cvode.atol(prc)
  } else if (strcmp($s1,"implicit")==0) {
    secondorder=0
    cvode_active(1)
    cvode_active(0)
    if (prc) dt=prc
  } else if (strcmp($s1,"CN")==0) {
    secondorder=2
    cvode_active(1) // this turns off local
    cvode_active(0)
    if (prc) dt=prc
  } else {
    printf("Integration method %s not recognized\n",$s1)
  }
}

//* Load local modifications to nrnoc.hoc and default.hoc
{load_file("local.hoc")}

// if (xwindows && graph_flag) { nrnmainmenu() } // @@@ CK: removed popup

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]

References and models cited by this paper

References and models that cite this paper

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

Dura-Bernal S, Li K, Neymotin SA, Francis JT, Principe JC, Lytton WW (2016) Restoring behavior via inverse neurocontroller in a lesioned cortical spiking model driving a virtual arm. Front. Neurosci. Neuroprosthetics 10:28 [Journal]

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

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]

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

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

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

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

(38 refs)