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

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Accession:150245
"... We developed a model of sensory and motor neocortex consisting of 704 spiking model-neurons. Sensory and motor populations included excitatory cells and two types of interneurons. Neurons were interconnected with AMPA/NMDA, and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a 2-joint virtual arm to reach to a fixed target. ... "
Reference:
1 . 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 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex U1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 interneuron basket PV cell; 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): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Synaptic Plasticity; Learning; Reinforcement Learning; STDP; Reward-modulated STDP; Sensory processing;
Implementer(s): Neymotin, Sam [samn at neurosim.downstate.edu]; Chadderdon, George [gchadder3 at gmail.com];
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex V1 interneuron basket PV cell; Neocortex U1 pyramidal intratelencephalic L2-5 cell; GabaA; AMPA; NMDA; Gaba; Glutamate;
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a2dmodeldb
readme.html
drspk.mod *
infot.mod *
intf6_.mod *
misc.mod *
nstim.mod *
stats.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
labels.hoc *
misc.h *
mosinit.hoc
network.hoc
nload.hoc
nqs.hoc *
nqsnet.hoc *
nrnoc.hoc *
params.hoc
python.hoc
pywrap.hoc *
run.hoc
samutils.hoc *
screenshot.png
sense.hoc *
setup.hoc *
simctrl.hoc *
stats.hoc *
stim.hoc
syncode.hoc *
trainedplast.nqs
units.hoc *
xgetargs.hoc *
                            
// $Id: xgetargs.hoc,v 1.20 2008/05/11 17:19:11 billl Exp $

print "Loading xgetargs.hoc..."

xgahfl=0
{load_file("decvec.hoc")}
strdef mesg
objref xgabxl,xgabxo

//* xgetargs()
// xgetargs(panel_name,command,arg1[,arg2,...],defaults) // existing or new params -- flag 2
//   may have no named params in this case since just set with call to command
//   eg xgetargs("New","redo","do this","do that","1,2")
// xgetargs(panel_name,command,"a1,a2,..") // existing params -- flag 1
// xgetargs(panel_name,command,strlist)
// xgetargs(1,...) // dismiss after setting
// xgetargs(list,...) // list of helper functions returned by xgetclrfunc()
// eg xgetargs("Random session","newrand","# of patts","patt size  ","overlap   ","5,33,7")
// optional 1st arg flag=1 means to remove panel after command is called
// Union contains: o[0]=VBox, o[1]=argv, [o[2]=param name list] o[3]=orig update
//                 o[4]=helper functions
//                 x[0]=#args, x[1]=flag, x[2]=dismiss x[3-5] reserved for future use
//                 s=panel/button name,t=quit call,u=varlable,v=scratch
obfunc xgetargs () { local i,j,args,flag,dismiss,na localobj o,argv,vb,l,st,xo
  if (!isassigned(xgabxl)) xgabxl=new List()
  st=new String2()
  na=numarg()  
  dismiss=0 i=1 
  xgabxl.append(o=new Union())
  if (argtype(i)==0) { dismiss=$1 i+=1 }
  if (argtype(i)==1) {xo=$oi i+=1} else xo=xgetclrfunc()
  o.os(4,"funcs",xo) // list of helper functions
  o.xs(2,"dismiss",dismiss) // dismiss=1 means dismiss at end
  o.os(1,"argv",argv=new Vector(na))
  argv.resize(0)
  o.os(0,"vb",vb=new VBox())
  sprint(o.t,"xgaqt(%s)",o)
  vb.dismiss_action(o.t)
  o.s=$si i+=1 o.t=$si i+=1
  vb.intercept(1)
  xpanel(o.s)
  xvarlabel(o.u)
  sprint(o.v,"xgetexec(%s)",o)
  xbutton(o.s,o.v)
  excu("xgetbuttn",o.o[4],o)
  if (i==na) { // this should be a list of existing params
    o.xs(1,"flag",flag=1) // flag -- variables have names
    o.os(2,"plist",l=new List()) // list of param names
    if (argtype(i)==2) {
      split_interp=1
      split($si,l) // list of strings
      split($si,argv) // list of values
    } else if (argtype(i)==1) {
      for ltr(xo,$oi) {
        l.append(xo)
        argv.append(str2num(xo.s))
      }
    } else { printf("xgetargs ERRA\n") xpanel() return o=nil}
    args=argv.size
    if (args==0) { // create them
      for ltr(xo,l) {
        sprint(st.s,"%s=1",xo.s) execute(st.s)
        args=l.count argv.resize(args) argv.fill(1)
      }
    } else if (args!=l.count) {printf("xgetargs ERRB %d %d\n",args,l.count) xpanel() return o=nil}
    o.os(3,"orig",argv.c)   // save original values
    o.xs(0,"nargs",args)
    excu("xgetlabl",o.o[4],o)
    for j=0,args-1 {
      sprint(o.v,"%s.x[%d]",argv,j)
      sprint(st.s,"xgetchg(%s,%d)",o,j)
      xvalue(l.o(j).t, o.v, 1, st.s, 1)
    }
  } else {
    j=i i=na
    if (strm($si,"^[a-z]")) { // a named variable; should all be name vars
      o.xs(1,"flag",flag=3) // flag -- variables have names and routine is called with args
      split_interp=1
      split($si,argv)
      o.os(2,"plist",l=new List()) // list of param names
      split($si,l) // list of strings
    } else {
      split_interp=0
      split($si,argv)
      o.xs(1,"flag",flag=2) // flag -- variables may have no names; are just args to a function
    }
    i=j // restore i
    o.xs(0,"nargs",args=argv.size)
    if (args!=na-i) { printf("xgetargs ERRC: mismatch %d %d\n",args,na-i) xpanel() return o=nil }
    o.os(3,"orig",argv.c)   // save original values
    for j=0,args-1 {
      sprint(o.v,"%s.x[%d]",argv,j)
      sprint(st.s,"xgetchg(%s,%d)",o,j)
      xvalue($si,o.v,1,st.s,1)
      if (flag==3) l.o(j).t=$si
      i+=1
    }
  }
  o.u=o.s // start with this label
  // xbutton("Help (2 clicks)","xgah()")
  xpanel()
  vb.intercept(0)
  vb.full_request(1)
  vb.map(o.s)
  xgabxo=o // global for current xgab object
  return o
}

//* xgah() should provide help -- doesn't
proc xgah () { 
  if (xgahfl==1) {
    continue_dialog("Press help button first, then elsewhere for button-specific help")
    xgahfl=0
  } else xgahfl=1
}

//* xgetclrfunc() -- set up the callbacks as empty functions
obfunc xgetclrfunc () { local flag localobj st,xo,o
  flag=0
  if (numarg()==1) if (isobj($o1,"List")) flag=1
  if (flag) { // just clear the functions
    for ltr(xo,$o1) xo.t="" // clear
    return $o1
  } else { // create
    st=new String() o=new List()
    for scase(st,"xgetchg2","xgetexec2","xgaqt2","xgetlabl","xgetbuttn") {
      o.append(new String2(st.s)) }
    if (numarg()==1) $o1=o
    return o
  }
}

//* xgetchg() done after a value is changed
proc xgetchg () { local i localobj o
  o=$o1 i=$2
print "A",o,i,o.o[4]
  if (excu("xgetchg2",o.o[4],o,i)) return
  sprint(o.u,"Press '%s' button for effect",o.s)
}

//* xgetexec() done when the 'make changes' button is pressed
proc xgetexec () { local i,args,dismiss,flag localobj o,l,av,vb,xo
  o=$o1
  if (excu("xgetexec2",o.o[4],o)) return
  args=o.x flag=o.x[1] dismiss=o.x[2] av=o.o[1] vb=o.o
  if (flag==1 || flag==3) {
    l=o.o[2]
    if (args!=l.count || args!=av.size) {
      printf("xgetexec() ERRA %d,%d,%d\n",args,l.count,av.size) return
    }
    for ltr(xo,l,&i) {
      sprint(o.v,"%s=%g",xo.s,av.x[i])
      execute(o.v)
    }
    if (flag==1) { // call the routine -- else will call below
      if (strm(o.t,"[(]")) o.v=o.t else sprint(o.v,"%s(%s)",o.t,o) // no args passed to function
    }
  }
  if (flag==2 || flag==3) {
    sprint(o.v,"%s(",o.t)
    for i=0,args-2 sprint(o.v,"%s%g,",o.v,av.x[i])
    sprint(o.v,"%s%g)",o.v,av.x[i]) 
  }
  execute(o.v)
  o.u="Changes submitted"
  if (dismiss) { xgaqt(o) // get rid of the box
  } else { o.o[3].copy(o.o[1]) } // new set of origs
}
  
//* xgaqt() called when the panel is dismissed
proc xgaqt () { local x localobj av,vb,o
  o=$o1 
  if (excu("xgaqt2",o.o[4],o)) return
  av=o.o[1] vb=o.o
  vb.unmap()
  if ((x=xgabxl.index(o))!=-1) xgabxl.remove(x)
  if (xgabxo==o) xgabxo=nil
}

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[PubMed]

References and models cited by this paper

References and models that cite this paper

Afshar A, Santhanam G, Yu BM, Ryu SI, Sahani M, Shenoy KV (2011) Single-trial neural correlates of arm movement preparation. Neuron 71:555-64

Almassy N, Edelman GM, Sporns O (1998) Behavioral constraints in the development of neuronal properties: a cortical model embedded in a real-world device. Cereb Cortex 8:346-61 [PubMed]

Bannister AP (2005) Inter- and intra-laminar connections of pyramidal cells in the neocortex. Neurosci Res 53:95-103 [PubMed]

Bedau MA (2005) Artificial life: more than just building and studying computational systems. Artif Life 11:1-3 [PubMed]

Berthier N (2011) The syntax of human infant reaching 8th International Conference on Complex Systems :1477-1487

Berthier NE, Clifton RK, McCall DD, Robin DJ (1999) Proximodistal structure of early reaching in human infants. Exp Brain Res 127:259-69

Carnevale NT, Hines ML (2006) The NEURON Book

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 [Journal]

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

Cools R (2006) Dopaminergic modulation of cognitive function-implications for L-DOPA treatment in Parkinson's disease. Neurosci Biobehav Rev 30:1-23 [PubMed]

Corbetta D, Snapp-Childs W (2009) Seeing and touching: the role of sensory-motor experience on the development of infant reaching. Infant Behav Dev 32:44-58

De Schutter E (2008) Why are computational neuroscience and systems biology so separate? PLoS Comput Biol 4:e1000078 [Journal] [PubMed]

Dyhrfjeld-Johnsen J, Santhakumar V, Morgan RJ, Huerta R, Tsimring L, Soltesz I (2007) Topological determinants of epileptogenesis in large-scale structural and functional models of the dentate gyrus derived from experimental data. J Neurophysiol 97:1566-87 [Journal] [PubMed]

   Dentate gyrus (Morgan et al. 2007, 2008, Santhakumar et al. 2005, Dyhrfjeld-Johnsen et al. 2007) [Model]

Edelman GM (1987) Neural Darwinism: The Theory of Neural Group Selection

Edelman GM (2004) Wider than the sky: The phenomenal gift of consciousness

Engel A, Konig P, Kreiter A, Gray C, Singer W (1991) Temporal coding by coherent oscillations as a potential solution to the binding problem: physiological evidence Nonlinear dynamics and neural networks, Schuster HG, ed.

Evans RC, Morera-Herreras T, Cui Y, Du K, Sheehan T, Kotaleski JH, Venance L, Blackwell KT (2012) The effects of NMDA subunit composition on calcium influx and spike timing-dependent plasticity in striatal medium spiny neurons. PLoS Comput Biol 8:e1002493 [Journal] [PubMed]

   NMDA subunit effects on Calcium and STDP (Evans et al. 2012) [Model]

Farries MA, Fairhall AL (2007) Reinforcement learning with modulated spike timing dependent synaptic plasticity. J Neurophysiol 98:3648-65 [PubMed]

Fenton AA, Lytton WW, Barry JM, Lenck-Santini PP, Zinyuk LE, Kubik S, Bures J, Poucet B, Mull (2010) Attention-like modulation of hippocampus place cell discharge. J Neurosci 30:4613-25

Florian RV (2007) Reinforcement learning through modulation of spike-timing-dependent synaptic plasticity. Neural Comput 19:1468-502 [PubMed]

Frank MJ, O'reilly RC (2006) A mechanistic account of striatal dopamine function in human cognition: psychopharmacological studies with cabergoline and haloperidol. Behav Neurosci 120:497-517 [PubMed]

Frank MJ, Seeberger LC, O`Reilly RC (2004) By carrot or by stick: cognitive reinforcement learning in parkinsonism. Science 306:1940-3 [Journal] [PubMed]

   Dynamic dopamine modulation in the basal ganglia: Learning in Parkinson (Frank et al 2004,2005) [Model]

Gourevitch B, Eggermont JJ (2007) Evaluating information transfer between auditory cortical neurons. J Neurophysiol 97:2533-43 [PubMed]

Graybiel AM, Aosaki T, Flaherty AW, Kimura M (1994) The basal ganglia and adaptive motor control. Science 265:1826-31 [PubMed]

Hikosaka O, Nakamura K, Sakai K, Nakahara H (2002) Central mechanisms of motor skill learning. Curr Opin Neurobiol 12:217-22

Hosp JA, Pekanovic A, Rioult-Pedotti MS, Luft AR (2011) Dopaminergic projections from midbrain to primary motor cortex mediate motor skill learning. J Neurosci 31:2481-7 [PubMed]

Houk JC, Wise SP (2004) Distributed modular architectures linking basal ganglia, cerebellum, and cerebral cortex: their role in planning and controlling action. Cereb Cortex 5:95-110 [PubMed]

Izhikevich EM (2007) Solving the Distal Reward Problem through Linkage of STDP and Dopamine Signaling. Cereb Cortex 17(10):2443-2452 [Journal] [PubMed]

   Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007) [Model]

Jones SR, Kerr CE, Wan Q, Pritchett DL, Hamalainen M, Moore CI (2010) Cued spatial attention drives functionally relevant modulation of the mu rhythm in primary somatosensory cortex. J Neurosci 30:13760-5 [PubMed]

Kelemen E, Fenton AA (2010) Dynamic grouping of hippocampal neural activity during cognitive control of two spatial frames. PLoS Biol 8:e1000403 [PubMed]

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 [Journal] [PubMed]

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

Kubikova L, Kostal L (2010) Dopaminergic system in birdsong learning and maintenance. J Chem Neuroanat 39:112-23

Le Novere N (2007) The long journey to a Systems Biology of neuronal function. BMC Syst Biol 1:28-23

Luft AR, Schwarz S (2009) Dopaminergic signals in primary motor cortex. Int J Dev Neurosci 27:415-21 [PubMed]

Lungarella M, Sporns O (2006) Mapping information flow in sensorimotor networks. PLoS Comput Biol 2:e144 [PubMed]

Lytton WW (2008) Computer modelling of epilepsy. Nat Rev Neurosci 9:626-37 [Journal] [PubMed]

Lytton WW, Neymotin SA, Hines ML (2008) The virtual slice setup. J Neurosci Methods 171:309-15 [Journal] [PubMed]

   The virtual slice setup (Lytton et al. 2008) [Model]

Lytton WW, Omurtag A (2007) Tonic-clonic transitions in computer simulation. J Clin Neurophysiol 24:175-81 [PubMed]

   Tonic-clonic transitions in a seizure simulation (Lytton and Omurtag 2007) [Model]

Lytton WW, Omurtag A, Neymotin SA, Hines ML (2008) Just in time connectivity for large spiking networks Neural Comput 20(11):2745-56 [Journal] [PubMed]

   JitCon: Just in time connectivity for large spiking networks (Lytton et al. 2008) [Model]

Lytton WW, Stewart M (2005) A rule-based firing model for neural networks Int J Bioelectromagn 7:47-50

Lytton WW, Stewart M (2006) Rule-based firing for network simulations. Neurocomputing 69:1160-1164

Mahmoudi B, Sanchez JC (2011) A symbiotic brain-machine interface through value-based decision making. PLoS One 6:e14760-23

Marsh B, Tarigoppula A, Francis J (2011) Correlates of reward expectation in the primary motor cortex: Developing an actor-critic model in macaques for a brain computer interface Society for Neuroscience Abstracts, 41

Mo J, Schroeder CE, Ding M (2011) Attentional modulation of alpha oscillations in macaque inferotemporal cortex. J Neurosci 31:878-82

Molina-Luna K, Pekanovic A, Rohrich S, Hertler B, Schubring-Giese M, Rioult-Pedotti MS, Luft (2009) Dopamine in motor cortex is necessary for skill learning and synaptic plasticity. PLoS One 4:e7082-21 [PubMed]

Neymotin S, Kerr C, Francis J, Lytton W (2011) Training oscillatory dynamics with spike-timing-dependent plasticity in a computer model of neocortex Signal Processing in Medicine and Biology Symposium (SPMB), IEEE :1-6

Neymotin SA, Jacobs KM, Fenton AA, Lytton WW (2011) Synaptic information transfer in computer models of neocortical columns. J Comput Neurosci. 30(1):69-84 [Journal] [PubMed]

   Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010) [Model]

Neymotin SA, Lazarewicz MT, Sherif M, Contreras D, Finkel LH, Lytton WW (2011) Ketamine disrupts theta modulation of gamma in a computer model of hippocampus Journal of Neuroscience 31(32):11733-11743 [Journal] [PubMed]

   Ketamine disrupts theta modulation of gamma in a computer model of hippocampus (Neymotin et al 2011) [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]

Pastalkova E, Serrano P, Pinkhasova D, Wallace E, Fenton AA, Sacktor TC (2006) Storage of spatial information by the maintenance mechanism of LTP. Science 313:1141-4 [PubMed]

Peterson BE, Healy MD, Nadkarni PM, Miller PL, Shepherd GM (1996) ModelDB: an environment for running and storing computational models and their results applied to neuroscience. J Am Med Inform Assoc 3:389-98 [Journal] [PubMed]

Potjans W, Morrison A, Diesmann M (2009) A spiking neural network model of an actor-critic learning agent. Neural Comput 21:301-39 [PubMed]

Qiu S, Anderson CT, Levitt P, Shepherd GM (2011) Circuit-specific intracortical hyperconnectivity in mice with deletion of the autism-associated Met receptor tyrosine kinase. J Neurosci 31:5855-64

Reid RC (2012) From functional architecture to functional connectomics. Neuron 75:209-17

Reynolds JN, Wickens JR (2005) Dopamine-dependent plasticity of corticostriatal synapses. Neural Netw 15:507-21 [PubMed]

Roberts PD, Bell CC (2002) Spike timing dependent synaptic plasticity in biological systems. Biol Cybern 87:392-403 [PubMed]

Rowan MS,Neymotin SA (2013) Synaptic Scaling Balances Learning in a Spiking Model of Neocortex Adaptive and Natural Computing Algorithms, Tomassini M, Antonioni A, Daolio F, Buesser P, ed. pp.20 [Journal]

   Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013) [Model]

Sanes JN (2003) Neocortical mechanisms in motor learning. Curr Opin Neurobiol 13:225-31

Seung HS (2003) Learning in spiking neural networks by reinforcement of stochastic synaptic transmission. Neuron 40:1063-73 [PubMed]

Shadmehr R, Krakauer JW (2008) A computational neuroanatomy for motor control. Exp Brain Res 185:359-81 [PubMed]

Shadmehr R, Wise S (2005) The computational neurobiology of reaching and pointing: a foundation for motor learning

Shen W, Flajolet M, Greengard P, Surmeier DJ (2008) Dichotomous dopaminergic control of striatal synaptic plasticity. Science 321:848-51 [PubMed]

Shepherd G (2004) The synaptic organization of the brain, Shepherd GM, ed.

Sober SJ, Brainard MS (2009) Adult birdsong is actively maintained by error correction. Nat Neurosci 12:927-31 [PubMed]

Song S, Miller KD, Abbott LF (2000) Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nat Neurosci 3:919-26 [PubMed]

Sporns O, Tononi G, Kotter R (2005) The human connectome: A structural description of the human brain. PLoS Comput Biol 1:e42-308

Thomson AM, Lamy C (2007) Functional maps of neocortical local circuitry. Front Neurosci 1:19-42 [PubMed]

Thomson AM, West DC, Wang Y, Bannister AP (2002) Synaptic connections and small circuits involving excitatory and inhibitory neurons in layers 2-5 of adult rat and cat neocortex: triple intracellular recordings and biocytin labelling in vitro. Cereb Cortex 12:936-53 [PubMed]

Thorndike E (1911) Animal intelligence

Tiesinga PH, Sejnowski TJ (2004) Rapid temporal modulation of synchrony by competition in cortical interneuron networks. Neural Comput 16:251-75 [PubMed]

Uhlhaas PJ, Singer W (2006) Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 52:155-68 [PubMed]

von der Malsburg C, Schneider W (1986) A neural cocktail-party processor. Biol Cybern 54:29-40 [PubMed]

von Kraus LM, Sacktor TC, Francis JT (2010) Erasing sensorimotor memories via PKMzeta inhibition. PLoS One 5:e11125-81

Von_hofsten C (1979) Development of visually directed reaching: The approach phase Department Of Psychology, University Of Uppsala [psykologiska Inst , Uppsala Univ ]

Webb B (2000) What does robotics offer animal behaviour? Anim Behav 60:545-558

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]

   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]

Eguchi A, Neymotin SA and Stringer SM (2014) Color opponent receptive fields self-organize in a biophysical model of visual cortex via spike-timing dependent plasticity 8:16. doi: Front. Neural Circuits 8:16 [Journal]

   Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014) [Model]

(79 refs)