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

 Download zip file   Auto-launch 
Help downloading and running models
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;
/
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: simctrl.hoc,v 1.14 2000/11/27 21:59:33 billl Exp $
// Graphic routines for neuremacs simulation control

proc sim_panel () {
  xpanel(simname)
        xvarlabel(output_file)
	xbutton("Init", "stdinit()")
	xbutton("Init & Run", "run()")
	xbutton("Stop", "stoprun=1")
	xbutton("Continue till Tstop", "continueRun(tstop)")
	xvalue("Continue till", "runStopAt", 1, "{continueRun(runStopAt) stoprun=1}", 1, 1)
	xvalue("Continue for", "runStopIn", 1, "{continueRun(t + runStopIn) stoprun=1}", 1,1)
	xbutton("Single Step", "steprun()")
	xvalue("Tstop", "tstop", 1, "tstop_changed()", 0, 1)
	graphmenu()
	sim_menu_bar()
	misc_menu_bar()
  xpanel()
}

proc misc_menu_bar() {
  xmenu("Miscellaneous")
    xbutton("Label Graphs", "labelgrs()")
    xbutton("Label With String", "labelwith()")
    xbutton("Label Panel", "labelpanel()")
	xbutton("Parameterized Function", "load_template(\"FunctionFitter\") makefitter()")
  xmenu()
}

proc sim_menu_bar() {
  xmenu("Simulation Control")
    xbutton("File Vers", "elisp(\"sim-current-files\")")
    xbutton("File Status...", "elisp(\"sim-rcs-status\")")
    xbutton("Sim Status", "elisp(\"sim-portrait\")")
    xbutton("Load Current Files", "elisp(\"sim-load-sim\")")
    xbutton("Load Templates", "elisp(\"sim-load-templates\")") 
    xbutton("Load File...", "elisp(\"sim-load-file\")") 
    xbutton("Save Sim...", "elisp(\"sim-save-sim\")")
    xbutton("Set File Vers...", "elisp(\"sim-set-file-ver\")")
    xbutton("Read Current Vers From Index", "elisp(\"sim-read-index-file\")")
    xbutton("Read Last Saved Vers", "elisp(\"sim-read-recent-versions\")")
    xbutton("Output to sim buffer", "elisp(\"sim-direct-output\")")
  xmenu()
}

proc labelpanel() {
  xpanel(simname,1)
	xvarlabel(output_file)
  xpanel()
}

proc labels () {
  labelwith($s1)
  labelgrs()
}

proc labelgrs () { local i, j, cnt
  for j=0,n_graph_lists-1 {
    cnt = graphList[j].count() - 1
    for i=0,cnt labelgr(graphList[j].object(i))
  }
}

proc labelwith () { local i, j, cnt
  temp_string_ = user_string_  // save the old one
  if (numarg() == 1) { /* interactive mode */  
    user_string_ = $s1
  } else {
    string_dialog("write what?", user_string_)
  }
  for j=0,n_graph_lists-1 {
    cnt = graphList[j].count() - 1
    for i=0,cnt {
      graphList[j].object(i).color(0)
      graphList[j].object(i).label(0.5,0.9,temp_string_)
      graphList[j].object(i).color(1)
      graphList[j].object(i).label(0.5,0.9,user_string_)
    }
  }
}

proc labelgr () { local i
  $o1.color(0)  // white overwrite
  for (i=0;i<10;i=i+1) { // erase every possible runnum for this date
    sprint(temp_string_,"%s %d%d",datestr,i,i)
    $o1.label(0.1,0.7,temp_string_) }
  $o1.color(1) // back to basic black
  sprint(temp_string_,"%s %02d",datestr,runnum)
  $o1.label(0.1,0.7,temp_string_)
}


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)