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: setup.hoc,v 1.25 2006/12/26 22:34:47 billl Exp $
// variables normally controlled by SIMCTRL


// load_file("setup.hoc")
load_file("stdgui.hoc")
show_panel=0
strdef simname, filename, output_file, datestr, uname, comment, section, osname
objref tmpfile,nil,graphItem,sfunc
sfunc = hoc_sf_  // from stdlib.hoc
proc chop () { sfunc.left($s1,sfunc.len($s1)-1) }

tmpfile = new File()
simname = "sim"      // helpful if running multiple simulations simultaneously
runnum = 1           // updated at end of run
system("uname -m",uname)  // keep track of type of machine for byte compatibility
chop(uname)
system("date +%y%b%d",datestr)
chop(datestr) // may prefer to downcase later
sprint(output_file,"data/%s.%02d",datestr,runnum)  // assumes a subdir called data
if (unix_mac_pc()==1) osname = "Linux" else if (unix_mac_pc()==2) { 
  osname = "Mac" } else if (unix_mac_pc()==3) osname = "PC"
printStep = 0.25 // time interval for saving to vector
graph_flag=0
batch_flag=1
xwindows = 0     // can still save but not look without xwindows

// load_file("nrnoc.hoc")

Loading data, please wait...