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

 Download zip file   Auto-launch 
Help downloading and running models
Accession:183014
We developed a 3-layer sensorimotor cortical network of consisting of 704 spiking model-neurons, including excitatory, fast-spiking and low-threshold spiking interneurons. Neurons were interconnected with AMPA/NMDA, and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a virtual musculoskeletal human arm, with realistic anatomical and biomechanical properties, to reach a target. Virtual arm position was used to simultaneously control a robot arm via a network interface.
References:
1 . 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 [PubMed]
2 . 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 10:28 [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 M1 L5B pyramidal pyramidal tract cell; Neocortex M1 L2/6 pyramidal intratelencephalic cell; Neocortex M1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neostriatum fast spiking 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; Python (web link to model);
Model Concept(s): Synaptic Plasticity; Learning; Reinforcement Learning; STDP; Reward-modulated STDP; Sensory processing; Motor control; Touch;
Implementer(s): Neymotin, Sam [samn at neurosim.downstate.edu]; Dura, Salvador [ salvadordura at gmail.com];
Search NeuronDB for information about:  Neocortex M1 L2/6 pyramidal intratelencephalic cell; Neocortex M1 L5B pyramidal pyramidal tract cell; Neocortex M1 interneuron basket PV cell; GabaA; AMPA; NMDA; Gaba; Glutamate;
/
arm2dms_modeldb
mod
msarm
stimdata
README.html
analyse_funcs.py
analysis.py
armGraphs.py
arminterface_pipe.py
basestdp.hoc
bicolormap.py
boxes.hoc *
bpf.h *
col.hoc
colors.hoc *
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
filtutils.hoc *
grvec.hoc
hinton.hoc *
hocinterface.py
infot.hoc *
init.hoc
intfsw.hoc *
labels.hoc
load.hoc
load.py
local.hoc *
main.hoc
main_demo.hoc
main_neurostim.hoc
misc.h *
misc.py *
msarm.hoc
network.hoc
neuroplot.py *
neurostim.hoc
nload.hoc
nqs.hoc *
nqsnet.hoc *
nrnoc.hoc
params.hoc
perturb.hoc
python.hoc
pywrap.hoc *
run.hoc
runbatch_neurostim.py
runsim_neurostim
samutils.hoc *
saveoutput.hoc
saveoutput2.hoc
setup.hoc *
sim.hoc
sim.py
sim_demo.py
simctrl.hoc *
stats.hoc *
stim.hoc
syncode.hoc *
units.hoc *
vector.py
xgetargs.hoc *
                            
// $Id: init.hoc,v 1.32 2012/02/14 21:50:34 samn Exp $

xwindows=1
show_panel=0
pwd()
load_file("xgetargs.hoc")
load_file("grvec.hoc")
load_file("syncode.hoc")
load_file("decnqs.hoc")
if (! VECST_INSTALLED) install_vecst()
if (! INSTALLED_stats) install_stats()
install_PLACE()
// install_clust()
install_updown()
transpose_clust=0
load_file("samutils.hoc")
load_file("intfsw.hoc")
load_file("drline.hoc")
load_file("stats.hoc")
load_file("infot.hoc")
load_file("decmat.hoc")
load_file("filtutils.hoc")
verbose_INTF6=verbose_infot=0
load_file("col.hoc")
load_file("pywrap.hoc")
load_file("hinton.hoc")
//load_file("geom.hoc") // has DPC template
load_file("units.hoc")
// load_file("spkts.hoc")



Loading data, please wait...