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 layer 5-6 pyramidal cell; Neocortex layer 2-3 pyramidal cell; Neocortex interneuron basket 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 layer 5-6 pyramidal cell; Neocortex layer 2-3 pyramidal cell; Neocortex interneuron basket 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 *
                            
This code generates the key results figures shown in

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.


This document provides brief installation and usage instructions.

INSTALLATION

Note: the code has been designed to work on Linux machines. It may work
on Macs and will definitely not work on Windows. If this is a problem,
please contact Cliff Kerr (cliffk@neurosim.downstate.edu) for assistance.

Dependencies:
1. NEURON
2. Python
3. Pylab, SciPy, NumPy, and Matplotlib.

Instructions:

1. Unzip all files (which it looks like you've already done).
2. Type "nrnivmodl *.mod" in the directory. This should create a
directory called either i686 or x86_64, depending on your computer's
architecture, and put a file called "special" in that directory.


USAGE

1. Type "runsim". Two graphs should appear, corresponding to the two
types of results figures in the paper.


OPTIONS

* To adjust cortical vs. thalamic damage, simulation time, and model
size, please adjust the hopefully-clearly-labeled parameters in runsim.

20121210 Unused packages were removed from Python scripts.

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

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

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

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   A single column thalamocortical network model (Traub et al 2005) [Model]

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Chadderdon GL, Mohan A, Suter BA, Neymotin SA, Kerr CC, Francis JT, Shepherd GM, Lytton WW (2014) Motor cortex microcircuit simulation based on brain activity mapping. Neural Comput 26:1239-62 [Journal] [PubMed]

   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, 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]

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]

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

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   Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016) [Model]

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

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