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

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"... We sought to measure how the activity of the network alters information flow from inputs to output patterns. Information handling by the network reflected the degree of internal connectivity. ... With greater connectivity strength, the recurrent network translated activity and information due to contribution of activity from intrinsic network dynamics. ... At still higher internal synaptic strength, the network corrupted the external information, producing a state where little external information came through. The association of increased information retrieved from the network with increased gamma power supports the notion of gamma oscillations playing a role in information processing."
1 . 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 [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 V1 pyramidal corticothalamic L6 cell; Neocortex V1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I Na,t; I A; I K;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Information transfer;
Implementer(s): Lytton, William [billl at]; Neymotin, Sam [samn at];
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex V1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 interneuron basket PV cell; GabaA; AMPA; NMDA; I Na,t; I A; I K;
AMPA.mod *
clampex.mod *
cp.mod *
cp2.mod *
Iahp.mod *
Ican.mod *
IL3.mod *
infot.mod *
intfsw.mod *
kdr2.mod *
misc.mod *
naf2.mod *
nap.mod *
NMDA.mod *
nthh.mod *
ntIh.mod *
ntt.mod *
updown.mod *
misc.h *
mosinit.hoc *
 $Id: readme.txt,v 1.2 2010/11/01 13:45:41 samn Exp $ 

                           Neocortical Column Demo Readme

This package contains the source code from the paper:
  Synaptic information transfer in computer models of neocortical columns.
  Article by SA Neymotin, KM Jacobs, AA Fenton, and WW Lytton
  Journal of Computational Neuroscience (2010), in press.
  PubMed ID 20556639.

It allows simulating the activity of a neocortical column using
conductance- based neurons. In addition, NEURON vector implementations
of normalized transfer entropy are provided in infot.mod. For more
information on methods used, please see the paper.

                      Compilation/running instructions (LINUX)

You will need the NEURON simulator in order to run this simulation.
It is available for download at
Detailed installation instructions are available there as well.

Once you have NEURON installed you will need to compile the .mod files
included in the zip file. To do so first extract the contents of the
zip file into a single flat directory.

If you are on LINUX/UNIX then run nrnivmodl *.mod from the command
line to compile the .mod files. If this is done properly, an
executable named 'special' will be produced in the x86_64 subdirectory
(on 64 bit machines) or x86 subdirectory on 32 bit machines.

(If you are using WINDOWS this is not guaranteed to work but try the
instructions at: for more
information on compiling new mechanisms into NEURON .)

Next, to run the simulation enter the following command at the command
  ./x86_64/special (or ./x86/special )

This will begin the NEURON simulator.  You will then be at the NEURON
command prompt which should look like this: oc> Type
load_file("mosinit.hoc") and press enter.  This will start the
neocortical column simulation.  A GUI window will be displayed that
will allow running the simulation and displaying output consisting of:

 1. spike raster
 2. local field potential
 3. voltage of several cells with different dynamical properties


For questions/comments/collaborations please contact 
Samuel Neymotin at samn at neurosim dot downstate dot edu
Bill Lytton at billl at neurosim dot downstate dot edu

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