ModelDB: Parametric computation and persistent gamma in a cortical model (Chambers et al. 2012)

Parametric computation and persistent gamma in a cortical model (Chambers et al. 2012)

Accession: 144579

Using the Traub et al (2005) model of the cortex we determined how 33 synaptic strength parameters control gamma oscillations. We used fractional factorial design to reduce the number of runs required to 4096. We found an expected multiplicative interaction between parameters.
Reference: Chambers JD, Bethwaite B, Diamond NT, Peachey T, Abramson D, Petrou S, Thomas EA (2012) Parametric computation predicts a multiplicative interaction between synaptic strength parameters that control gamma oscillations. 6:53. Epub 2012 Jul 24. Front Comput Neurosci. 6:53:1-12 [PubMed]

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Model Information (Click on a link to find other models with that property)

Model Type:	Network; Axon; Synapse; Channel; Dendrite;
Brain Region(s)/Organism:
Cell Type(s):	Neocortical pyramidal neuron: deep; Neocortical pyramidal neuron: superficial; Neocortical basket cell; Neocortical Fast Spiking (FS) interneuron; Spiny stellate cell; Neocortical Regular Spiking (RS) neuron; Neocortical Low Threshold Spiking (LTS) neuron;
Channel(s):	I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na;
Gap Junctions:	Gap junctions;
Receptor(s):	GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):	Gaba; Glutamate;
Simulation Environment:	Neuron;
Model Concept(s):	Oscillations; Parameter sensitivity;
Implementer(s):	Thomas, Evan [evan at evan-thomas.net]; Chambers, Jordan [jordandchambers at gmail.com];

Search NeuronDB for information about: Neocortical pyramidal neuron: deep; Neocortical pyramidal neuron: superficial; Neocortical basket cell; GabaA; AMPA; NMDA; I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na; Gaba; Glutamate;

Model files

Help downloading and running models

These are the source files to generate the data in Figs 4-6 of the paper:

"Parametric computation predicts a multiplicative interaction between synaptic
strength parameters that control gamma oscillations" by Jordan D. Chambers,
Blair Bethwaite, Neil T. Diamond, Tom Peachey, David Abramson,
Steve Petrou1 and Evan A. Thomas. 
Frontiers in Computational Neuroscience (2012) 6:1

1) Build the neuron load library from the command line
nrnivmodl mod

2) The python script des2runs.py reads the design file created by Nimrod,
creates a PBS run file which passes the parameters to neuron model and 
submits the run to the PBS queueing system.

3) The matlab script EFPgen.m reads the output files and generates local 
field traces in matlab format (EFP.mat)

4) The matlab script EFP2PSD.m reads the EPF data and creates power spectra
in matlab format (PSD.mat)

5) The matlab script singleoutput.m reads the PSD file and generates the
output used in figs 4, 5 and 6 of the paper.

You will almost certainly need to modify these scripts to work in your
environment.

Any questions? Email me evan@evan-thomas.net

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