ModelDB: Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010)

Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010)

Accession: 144027

"... The network simulations were also based on a previously published model(Latham et al. 2000), but with modifications to allow the addition and detection of extra spikes (see Supplementary Information, section 7)."
Reference: London M, Roth A, Beeren L, Hausser M, Latham PE (2010) Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex. Nature 466:123-7 [PubMed]

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

Model Type:	Network;
Brain Region(s)/Organism:	Neocortex;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:	C or C++ program;
Model Concept(s):	Activity Patterns;
Implementer(s):

Model files

Help downloading and running models

This is the readme for the code for the paper:

London M, Roth A, Beeren L, Hausser M, Latham PE (2010) Sensitivity to
perturbations in vivo implies high noise and suggests rate coding in
cortex. Nature 466:123-7

The network code was supplied by Peter Latham and updated by Tom Morse
for compiling in a modern linux (tested with g++ 4.4.3) by simply
typing "make".  You can follow built-in help by running the executable
./theta1d without any arguments.

To run you can create a sample input file by typing:

./theta1d -s > sample_inputfile.txt

You can then edit sample_inputfile.txt as desired and then type

./theta1d sample_inputfile.txt

to run the model.  The provided sample takes 10 seconds to run and
should produce graphs such as under matlab/octave commands:

For population averaged rate for excitatory (blue) and inhibitory
cells (red):

load arate;
figure
plot(arate(:,1),arate(:,2))
hold on
plot(arate(:,1),arate(:,3),'r')



For the last second of voltage activity of a selected neuron:

load v;
figure
plot(v(9000:10000,1),v(9000:10000,2))

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