Neural transformations on spike timing information (Tripp and Eliasmith 2007)

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Accession:136380
" ... Here we employ computational methods to show that an ensemble of neurons firing at a constant mean rate can induce arbitrarily chosen temporal current patterns in postsynaptic cells. ..."
Reference:
1 . Tripp B, Eliasmith C (2007) Neural populations can induce reliable postsynaptic currents without observable spike rate changes or precise spike timing. Cereb Cortex 17:1830-40 [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): Abstract integrate-and-fire leaky neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Activity Patterns; Temporal Pattern Generation;
Implementer(s): Tripp, Bryan [bryan.tripp at mail.mcgill.ca]; Eliasmith, Chris [celiasmith at uwaterloo.ca];
% This script experiments with sensitivity to spike jitter AND NOISE SPIKES
% with varying ISI COVs

useBandLimitedJitter = 0;

mix = [0 1 0; 1 8 0; 1 1 0; 1 0 0; 3 0 1; 1 0 1; 1 0 5]; %weights for combining Poisson, regular, and burst firing 

% jitter (s), noise spikes (proportion of base pattern)
noise = [0 .25; ... 
        0 .5; ...
        0 1; ...
        .004 .25; ...
        .004 .5; ...
        .004 1; ...
        ] 

doCOV(mix, noise, 'data_COVNS', useBandLimitedJitter)


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