A spiking model of cortical broadcast and competition (Shanahan 2008)

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Accession:116871
"This paper presents a computer model of cortical broadcast and competition based on spiking neurons and inspired by the hypothesis of a global neuronal workspace underlying conscious information processing in the human brain. In the model, the hypothesised workspace is realised by a collection of recurrently interconnected regions capable of sustaining and disseminating a reverberating spatial pattern of activation. ..."
Reference:
1 . Shanahan M (2008) A spiking neuron model of cortical broadcast and competition. Conscious Cogn 17:288-303 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Neocortex;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Temporal Pattern Generation; Spatio-temporal Activity Patterns; Simplified Models; Working memory;
Implementer(s): Shanahan, Murray [m.shanahan at imperial.ac.uk];
function count = count_firings(layer,i,tmin,tmax,a,b)
% Count neuron firings for layer i between times tmin and tmax, for
% neurons numbered from a to b

firings = layer{i}.firings;
% Convert indices
C1 = reshape(1:256,16,16);
C2 = zeros(16,16);
C2(1:64) = C1(9:16,1:8); % NW
C2(65:128) = C1(9:16,9:16); % NE
C2(129:192) = C1(1:8,1:8); % SW
C2(193:256) = C1(1:8,9:16); % SE
% Invert index
for k = 1:256
   C1(C2(k)) = k;
end
% Map to new neuron numbers
for k = 1:length(firings)
   firings(k,2) = C1(firings(k,2));
end
F = firings(:,1) >= tmin & firings(:,1) < tmax & ...
   firings(:,2) >= a & firings(:,2) < b;
count = sum(F);

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