Edinburgh Research Archive

Reading out population codes with a matched filter

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dc.contributor.author
van Rossum, Mark
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dc.contributor.author
Renart, Alfonso
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dc.contributor.author
Nelson, Sacha
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dc.contributor.author
Wang, X.-J.
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dc.contributor.author
Turrigiano, Gina G.
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dc.date.accessioned
2003-11-11T13:08:00Z
dc.date.available
2003-11-11T13:08:00Z
dc.date.issued
2001
dc.description.abstract
We study the optimal way to decode information present in a population code. Using a matched filter, the performance in Gaussian additive noise is as good as the theoretical maximum. The scheme can be applied when correlations among the neurons in the population are present. We show how the read out of the matched filter can be implemented in a neurophysiological realistic manner. The method seems advantageous for computations in layered networks.
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dc.format.extent
105317 bytes
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dc.format.mimetype
application/pdf
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dc.identifier.uri
http://hdl.handle.net/1842/234
dc.language.iso
en
dc.subject
Institute for Adaptive and Neural Computation
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dc.title
Reading out population codes with a matched filter
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dc.type
Preprint
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Informatics Publications