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| Research article summary (published 29 Sep 2003): |
Doubly distributional population codes: simultaneous representation of uncertainty and multiplicity.
Full Abstract
Perceptual inference fundamentally involves uncertainty, arising from noise in sensation and the ill-posed nature of many perceptual problems. Accurate perception requires that this uncertainty be correctly represented, manipulated, and learned about. The choices subjects make in various psychophysical experiments suggest that they do indeed take such uncertainty into account when making perceptual inferences, posing the question as to how uncertainty is represented in the activities of neuronal populations. Most theoretical investigations of population coding have ignored this issue altogether; the few existing proposals that address it do so in such a way that it is fatally conflated with another facet of perceptual problems that also needs correct handling:
multiplicity (that is, the simultaneous presence of multiple distinct stimuli). We present and validate a more powerful proposal for the way that population activity may encode uncertainty, both distinctly from and simultaneously with multiplicity.
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Author information
Author/s: Sahani, Maneesh (M); Dayan, Peter (P);
Affiliation: W.M. Keck Foundation Center for Integrative Neurosciences, Univ. of Calif., San Francisco, CA 94143-0732, USA. maneesh(-atsign-)phy.ucsf.edu
Journal and publication information
Publication Type: Journal Article
Journal: Neural computation (Neural Comput), published in United States. (Language: eng)
Reference: 2003-Oct; vol 15 (issue 10) : pp 2255-79
Dates: Created 2003/09/26; Completed 2003/10/29; Revised 2004/11/17;
PMID: 14511521, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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