# Predictive information in a sensory population

## Author(s): Palmer, Stephanie E; Marre, Olivier; Berry II, Michael J; Bialek, William

To refer to this page use: http://arks.princeton.edu/ark:/88435/pr1406k
DC FieldValueLanguage
dc.contributor.authorPalmer, Stephanie E-
dc.contributor.authorMarre, Olivier-
dc.contributor.authorBerry II, Michael J-
dc.contributor.authorBialek, William-
dc.date.accessioned2017-11-21T18:53:42Z-
dc.date.available2017-11-21T18:53:42Z-
dc.date.issued2015-06-02en_US
dc.identifier.citationPalmer, Stephanie E, Marre, Olivier, Berry, Michael J, Bialek, William. (2015). Predictive information in a sensory population. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 112 (6908 - 6913. doi:10.1073/pnas.1506855112en_US
dc.identifier.issn0027-8424-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1406k-
dc.description.abstractGuiding behavior requires the brain to make predictions about the future values of sensory inputs. Here, we show that efficient pre- dictive computation starts at the earliest stages of the visual system. We compute how much information groups of retinal ganglion cells carry about the future state of their visual inputs and show that nearly every cell in the retina participates in a group of cells for which this predictive information is close to the physical limit set by the statistical structure of the inputs themselves. Groups of cells in the retina carry information about the future state of their own activity, and we show that this information can be compressed further and encoded by downstream predictor neurons that exhibit feature selectivity that would support predictive computations. Efficient representation of predictive information is a candidate principle that can be applied at each stage of neural computation.en_US
dc.format.extent6908 - 6913en_US
dc.language.isoenen_US
dc.relation.ispartofPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAen_US
dc.rightsAuthor's manuscripten_US
dc.titlePredictive information in a sensory populationen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1073/pnas.1506855112-
dc.date.eissued2015-05-18en_US
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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