Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 112, Issue 22, Pages 6908-6913Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1506855112
Keywords
neural coding; retina; information theory
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Funding
- National Science Foundation (NSF) [PHY-1066293]
- NSF [IIS-0613435, PHY-0957573, PHY-1305525, CCF-0939370]
- National Institutes of Health [EY-014196]
- Novartis (through the Life Sciences Research Foundation)
- Swartz Foundation
- W. M. Keck Foundation
- Division Of Physics
- Direct For Mathematical & Physical Scien [1451171, 1305525] Funding Source: National Science Foundation
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Guiding behavior requires the brain to make predictions about the future values of sensory inputs. Here, we show that efficient predictive 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.
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