Probabilistic Computation in Human Perception under Variability in Encoding Precision
Name
Keshvari-2012-Probabilistic Comput.pdf
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Author(s)
Keshvari, Shaiyan Oliver
Berg, Ronald van den
Ma, Wei Ji
Date Issued
June 2012
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Keshvari, Shaiyan, Ronald van den Berg, and Wei Ji Ma. “Probabilistic Computation in Human Perception Under Variability in Encoding Precision.” Ed. Marc O. Ernst. PLoS ONE 7.6 (2012): e40216.
Version
Final published version
Abstract
A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain’s remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0040216
