title: Probabilistic computation in human perception under variability in encoding precision.
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.
authors: Department of Neuroscience, Baylor College of Medicine, Houston, Texas, United States of America.
authors: Shaiyan
authors: S
authors: Keshvari
authors: Ronald
authors: R
authors: van den Berg
authors: Wei Ji
authors: WJ
authors: Ma
mesh_terms: D000328:Adult; D003657:Decision Making; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008959:Models, Neurological; D010775:Photic Stimulation; D011336:Probability; D015203:Reproducibility of Results; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult