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dc.contributor.authorRoach, N.W.*
dc.contributor.authorMcGraw, Paul V.*
dc.contributor.authorWhitaker, David J.*
dc.contributor.authorHeron, James*
dc.date.accessioned2017-01-26T12:52:55Z
dc.date.available2017-01-26T12:52:55Z
dc.date.issued2017-01-10
dc.identifier.citationRoach NW, McGraw PV, Whitaker DJ et al (2017) Generalization of prior information for rapid Bayesian time estimation. Proceedings of the National Academy of Sciences of the United States of America. 114(2): 412-417.en_US
dc.identifier.urihttp://hdl.handle.net/10454/11184
dc.descriptionYesen_US
dc.description.abstractTo enable effective interaction with the environment, the brain combines noisy sensory information with expectations based on prior experience. There is ample evidence showing that humans can learn statistical regularities in sensory input and exploit this knowledge to improve perceptual decisions and actions. However, fundamental questions remain regarding how priors are learned and how they generalize to different sensory and behavioral contexts. In principle, maintaining a large set of highly specific priors may be inefficient and restrict the speed at which expectations can be formed and updated in response to changes in the environment. However, priors formed by generalizing across varying contexts may not be accurate. Here, we exploit rapidly induced contextual biases in duration reproduction to reveal how these competing demands are resolved during the early stages of prior acquisition. We show that observers initially form a single prior by generalizing across duration distributions coupled with distinct sensory signals. In contrast, they form multiple priors if distributions are coupled with distinct motor outputs. Together, our findings suggest that rapid prior acquisition is facilitated by generalization across experiences of different sensory inputs but organized according to how that sensory information is acted on.en_US
dc.language.isoenen_US
dc.rights© 2016 National Academy of Sciences. Full-text reproduced in accordance with the publisher’s self-archiving policy.
dc.subjectBayesian inference; Time perception; Sensorimotor learningen_US
dc.titleGeneralization of prior information for rapid Bayesian time estimationen_US
dc.status.refereedYesen_US
dc.date.Accepted2016-11-28
dc.date.application2016-12-22
dc.typeArticleen_US
dc.type.versionAccepted manuscripten_US
dc.identifier.doihttps://doi.org/10.1073/pnas.1610706114
refterms.dateFOA2018-07-25T16:00:02Z


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