Literature DB >> 20884577

Rapidly learned stimulus expectations alter perception of motion.

Matthew Chalk1, Aaron R Seitz, Peggy Seriès.   

Abstract

Expectations broadly influence our experience of the world. However, the process by which they are acquired and then shape our sensory experiences is not well understood. Here, we examined whether expectations of simple stimulus features can be developed implicitly through a fast statistical learning procedure. We found that participants quickly and automatically developed expectations for the most frequently presented directions of motion and that this altered their perception of new motion directions, inducing attractive biases in the perceived direction as well as visual hallucinations in the absence of a stimulus. Further, the biases in motion direction estimation that we observed were well explained by a model that accounted for participants' behavior using a Bayesian strategy, combining a learned prior of the stimulus statistics (the expectation) with their sensory evidence (the actual stimulus) in a probabilistically optimal manner. Our results demonstrate that stimulus expectations are rapidly learned and can powerfully influence perception of simple visual features.

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Year:  2010        PMID: 20884577     DOI: 10.1167/10.8.2

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  46 in total

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Authors:  Xue-Xin Wei; Alan A Stocker
Journal:  Nat Neurosci       Date:  2015-09-07       Impact factor: 24.884

2.  Neural Integration of Stimulus History Underlies Prediction for Naturalistically Evolving Sequences.

Authors:  Brian Maniscalco; Jennifer L Lee; Patrice Abry; Amy Lin; Tom Holroyd; Biyu J He
Journal:  J Neurosci       Date:  2018-01-08       Impact factor: 6.167

3.  Expectations developed over multiple timescales facilitate visual search performance.

Authors:  Nikos Gekas; Aaron R Seitz; Peggy Seriès
Journal:  J Vis       Date:  2015       Impact factor: 2.240

4.  Generalization of prior information for rapid Bayesian time estimation.

Authors:  Neil W Roach; Paul V McGraw; David J Whitaker; James Heron
Journal:  Proc Natl Acad Sci U S A       Date:  2016-12-22       Impact factor: 11.205

5.  The brain uses adaptive internal models of scene statistics for sensorimotor estimation and planning.

Authors:  Oh-Sang Kwon; David C Knill
Journal:  Proc Natl Acad Sci U S A       Date:  2013-02-25       Impact factor: 11.205

6.  Environmental consistency determines the rate of motor adaptation.

Authors:  Luis Nicolas Gonzalez Castro; Alkis M Hadjiosif; Matthew A Hemphill; Maurice A Smith
Journal:  Curr Biol       Date:  2014-05-01       Impact factor: 10.834

7.  Dissociable behavioural outcomes of visual statistical learning.

Authors:  Brett C Bays; Nicholas B Turk-Browne; Aaron R Seitz
Journal:  Vis cogn       Date:  2016-02-22

8.  Construction and evaluation of an integrated dynamical model of visual motion perception.

Authors:  Émilien Tlapale; Barbara Anne Dosher; Zhong-Lin Lu
Journal:  Neural Netw       Date:  2015-03-28

9.  Error-driven learning in statistical summary perception.

Authors:  Judith E Fan; Nicholas B Turk-Browne; Jordan A Taylor
Journal:  J Exp Psychol Hum Percept Perform       Date:  2015-09-21       Impact factor: 3.332

10.  Prior expectations induce prestimulus sensory templates.

Authors:  Peter Kok; Pim Mostert; Floris P de Lange
Journal:  Proc Natl Acad Sci U S A       Date:  2017-09-12       Impact factor: 11.205

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