A Bayesian model of sensory adaptation

Yoshiyuki Sato, Kazuyuki Aihara

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Recent studies reported two opposite types of adaptation in temporal perception. Here, we propose a Bayesian model of sensory adaptation that exhibits both types of adaptation. We regard adaptation as the adaptive updating of estimations of time-evolving variables, which determine the mean value of the likelihood function and that of the prior distribution in a Bayesian model of temporal perception. On the basis of certain assumptions, we can analytically determine the mean behavior in our model and identify the parameters that determine the type of adaptation that actually occurs. The results of our model suggest that we can control the type of adaptation by controlling the statistical properties of the stimuli presented.

Original languageEnglish
Article numbere19377
JournalPloS one
Volume6
Issue number4
DOIs
Publication statusPublished - 2011
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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