Integrative Bayesian model of two opposite types of sensory adaptation

Y. Sato, K. Aihara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Adaptation is a fundamental property of human perception. Recently, it was found that there are two opposite types of adaptation to repetitive stimuli with temporal difference. In this paper, we construct an integrative model of adaptation. We model the perception as a Bayesian inference and also model the two types of adaptation as changes in the likelihood function and the prior distribution in the Bayesian inference. We examine our model analytically and show how the type of adaptation depends on model parameters.

Original languageEnglish
Title of host publicationProceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09
Pages518-521
Number of pages4
Publication statusPublished - 2009 Dec 1
Externally publishedYes
Event14th International Symposium on Artificial Life and Robotics, AROB 14th'09 - Oita, Japan
Duration: 2008 Feb 52009 Feb 7

Publication series

NameProceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09

Other

Other14th International Symposium on Artificial Life and Robotics, AROB 14th'09
CountryJapan
CityOita
Period08/2/509/2/7

Keywords

  • Bayesian calibration
  • Bayesian inference
  • Lag adaptation
  • Ventriloquism aftereffect

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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