a bayesian model of sensory adaptation感觉适应的贝叶斯模型.pdfVIP

A Bayesian Model of Sensory Adaptation 1 2 Yoshiyuki Sato *, Kazuyuki Aihara 1 Graduate School of Information Systems, The University of Electro-Communications, Tokyo, Japan, 2 Institute of Industrial Science, The University of Tokyo, Tokyo, Japan 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. Citation: Sato Y, Aihara K (2011) A Bayesian Model of Sensory Adaptation. PLoS ONE 6(4): e19377. doi:10.1371/journal.pone.0019377 Editor: Hiroaki Matsunami, Duke University, United States of America Received October 13, 2010; Accepted April 3, 2011; Published April 25, 2011 Copyright: 2011 Sato, Aihara. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This research is partially supported by the Japan Society for the Promotion of Science (JSPS) through its Funding Program for World-Leading Innovative RD on Science and Technology (FIRST Program) and Grant-in-Aid for Scientific Researc