Research on brain network underlying multisensory integration using Bayesian theory

2018 Fiscal Year Final Research Report

• Project/Area Number: 16H03749
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Experimental psychology
• Research Institution: The University of Tokyo
• Principal Investigator: Yotsumoto Yuko 東京大学, 大学院総合文化研究科, 准教授 (80580927)
• Co-Investigator(Kenkyū-buntansha): 佐藤 隆夫 立命館大学, 総合心理学部, 教授 (60272449)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Keywords: ベイズ理論 / 知覚

Outline of Final Research Achievements

The aim of this study was to investigate how our brain compensates sensory uncertainty by combining multisensory information derived from an event, and by integrating the current sensory signal with the prior knowledge about the statistical structure of previous events.We measured the timing sensitivity and the central tendency for unisensory and multisensory stimuli with sensory uncertainty systematically manipulated by adding noise, and proposed computational models that indicate that the optimal multisensory integration precedes the Bayesian time estimation causing the central tendency. Our study suggested that the brain exploits the prior information stored at different processing stages adaptively in accordance with incoming sensory evidences.

Free Research Field

知覚、認知神経科学

Academic Significance and Societal Importance of the Research Achievements

一連の研究により、ヒトの脳は、さまざまなモダリティの感覚情報を統計的に最適かされた方法で統合することが示された。また、その結果に基づいて感覚情報の統合モデルを提案した。