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2016 Fiscal Year Final Research Report

Brain decoding of impressions on visual images

Research Project

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Project/Area Number 26870935
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Kansei informatics
Cognitive science
Research InstitutionAdvanced Telecommunications Research Institute International

Principal Investigator

Horikawa Tomoyasu  株式会社国際電気通信基礎技術研究所, 脳情報通信総合研究所, 主任研究員 (60721876)

Project Period (FY) 2014-04-01 – 2017-03-31
Keywords脳情報デコーディング / fMRI / 印象 / 視覚
Outline of Final Research Achievements

The brain decoding approach was used to examine whether impressions on visual images can be predicted from human brain activity patterns measured using functional magnetic resonance imaging. The decoding analyses were performed to evaluate the predictability of 1) hierarchical visual features, 2) twelve types of impression scores associated with surface characteristics, and 3) positive-negative scores (valence), which were obtained using computational models and human rating. The analyses suggest that the lower/higher visual features were better predicted from the lower/higher visual areas, the impression scores were successfully predicted from the mid- to high-level visual areas, and the valence score was accurately predicted from the frontal brain areas. These results suggest that the multi-level visual information associated with subjective impressions on visual images can be decoded from human brain activity patterns.

Free Research Field

神経情報学

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Published: 2018-03-22  

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