Neural information processing of visual pleasantness, unpleasantness, and thrill

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K21803
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 61:Human informatics and related fields
• Research Institution: The University of Tokyo
• Principal Investigator: Motoyoshi Isamu 東京大学, 大学院総合文化研究科, 教授 (60447034)
• Project Period (FY): 2020-07-30 – 2023-03-31
• Keywords: 視覚 / 情動 / 感性 / 快不快

Outline of Final Research Achievements

The present study investigated the possibility that emotional responses to natural images, such as pleasantness or unpleasantness, depend on rapid neural responses to specific features in the images, using psychological experiments and EEG analysis. The results showed that emotional responses strongly depend on a few class of specific image statistics, and that short latency EEG potentials to these image statistics are highly correlated with subjective emotional responses. It was found that image statistics that cause unpleasantness tend to deviate from the statistical regularity of the natural environment. As applications of these results, we also found that image features can be used to discriminate 'texturality' of a natural image, to classify painting styles, and to reconstruct the image itself from EEG signals.

Free Research Field

実験心理学

Academic Significance and Societal Importance of the Research Achievements

視覚的な美醜を扱った過去の研究は，恣意的に作られた幾何学図形の恣意的な変数の効果を検討したものが多い．本研究で得られた成果は，現実世界の自然画像に含まれる美醜に関連する特徴を心理・生理データから逆導出する点で高い生態学的妥当性をもっており，感覚刺激による情動喚起の基礎研究のみならず嗜好やデザインの研究の方向性に影響を与えると期待される．また，本研究が示唆した情動的価値の直接計算の過程は，知覚→認知→価値判断というナイーブな理解の図式を打破し，視覚情報処理が本質的に課題特異的であることも明らかにしている．