Decoding dynamic affective responses to naturalistic videos with shared neural patterns.

Autor: Chan HY; Department of Marketing Management, Rotterdam School of Management, Erasmus University Rotterdam, the Netherlands. Electronic address: chan@rsm.nl., Smidts A; Department of Marketing Management, Rotterdam School of Management, Erasmus University Rotterdam, the Netherlands., Schoots VC; Department of Marketing Management, Rotterdam School of Management, Erasmus University Rotterdam, the Netherlands., Sanfey AG; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands., Boksem MAS; Department of Marketing Management, Rotterdam School of Management, Erasmus University Rotterdam, the Netherlands.
Jazyk: angličtina
Zdroj: NeuroImage [Neuroimage] 2020 Aug 01; Vol. 216, pp. 116618. Date of Electronic Publication: 2020 Feb 07.
DOI: 10.1016/j.neuroimage.2020.116618
Abstrakt: This study explored the feasibility of using shared neural patterns from brief affective episodes (viewing affective pictures) to decode extended, dynamic affective sequences in a naturalistic experience (watching movie-trailers). Twenty-eight participants viewed pictures from the International Affective Picture System (IAPS) and, in a separate session, watched various movie-trailers. We first located voxels at bilateral occipital cortex (LOC) responsive to affective picture categories by GLM analysis, then performed between-subject hyperalignment on the LOC voxels based on their responses during movie-trailer watching. After hyperalignment, we trained between-subject machine learning classifiers on the affective pictures, and used the classifiers to decode affective states of an out-of-sample participant both during picture viewing and during movie-trailer watching. Within participants, neural classifiers identified valence and arousal categories of pictures, and tracked self-reported valence and arousal during video watching. In aggregate, neural classifiers produced valence and arousal time series that tracked the dynamic ratings of the movie-trailers obtained from a separate sample. Our findings provide further support for the possibility of using pre-trained neural representations to decode dynamic affective responses during a naturalistic experience.
Competing Interests: Declaration of competing interest The authors declare no competing financial interests.
(Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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