Literature DB >> 32294538

Intersubject representational similarity analysis reveals individual variations in affective experience when watching erotic movies.

Pin-Hao A Chen1, Eshin Jolly2, Jin Hyun Cheong2, Luke J Chang3.   

Abstract

We spend much of our lives pursuing or avoiding affective experiences. However, surprisingly little is known about how these experiences are represented in the brain and if they are shared across individuals. Here, we explored variations in the construction of an affective experience during a naturalistic viewing paradigm based on subjective preferences in sociosexual desire and self-control using intersubject representational similarity analysis (IS-RSA). We found that when watching erotic movies, intersubject variations in sociosexual desire preferences of 26 heterosexual males were associated with similarly structured fluctuations in the cortico-striatal reward, default mode, and mentalizing networks. In contrast, variations in the self-control preferences were associated with shared dynamics in the fronto-parietal executive control and cingulo-insular salience networks. Importantly, these results were specific to the affective experience, as we did not observe any relationship with variation in preferences when individuals watched neutral movies. Moreover, these results appear to require multivariate representations of preferences as we did not observe any significant associations using single scalar summary scores. Our findings indicate that multidimensional variations in individual preferences can be used to uncover unique dimensions of an affective experience, and that IS-RSA can provide new insights into the neural processes underlying psychological experiences elicited through naturalistic experimental designs.
Copyright © 2020. Published by Elsevier Inc.

Entities:  

Keywords:  Affect; Desire; Intersubject correlation; Intersubject representational similarity analysis; Self-control; fMRI

Mesh:

Year:  2020        PMID: 32294538      PMCID: PMC7955800          DOI: 10.1016/j.neuroimage.2020.116851

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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