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  The default-mode network represents aesthetic appeal that generalizes across visual domains

Vessel, E. A., Isik, A. I., Belfi, A. M., Stahl, J. L., & Starr, a. G. G. (2019). The default-mode network represents aesthetic appeal that generalizes across visual domains. Proceedings of the National Academy of Sciences of the United States of America. doi:10.1073/pnas.1902650116.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-9D87-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-9D88-2
Genre: Journal Article

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 Creators:
Vessel, Edward Allen1, Author              
Isik, Ayse Ilkay1, Author              
Belfi, Amy M.2, Author
Stahl, Jonathan L.3, Author
Starr, and G. Gabrielle4, Author
Affiliations:
1Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society, Grüneburgweg 14, 60322 Frankfurt am Main, DE, ou_2421697              
2Department of Psychological Science, Missouri University of Science and Technology , Rolla, MO 65409, ou_persistent22              
3Department of Psychology, The Ohio State University , Columbus, OH 43210, ou_persistent22              
4Departments of English and Neuroscience, Pomona College , Claremont, CA 91711, ou_persistent22              

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Free keywords: visual aesthetics, default-mode network, artwork, architecture, natural landscape
 Abstract: Visual aesthetic evaluations, which impact decision-making and well-being, recruit the ventral visual pathway, subcortical reward circuitry, and parts of the medial prefrontal cortex overlapping with the default-mode network (DMN). However, it is unknown whether these networks represent aesthetic appeal in a domain-general fashion, independent of domain-specific representations of stimulus content (artworks versus architecture or natural landscapes). Using a classification approach, we tested whether the DMN or ventral occipitotemporal cortex (VOT) contains a domain-general representation of aesthetic appeal. Classifiers were trained on multivoxel functional MRI response patterns collected while observers made aesthetic judgments about images from one aesthetic domain. Classifier performance (high vs. low aesthetic appeal) was then tested on response patterns from held-out trials from the same domain to derive a measure of domain-specific coding, or from a different domain to derive a measure of domain-general coding. Activity patterns in category-selective VOT contained a degree of domain-specific information about aesthetic appeal, but did not generalize across domains. Activity patterns from the DMN, however, were predictive of aesthetic appeal across domains. Importantly, the ability to predict aesthetic appeal varied systematically; predictions were better for observers who gave more extreme ratings to images subsequently labeled as “high” or “low.” These findings support a model of aesthetic appreciation whereby domain-specific representations of the content of visual experiences in VOT feed in to a “core” domain-general representation of visual aesthetic appeal in the DMN. Whole-brain “searchlight” analyses identified additional prefrontal regions containing information relevant for appreciation of cultural artifacts (artwork and architecture) but not landscapes.

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Language(s): eng - English
 Dates: 2019-02-132019-07-152019-09-04
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1073/pnas.1902650116
 Degree: -

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Title: Proceedings of the National Academy of Sciences of the United States of America
  Other : Proc. Acad. Sci. USA
  Other : Proc. Acad. Sci. U.S.A.
  Other : Proceedings of the National Academy of Sciences of the USA
  Abbreviation : PNAS
Source Genre: Journal
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Publ. Info: Washington, D.C. : National Academy of Sciences
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 0027-8424
CoNE: https://pure.mpg.de/cone/journals/resource/954925427230