September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
The default mode network, but not ventral occipitotemporal cortex, contains a domain-general representation of visual aesthetic appeal
Author Affiliations & Notes
  • Edward A Vessel
    Max Planck Institute for Empirical Aesthetics
  • Ayse Ilkay Isik
    Max Planck Institute for Empirical Aesthetics
  • Amy M Belfi
    Missouri University of Science and Technology
  • Jonathan L. Stahl
    The Ohio State University
  • G. Gabrielle Starr
    Pomona College
Journal of Vision September 2019, Vol.19, 97d. doi:https://doi.org/10.1167/19.10.97d
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      Edward A Vessel, Ayse Ilkay Isik, Amy M Belfi, Jonathan L. Stahl, G. Gabrielle Starr; The default mode network, but not ventral occipitotemporal cortex, contains a domain-general representation of visual aesthetic appeal. Journal of Vision 2019;19(10):97d. doi: https://doi.org/10.1167/19.10.97d.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Judgments of aesthetic appeal are critical for decision-making, and aesthetic experiences strongly impact well-being. A wide variety of visual objects can be evaluated aesthetically, from landscapes to artworks. Aesthetic evaluations 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 any of these networks represent aesthetic appeal in a domain-general fashion, independent of domain-specific representations of stimulus content. 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 fMRI response patterns collected while 18 observers made aesthetic judgments about images from one aesthetic domain (e.g. artwork). 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 trials of a different domain (e.g. architecture or landscape) to derive a measure of domain-general coding. Activity patterns in the 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, variation in classifier performance across observers reflected the distances (d’) between each observers’ behavioral ratings of images labeled as “high” or “low” aesthetic appeal, rather than random measurement noise (R2 = 0.53). 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 of landscapes.

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