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Published January 24, 2023 | Published
Journal Article Open

Neural mechanisms underlying the hierarchical construction of perceived aesthetic value


Little is known about how the brain computes the perceived aesthetic value of complex stimuli such as visual art. Here, we used computational methods in combination with functional neuroimaging to provide evidence that the aesthetic value of a visual stimulus is computed in a hierarchical manner via a weighted integration over both low and high level stimulus features contained in early and late visual cortex, extending into parietal and lateral prefrontal cortices. Feature representations in parietal and lateral prefrontal cortex may in turn be utilized to produce an overall aesthetic value in the medial prefrontal cortex. Such brain-wide computations are not only consistent with a feature-based mechanism for value construction, but also resemble computations performed by a deep convolutional neural network. Our findings thus shed light on the existence of a general neurocomputational mechanism for rapidly and flexibly producing value judgements across an array of complex novel stimuli and situations.

Additional Information

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. We thank Peter Dayan, Shin Shimojo, Pietro Perona, Lesley Fellows, Avinash Vaidya and Jeff Cockburn for discussions and suggestions. We also thank Ronan O'Doherty for drawing the bird and fruit-bowl paintings, Seiji Iigaya and Erica Iigaya for drawing the color field painting presented in this manuscript. This work was supported by NIDA grant R01DA040011 and the Caltech Conte Center for Social Decision Making (P50MH094258) to J.O.D., the Japan Society for Promotion of Science, the Swartz Foundation and the Suntory Foundation to K.I., and the William H. and Helen Lang SURF Fellowship to I.A.W. Contributions. K.I. and J.P.O. conceived and designed the project. K.I., S.Y., I.A.W., S.T., performed experiments and K.I., S.Y., I.A.W., L.C., J.P.O. analyzed and discussed results. K.I., S.Y., I.A.W., J.P.O. wrote the manuscript. Data availability. The data that support the findings of this study are available at https://github.com/kiigaya/Art or from the corresponding author upon request. Source data are provided with this paper. Code availability. The code that supports the findings of this study are available at https://github.com/kiigaya/Art or from the corresponding author upon request. The authors declare no competing interests.

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August 22, 2023
October 25, 2023