Neural mechanisms underlying the hierarchical construction of perceived aesthetic value

Kiyohito Iigaya (), Sanghyun Yi, Iman A. Wahle, Sandy Tanwisuth, Logan Cross and John P. O’Doherty ()
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Kiyohito Iigaya: California Institute of Technology
Sanghyun Yi: California Institute of Technology
Iman A. Wahle: California Institute of Technology
Sandy Tanwisuth: California Institute of Technology
Logan Cross: California Institute of Technology
John P. O’Doherty: California Institute of Technology

Nature Communications, 2023, vol. 14, issue 1, 1-19

Abstract: Abstract 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.

Date: 2023
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DOI: 10.1038/s41467-022-35654-y

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