Neural mechanisms underlying the hierarchical construction of perceived aesthetic value

• Published in: Nature communications Vol. 14; no. 1; pp. 127 - 19
• Main Authors: Iigaya, Kiyohito, Yi, Sanghyun, Wahle, Iman A., Tanwisuth, Sandy, Cross, Logan, O’Doherty, John P.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 24.01.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/378/116; 631/378/2649; Aesthetics; Artificial neural networks; Brain; Brain - diagnostic imaging; Brain mapping; Brain Mapping - methods; Computational neuroscience; Construction; Cortex (parietal); Esthetics; Functional magnetic resonance imaging; Humanities and Social Sciences; Magnetic Resonance Imaging - methods; Medical imaging; multidisciplinary; Neural networks; Neuroimaging; Neurosciences; Prefrontal cortex; Prefrontal Cortex - diagnostic imaging; Science; Science (multidisciplinary); Valuation; Visual cortex; Visual Cortex - diagnostic imaging; Visual stimuli
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-022-35654-y

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. How the brain computes the value of complex stimuli such as visual art remains poorly understood. Here, the authors use computational models and fMRI to show that this process involves an integration over low- and high-level features across visual, parietal, and frontal cortical areas.