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01-11-2018 | Original Paper

Two-Stage Processing of Aesthetic Information in the Human Brain Revealed by Neural Adaptation Paradigm

Authors: Miho Iwasaki, Yasuki Noguchi, Ryusuke Kakigi

Published in: Brain Topography | Issue 6/2018

Abstract

Some researchers in aesthetics assume visual features related to aesthetic perception (e.g. golden ratio and symmetry) commonly embedded in masterpieces. If this is true, an intriguing hypothesis is that the human brain has neural circuitry specialized for the processing of visual beauty. We presently tested this hypothesis by combining a neuroimaging technique with the repetition suppression (RS) paradigm. Subjects (non-experts in art) viewed two images of sculptures sequentially presented. Some sculptures obeyed the golden ratio (canonical images), while the golden proportion were impaired in other sculptures (deformed images). We found that the occipito-temporal cortex in the right hemisphere showed the RS when a canonical sculpture (e.g. Venus de Milo) was repeatedly presented, but not when its deformed version was repeated. Furthermore, the right parietal cortex showed the RS to the canonical proportion even when two sculptures had different identities (e.g. Venus de Milo as the first stimulus and David di Michelangelo as the second), indicating that this region encodes the golden ratio as an abstract rule shared by different sculptures. Those results suggest two separate stages of neural processing for aesthetic information (one in the occipito-temporal and another in the parietal regions) that are hierarchically arranged in the human brain.

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Title: Two-Stage Processing of Aesthetic Information in the Human Brain Revealed by Neural Adaptation Paradigm
Authors: Miho Iwasaki
Yasuki Noguchi
Ryusuke Kakigi
Publication date: 01-11-2018
Publisher: Springer US
Published in: Brain Topography / Issue 6/2018
Print ISSN: 0896-0267
Electronic ISSN: 1573-6792
DOI: https://doi.org/10.1007/s10548-018-0654-7

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Two-Stage Processing of Aesthetic Information in the Human Brain Revealed by Neural Adaptation Paradigm

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