Characterizing Dynamic Neural Representations of Scene Attractiveness

Author:

Kaiser Daniel1ORCID

Affiliation:

1. Justus-Liebig-University Gießen, Germany

Abstract

Abstract Aesthetic experiences during natural vision are varied: They can arise from viewing scenic landscapes, interesting architecture, or attractive people. Recent research in the field of neuroaesthetics has taught us a lot about where in the brain such aesthetic experiences are represented. Much less is known about when such experiences arise during the cortical processing cascade. Particularly, the dynamic neural representation of perceived attractiveness for rich natural scenes is not well understood. Here, I present data from an EEG experiment, in which participants provided attractiveness judgments for a set of diverse natural scenes. Using multivariate pattern analysis, I demonstrate that scene attractiveness is mirrored in early brain signals that arise within 200 msec of vision, suggesting that the aesthetic appeal of scenes is first resolved during perceptual processing. In more detailed analyses, I show that even such early neural correlates of scene attractiveness are partly related to interindividual variation in aesthetic preferences and that they generalize across scene contents. Together, these results characterize the time-resolved neural dynamics that give rise to aesthetic experiences in complex natural environments.

Publisher

MIT Press

Subject

Cognitive Neuroscience

Reference47 articles.

1. The psychophysics toolbox;Brainard;Spatial Vision,1997

2. First gender, then attractiveness: Indications of gender-specific attractiveness processing via ERP onsets;Carbon;Neuroscience Letters,2018

3. Activation of the prefrontal cortex in the human visual aesthetic perception;Cela-Conde;Proceedings of the National Academy of Sciences, U.S.A.,2004

4. Unique semantic space in the brain of each beholder predicts perceived similarity;Charest;Proceedings of the National Academy of Sciences, U.S.A.,2014

5. Deep neural networks as scientific models;Cichy;Trends in Cognitive Sciences,2019

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