Abstract
People readily distinguish beauty experiences from other mundane pleasures. This intuition is reflected in models of aesthetic experience and confirmed by fMRI evidence that prefrontal regions and the default mode network are selectively involved in experiencing beauty. This is consistent with Immanuel Kant's notion that "beauty requires thought" being a defining quality of the experience of beauty. Here we experimentally test Kant's hypothesis that beauty differs from "ordinary" pleasures in requiring cognitive capacity. Participants were presented with beautiful images (self-selected or experimenter-selected), ordinary pleasures (pretty image or eating candy), or neutral images for 30 s each. During stimulus exposure and a further 60 s after, participants continuously rated pleasure using a custom smartphone app (emotiontracker.com), which samples the distance between two fingers once per second and converts it to a numerical rating (1-10). At the end of each trial, we asked participants if they felt beauty (options: definitely yes, perhaps yes, perhaps no, definitely no). We manipulated cognitive capacity by requiring participants to execute an auditory 2-back task (N=20) in 50% of trials. Only for beautiful stimuli, continuous-pleasure and final-beauty ratings were much lower for trials with vs. without the 2-back task (M=7.7 vs. 5.5 maximum pleasure for self-selected images, and 7.3 vs. 5.4 for experimenter-selected, SE≈0.7). Pleasure and beauty ratings for all other stimuli were unaffected. In a smaller control experiment, we asked participants to remember a string of digits (one digit more than their digit span) in 50% of trials to selectively limit working memory capacities. This manipulation did not result in an impairment of beauty experiences. These results indicate that the process underlying a beauty experience has specific cognitive demands (not working memory), which, in combination with the experience of high pleasure, may be hallmarks of experiencing beauty.
Meeting abstract presented at VSS 2016