Abstract
One can infer an artist's identity from his or her artworks, but little is known about the neural representation of such elusive categorization. Here, we constructed a 'neural art appraiser' based on machine-learning methods that predicted the painter from the functional MRI activity pattern elicited by a painting. We found that Dali's and Picasso's artworks could be accurately classified based on brain activity alone, and that broadly distributed brain activity contributed to the neural prediction. Our approach provides a new means to probe into complex neural processes underlying art experiences.
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