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Neural art appraisal of painter: Dali or Picasso?

Yamamura, Hiromia c; Sawahata, Yasuhitoc; Yamamoto, Miyukia b; Kamitani, Yukiyasuc

doi: 10.1097/WNR.0b013e3283331322

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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aComprehensive Human Sciences, University of Tsukuba, Ibaraki

bAIST Neuroscience Research Institute, Ibaraki

cATR Computational Neuroscience Laboratories, Kyoto, Japan

Correspondence to Dr Yukiyasu Kamitani, PhD, ATR Computational Neuroscience Laboratories, 2-2-2 Hikaridai, Keihanna Science City, Kyoto 619-0288, Japan

Tel: +81 774 95 1212; fax: +81 774 95 1259; e-mail:

Hiromi Yamamura and Yasuhito Sawahata contributed equally to this work

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (

Received 21 August 2009 accepted 15 September 2009

© 2009 Lippincott Williams & Wilkins, Inc.