| Literature DB >> 19907352 |
Hiromi Yamamura1, Yasuhito Sawahata, Miyuki Yamamoto, Yukiyasu Kamitani.
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.Mesh:
Year: 2009 PMID: 19907352 DOI: 10.1097/WNR.0b013e3283331322
Source DB: PubMed Journal: Neuroreport ISSN: 0959-4965 Impact factor: 1.837