Nature Communications (Apr 2016)
A small number of abnormal brain connections predicts adult autism spectrum disorder
- Noriaki Yahata,
- Jun Morimoto,
- Ryuichiro Hashimoto,
- Giuseppe Lisi,
- Kazuhisa Shibata,
- Yuki Kawakubo,
- Hitoshi Kuwabara,
- Miho Kuroda,
- Takashi Yamada,
- Fukuda Megumi,
- Hiroshi Imamizu,
- José E. Náñez Sr,
- Hidehiko Takahashi,
- Yasumasa Okamoto,
- Kiyoto Kasai,
- Nobumasa Kato,
- Yuka Sasaki,
- Takeo Watanabe,
- Mitsuo Kawato
Affiliations
- Noriaki Yahata
- Department of Youth Mental Health, Graduate School of Medicine, The University of Tokyo
- Jun Morimoto
- Department of Brain Robot Interface, ATR Brain Information Communication Research Laboratory Group
- Ryuichiro Hashimoto
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- Giuseppe Lisi
- Department of Brain Robot Interface, ATR Brain Information Communication Research Laboratory Group
- Kazuhisa Shibata
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- Yuki Kawakubo
- Department of Child Neuropsychiatry, Graduate School of Medicine, The University of Tokyo
- Hitoshi Kuwabara
- Disability Services Office, The University of Tokyo
- Miho Kuroda
- Department of Child Neuropsychiatry, Graduate School of Medicine, The University of Tokyo
- Takashi Yamada
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- Fukuda Megumi
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- Hiroshi Imamizu
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- José E. Náñez Sr
- School of Social and Behavioral Sciences, Arizona State University
- Hidehiko Takahashi
- Department of Psychiatry, Kyoto University Graduate School of Medicine
- Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University
- Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo
- Nobumasa Kato
- Medical Institute of Developmental Disabilities Research, Showa University Karasuyama Hospital
- Yuka Sasaki
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- Takeo Watanabe
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- Mitsuo Kawato
- Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group
- DOI
- https://doi.org/10.1038/ncomms11254
- Journal volume & issue
-
Vol. 7,
no. 1
pp. 1 – 12
Abstract
Autism spectrum disorder (ASD) is manifested by subtle but significant changes in the brain. Here, Yahata and colleagues devise a novel machine learning algorithm and develop a reliable ASD classifier based on brain functional connectivity, with which they quantitatively measure neuroimaging dimensions between ASD and other mental disorders.
