A small number of abnormal brain connections predicts adult autism spectrum disorder

Nature Communications

Volumn 7, Issue , 2016, Pages

  Yahata, Noriaki ^a,b,c   Morimoto, Jun ^c   Hashimoto, Ryuichiro ^c,d,e   Lisi, Giuseppe ^c   Shibata, Kazuhisa ^c,f   Kawakubo, Yuki ^a   Kuwabara, Hitoshi ^g   Kuroda, Miho ^a,h   Yamada, Takashi ^c,d   Megumi, Fukuda ^c,i   Imamizu, Hiroshi ^c,g   Náñez, José E ^j   Takahashi, Hidehiko ^k   Okamoto, Yasumasa ^l   Kasai, Kiyoto ^a   Kato, Nobumasa ^d   Sasaki, Yuka ^c,f   Watanabe, Takeo ^c,f   Kawato, Mitsuo ^c  

^a UNIVERSITY OF TOKYO   (Japan)

^b NATIONAL INSTITUTE OF RADIOLOGICAL SCIENCES   (Japan)

^c ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

^d Showa University Karasuyama Hospital   (Japan)

^e TOKYO METROPOLITAN UNIVERSITY   (Japan)

^f BROWN UNIVERSITY   (United States)

^g UNIVERSITY OF TOKYO   (Japan)

^h FUKUSHIMA UNIVERSITY   (Japan)

ⁱ UNIVERSITY COLLEGE LONDON   (United Kingdom)

^j ARIZONA STATE UNIVERSITY   (United States)

^k KYOTO UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

^l HIROSHIMA UNIVERSITY   (Japan)

more..

Author keywords

[No Author keywords available]

Indexed keywords

ABNORMALITY; ALGORITHM; BRAIN; COHORT ANALYSIS; DEMOGRAPHIC SURVEY; MACHINE LEARNING; NERVOUS SYSTEM DISORDER; NEUROLOGY; PREDICTION;

ADULT; ALGORITHM; ARTICLE; ATTENTION DEFICIT DISORDER; AUTISM; BRAIN DEVELOPMENT; BRAIN REGION; CLASSIFIER; COHORT ANALYSIS; CONNECTOME; CONTROLLED STUDY; FEMALE; HUMAN; JAPAN; JAPANESE (PEOPLE); MACHINE LEARNING; MAJOR CLINICAL STUDY; MAJOR DEPRESSION; MALE; MEASUREMENT ACCURACY; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTION; PREDICTIVE VALUE; SCHIZOPHRENIA; UNITED STATES; VALIDATION STUDY; ADOLESCENT; AUTISM SPECTRUM DISORDER; BIOLOGICAL MODEL; BRAIN; NERVE CELL NETWORK; NERVE TRACT; PATHOPHYSIOLOGY; PROGNOSIS; YOUNG ADULT;

JAPAN; UNITED STATES;

ADOLESCENT; ADULT; ALGORITHMS; AUTISM SPECTRUM DISORDER; BRAIN; FEMALE; HUMANS; MALE; MODELS, NEUROLOGICAL; NERVE NET; NEURAL PATHWAYS; PROGNOSIS; YOUNG ADULT;

EID: 84964221788     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms11254     Document Type: Article

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