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タイトル: A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity
著者: Yamashita, Masahiro
Yoshihara, Yujiro
Hashimoto, Ryuichiro
Yahata, Noriaki
Ichikawa, Naho
Sakai, Yuki
Yamada, Takashi
Matsukawa, Noriko
Okada, Go
Tanaka, Saori C
Kasai, Kiyoto
Kato, Nobumasa
Okamoto, Yasumasa
Seymour, Ben
Takahashi, Hidehiko
Kawato, Mitsuo
Imamizu, Hiroshi
著者名の別形: 山下, 真寛
吉原, 雄二郎
橋本, 龍一郎
八幡, 憲明
市川, 奈穂
酒井, 雄希
山田, 貴志
松河, 理子
岡田, 剛
田中, 沙織
笠井, 清登
加藤, 進昌
岡本, 泰昌
髙橋, 英彦
川人, 光男
今水, 寛
発行日: 10-Dec-2018
出版者: eLife Sciences Publications, Ltd
誌名: eLife
巻: 7
論文番号: e38844
抄録: Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter three-back task performance in healthy participants, using resting state functional magnetic resonance imaging (rs-fMRI). This normative model was applied to independent participants (N = 965) including four psychiatric diagnoses. Individual’s predicted WMA significantly correlated with a measured WMA in both healthy population and schizophrenia. Our predicted effect size estimates on WMA impairment were comparable to previous meta-analysis results. These results suggest a general association between brain connectivity and working memory ability applicable commonly to health and psychiatric diseases.
記述: 複数の精神疾患における記憶力を共通のモデルで予測することに成功 --疾患に共通する認知機能低下のメカニズム解明に大きく前進--. 京都大学プレスリリース. 2019-01-11.
著作権等: © 2018, Yamashita et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
URI: http://hdl.handle.net/2433/236017
DOI(出版社版): 10.7554/eLife.38844
PubMed ID: 30526859
関連リンク: http://www.kyoto-u.ac.jp/ja/research/research_results/2018/190108_5%2Chtml
出現コレクション:学術雑誌掲載論文等

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