このエントリーをはてなブックマークに追加
ID 48223
本文ファイル
著者
Yamashita, Ayumu
Yahata, Noriaki
Itahashi, Takashi
Lisi, Giuseppe
Yamada, Takashi
Ichikawa, Naho 脳・こころ・感性科学研究センター 広大研究者総覧
Takamura, Masahiro 脳・こころ・感性科学研究センター 広大研究者総覧
Yoshihara, Yujiro
Kunimatsu, Akira
Okada, Naohiro
Yamagata, Hirotaka
Matsuo, Koji
Hashimoto, Ryuichiro
Okada, Go 大学院医系科学研究科(医) 広大研究者総覧
Sakai, Yuki
Morimoto, Jun
Narumoto, Jin
Shimada, Yasuhiro
Kasai, Kiyoto
Kato, Nobumasa
Takahashi, Hidehiko
Okamoto, Yasumasa 大学院医系科学研究科(医) 広大研究者総覧
Tanaka, Saori C.
Kawato, Mitsuo
Yamashita, Okito
Imamizu, Hiroshi
抄録(英)
When collecting large amounts of neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because of the limited capacity of a single site. However, site differences represent a barrier when acquiring multisite neuroimaging data. We utilized a traveling-subject dataset in conjunction with a multisite, multidisorder dataset to demonstrate that site differences are composed of biological sampling bias and engineering measurement bias. The effects on resting-state functional MRI connectivity based on pairwise correlations because of both bias types were greater than or equal to psychiatric disorder differences. Furthermore, our findings indicated that each site can sample only from a subpopulation of participants. This result suggests that it is essential to collect large amounts of neuroimaging data from as many sites as possible to appropriately estimate the distribution of the grand population. Finally, we developed a novel harmonization method that removed only the measurement bias by using a traveling-subject dataset and achieved the reduction of the measurement bias by 29% and improvement of the signal-to-noise ratios by 40%. Our results provide fundamental knowledge regarding site effects, which is important for future research using multisite, multidisorder resting-state functional MRI data.
内容記述
This study was conducted under the contract research Grant Number JP18dm0307008, JP17dm0107044 (“Development of BMI Technologies for Clinical Application” of the Strategic Research Program for Brain Sciences), JP18dm0307002, JP18dm0307004, and JP18dm0307009 supported by the Japan Agency for Medical Research and Development (AMED). This study was also partially supported by the ImPACT Program of the Council for Science, Technology and Innovation (Cabinet Office, Government of Japan). H.I. was partially supported by JSPS KAKENHI 26120002. A.Y. was partially supported by JSPS KAKENHI 15J06788.
掲載誌名
PLoS Biology
17巻
4号
開始ページ
e3000042
出版年月日
2019-04-18
出版者
Public Library of Science
ISSN
1544-9173
1545-7885
出版者DOI
PubMedID
言語
英語
NII資源タイプ
学術雑誌論文
広大資料タイプ
学術雑誌論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
publisher
権利情報
© 2019 Yamashita et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
関連情報URL
部局名
医系科学研究科
その他