| Item type |
デフォルトアイテムタイプ_（フル）(1) |
| 公開日 |
2023-03-18 |
| タイトル |
|
|
タイトル |
Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias |
|
言語 |
en |
| 作成者 |
Yamashita, Ayumu
Yahata, Noriaki
Itahashi, Takashi
Lisi, Giuseppe
Yamada, Takashi
Ichikawa, Naho
Takamura, Masahiro
Yoshihara, Yujiro
Kunimatsu, Akira
Okada, Naohiro
Yamagata, Hirotaka
Matsuo, Koji
Hashimoto, Ryuichiro
Okada, Go
Sakai, Yuki
Morimoto, Jun
Narumoto, Jin
Shimada, Yasuhiro
Kasai, Kiyoto
Kato, Nobumasa
Takahashi, Hidehiko
Okamoto, Yasumasa
Tanaka, Saori C.
Kawato, Mitsuo
Yamashita, Okito
Imamizu, Hiroshi
|
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利情報 |
|
|
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. |
| 内容記述 |
|
|
内容記述 |
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. |
|
言語 |
en |
| 内容記述 |
|
|
内容記述タイプ |
Other |
|
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. |
| 出版者 |
|
|
出版者 |
Public Library of Science |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 関連情報 |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
10.1371/journal.pbio.3000042 |
| 関連情報 |
|
|
|
識別子タイプ |
PMID |
|
|
関連識別子 |
30998673 |
| 関連情報 |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1371/journal.pbio.3000042 |
| 収録物識別子 |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1544-9173 |
| 収録物識別子 |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1545-7885 |
| 開始ページ |
|
|
開始ページ |
e3000042 |
| 書誌情報 |
PLoS Biology
PLoS Biology
巻 17,
号 4,
p. e3000042,
発行日 2019-04-18
|
| 旧ID |
48223 |
PLoSBiol_17_e3000042.pdf (4.0 MB)
