| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2024-04-30 |
| タイトル |
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タイトル |
Aberrant Large-Scale Network Interactions Across Psychiatric Disorders Revealed by Large-Sample Multi-Site Resting-State Functional Magnetic Resonance Imaging Datasets |
| 言語 |
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言語 |
eng |
| キーワード |
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主題Scheme |
Other |
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主題 |
dynamic causal modeling |
| キーワード |
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主題Scheme |
Other |
|
主題 |
schizophrenia |
| キーワード |
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主題Scheme |
Other |
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主題 |
major depressive disorder |
| キーワード |
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主題Scheme |
Other |
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主題 |
bipolar disorder |
| 資源タイプ |
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資源タイプ |
journal article |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
Ishida, Takuya
Nakamura, Yuko
田中, 沙織
Mitsuyama, Yuki
Yokoyama, Satoshi
Shinzato, Hotaka
Itai, Eri
Okada, Go
Kobayashi, Yuko
Kawashima, Takahiko
Miyata, Jun
Yoshihara, Yujiro
Takahashi, Hidehiko
Morita, Susumu
Kawakami, Shintaro
Abe, Osamu
Okada, Naohiro
Kunimatsu, Akira
Yamashita, Ayumu
Yamashita, Okito
Imamizu, Hiroshi
Morimoto, Jun
Okamoto, Yasumasa
Murai, Toshiya
Kasai, Kiyoto
Kawato, Mitsuo
Koike, Shinsuke
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Background and Hypothesis
Dynamics of the distributed sets of functionally synchronized brain regions, known as large-scale networks, are essential for the emotional state and cognitive processes. However, few studies were performed to elucidate the aberrant dynamics across the large-scale networks across multiple psychiatric disorders. In this paper, we aimed to investigate dynamic aspects of the aberrancy of the causal connections among the large-scale networks of the multiple psychiatric disorders.
Study Design
We applied dynamic causal modeling (DCM) to the large-sample multi-site dataset with 739 participants from 4 imaging sites including 4 different groups, healthy controls, schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), to compare the causal relationships among the large-scale networks, including visual network, somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network, and default mode network.
Study Results
DCM showed that the decreased self-inhibitory connection of LIN was the common aberrant connection pattern across psychiatry disorders. Furthermore, increased causal connections from LIN to multiple networks, aberrant self-inhibitory connections of DAN and SMN, and increased self-inhibitory connection of SAN were disorder-specific patterns for SCZ, MDD, and BD, respectively.
Conclusions
DCM revealed that LIN was the core abnormal network common to psychiatric disorders. Furthermore, DCM showed disorder-specific abnormal patterns of causal connections across the 7 networks. Our findings suggested that aberrant dynamics among the large-scale networks could be a key biomarker for these transdiagnostic psychiatric disorders. |
| 書誌情報 |
en : Schizophrenia Bulletin
巻 49,
号 4,
p. 933-943,
発行日 2023-03-09
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| 出版者 |
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出版者 |
Oxford University Press |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
1745-1701 |
| 出版者版DOI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1093/schbul/sbad022 |
| 出版者版URI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
URI |
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関連識別子 |
https://academic.oup.com/schizophreniabulletin/article/49/4/933/7074397 |
| 権利 |
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権利情報Resource |
https://creativecommons.org/licenses/by-nc/4.0/ |
|
権利情報 |
$00A9 The Author(s) 2023. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
| 著者版フラグ |
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出版タイプ |
NA |
