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Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.
https://repo.qst.go.jp/records/77181
https://repo.qst.go.jp/records/7718123968d2e-db30-4736-ade1-985918a177b7
| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2019-10-21 | |||||
| タイトル | ||||||
| タイトル | Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis. | |||||
| 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 | |||||
| アクセス権 | ||||||
| アクセス権 | metadata only access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
| 著者 |
Grandjean, Joanes
× Grandjean, Joanes× Canella, Carola× Anckaerts, Cynthia× Gülebru, Ayrancı× Bougacha, Salma× Bienert, Thomas× Buehlmann, David× Coletta, Ludovico× Gallino, Daniel× Gass, Natalia× Clément, M Garin× Abhay Nadkarni, Nachiket× Neele, S Hübner× Karatas, Meltem× Komaki, Yuji× Kreitz, Silke× Mandino, Francesca× E Mechling, Anna× Sato, Chika× Sauer, Katja× Shah, Disha× Strobelt, Sandra× Takata, Norio× Wank, Isabel× Wu, Tong× Yahata, Noriaki× Yun Yeow, Ling× Yee, Yohan× Aoki, Ichio× Mallar Chakravarty, M× Wei-Tang, Chang× Dhenain, Marc× von Elverfeldt, Dominik× Laura-Adela, Harsan× Hess, Andreas× Jiang, Tianzi× A Keliris, Georgios× P Lerch, Jason× Andreas, Meyer-Lindenberg× Okano, Hideyuki× Rudin, Markus× Sartorius, Alexander× Van der Linden, Annemie× Verhoye, Marleen× Wolfgang, Weber-Fahr× Wenderoth, Nicole× Zerbi, Valerio× Gozzi, Alessandro× Chika, Sato× Noriaki, Yahata× Ichio, Aoki |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations. | |||||
| 書誌情報 |
NeuroImage 巻 205, p. 116278, 発行日 2020-01 |
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| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 1053-8119 | |||||
| PubMed番号 | ||||||
| 識別子タイプ | PMID | |||||
| 関連識別子 | 31614221 | |||||
| DOI | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.1016/j.neuroimage.2019.116278 | |||||
