作者
Joanes Grandjean, Carola Canella, Cynthia Anckaerts, Gülebru Ayrancı, Salma Bougacha, Thomas Bienert, David Buehlmann, Ludovico Coletta, Daniel Gallino, Natalia Gass, Clément M Garin, Nachiket Abhay Nadkarni, Neele S Hübner, Meltem Karatas, Yuji Komaki, Silke Kreitz, Francesca Mandino, Anna E Mechling, Chika Sato, Katja Sauer, Disha Shah, Sandra Strobelt, Norio Takata, Isabel Wank, Tong Wu, Noriaki Yahata, Ling Yun Yeow, Yohan Yee, Ichio Aoki, M Mallar Chakravarty, Wei-Tang Chang, Marc Dhenain, Dominik von Elverfeldt, Laura-Adela Harsan, Andreas Hess, Tianzi Jiang, Georgios A Keliris, Jason P Lerch, Andreas Meyer-Lindenberg, Hideyuki Okano, Markus Rudin, Alexander Sartorius, Annemie Van der Linden, Marleen Verhoye, Wolfgang Weber-Fahr, Nicole Wenderoth, Valerio Zerbi, Alessandro Gozzi
发表日期
2020/1/15
期刊
Neuroimage
卷号
205
页码范围
116278
出版商
Academic Press
简介
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 …
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J Grandjean, C Canella, C Anckaerts, G Ayrancı… - Neuroimage, 2020
