PT  - JOURNAL ARTICLE
AU  - Grandjean, Joanes
AU  - Canella, Carola
AU  - Anckaerts, Cynthia
AU  - Ayrancı, Gülebru
AU  - Bougacha, Salma
AU  - Bienert, Thomas
AU  - Buehlmann, David
AU  - Coletta, Ludovico
AU  - Gallino, Daniel
AU  - Gass, Natalia
AU  - Garin, Clement M.
AU  - Nadkarni, Nachiket Abhay
AU  - Hübner, Neele
AU  - Karatas, Meltem
AU  - Komaki, Yuji
AU  - Kreitz, Silke
AU  - Mandino, Francesca
AU  - Mechling, Anna E.
AU  - Sato, Chika
AU  - Sauer, Katja
AU  - Shah, Disha
AU  - Strobelt, Sandra
AU  - Takata, Norio
AU  - Wank, Isabel
AU  - Wu, Tong
AU  - Yahata, Noriaki
AU  - Yeow, Ling Yun
AU  - Yee, Yohan
AU  - Aoki, Ichio
AU  - Chakravarty, M. Mallar
AU  - Chang, Wei-Tang
AU  - Dhenain, Marc
AU  - von Elverfeldt, Dominik
AU  - Harsan, Laura-Adela
AU  - Hess, Andreas
AU  - Jiang, Tianzi
AU  - Keliris, Georgios A
AU  - Lerch, Jason P.
AU  - Okano, Hideyuki
AU  - Rudin, Markus
AU  - Sartorius, Alexander
AU  - Van der Linden, Annemie
AU  - Verhoye, Marleen
AU  - Weber-Fahr, Wolfgang
AU  - Wenderoth, Nicole
AU  - Zerbi, Valerio
AU  - Gozzi, Alessandro
TI  - Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis
AID  - 10.1101/541060
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 541060
4099  - http://biorxiv.org/content/early/2019/02/08/541060.short
4100  - http://biorxiv.org/content/early/2019/02/08/541060.full
AB  - 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 world-wide. 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 murine 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. 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.