TY - JOUR
T1 - Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis
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, Clément M.
AU - Nadkarni, Nachiket Abhay
AU - Hübner, Neele S.
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 - Meyer-Lindenberg, Andreas
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
N1 - Funding Information:
A.M.L. has received consultant fees from Blueprint Partnership, Boehringer Ingelheim, Daimler und Benz Stiftung, Elsevier, F. Hoffmann-La Roche, ICARE Schizophrenia, K. G. Jebsen Foundation, L.E.K. Consulting, Lundbeck International Foundation (LINF), R. Adamczak, Roche Pharma, Science Foundation, Synapsis Foundation–Alzheimer Research Switzerland, and System Analytics and has received lectures including travel fees from Boehringer Ingelheim, Fama Public Relations, Institut d’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Janssen-Cilag, Klinikum Christophsbad, Göppingen, Lilly Deutschland, Luzerner Psychiatrie, LVR Klinikum Düsseldorf, LWL Psychiatrie Verbund Westfalen-Lippe, Otsuka Pharmaceuticals, Reunions i Ciencia S. L., Spanish Society of Psychiatry, Südwestrundfunk Fernsehen, Stern TV, and Vitos Klinikum Kurhessen.
Funding Information:
This work was supported by the Singapore Bioimaging Consortium (SBIC) , A*STAR, Singapore . AG acknowledges funding from the Simons Foundation ( SFARI 314688 and 400101 ), the Brain and Behavior Foundation (2017 NARSAD independent Investigator Grant) and the European Research Council (ERC, G.A. 802371 ). This work was also supported by the JSPS KAKENHI Grant Number 16K07032 to NT, 16K10233 to NY, and 18K18375 to CS, by Brain/MINDS, the Strategic Research Program for Brain Sciences (SRPBS) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (MEXT) and Japan Agency for Medical Research and Development (AMED) to NT and HO, by AMED under Grant Number JP19dm0307007h0002 and JP19dm0307008h0002 to NY, JP19dm0307026h0002 to CS, and 17dm0107066h to IA, by COI program by Japan Science and Technology Agency (JST) to IA, and by ERATO JPMJER1801 by JST to NY. It was further supported as part of the Excellence Cluster ‘BrainLinks-BrainTools’ by the German Research Foundation , grant EXC1086 . AH acknowledges funding from the German BMBF (NeuroImpa, 01EC1403C and NeuroRad 02NUK034D ). MD acknowledges funding from France-Alzheimer Association , Plan Alzheimer Foundation and the French Public Investment Bank ’s “ROMANE” program. This work was also supported by the Fund for Scientific Research Flanders (FWO) (grant agreements G057615N and 12S4815N - AvL ), the Stichting Alzheimer Onderzoek (SAO-FRA, grant agreement 13026-AvL ), the interdisciplinary PhD grant BOF DOCPRO 2014 - MV ). NG acknowledges NEWMEDS project funded from the Innovative Medicine Initiative Joint Undertaking under Grant Agreement no. 115008 of which resources are composed of European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme ( FP7/2007-2013 ); as well as funding from the German Research Foundation (Deutsche Forschungsgemeinschaft) : DFG SA 1869/15-1 and DFG GA 2109/2-1 . The authors would like to thank Itamar Kahn, Eyal Bergmann and Daniel Gutierrez-Barragan for critically reading the manuscript. Appendix A
Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2020/1/15
Y1 - 2020/1/15
N2 - 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.
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 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.
KW - Connectome
KW - Default-mode network
KW - Functional connectivity
KW - ICA
KW - Seed-based
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U2 - 10.1016/j.neuroimage.2019.116278
DO - 10.1016/j.neuroimage.2019.116278
M3 - Article
C2 - 31614221
AN - SCOPUS:85073682087
SN - 1053-8119
VL - 205
JO - NeuroImage
JF - NeuroImage
M1 - 116278
ER -