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Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Authors :
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
Source :
NeuroImage, Vol 205, Iss , Pp 116278- (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

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.

Details

Language :
English
ISSN :
10959572
Volume :
205
Issue :
116278-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.0f102b5e81144188c9903975357a3a8
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2019.116278