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

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 SauerDisha 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

Research output: Contribution to journalArticle

9 Citations (Scopus)

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.

Original languageEnglish
Article number116278
JournalNeuroImage
Volume205
DOIs
Publication statusPublished - 2020 Jan 15

Keywords

  • Connectome
  • Default-mode network
  • Functional connectivity
  • ICA
  • Seed-based

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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