Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis
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
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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Neuroimage. - 205 (2020) , 116278, ISSN: 1095-9572
- Ereignis
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Veröffentlichung
- (wo)
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Freiburg
- (wer)
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Universität
- (wann)
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2020
- Urheber
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Grandjean, Joanes
Bienert, Thomas
Hübner, Neele
Karataş, Meltem
Mechling, Anna
Elverfeldt, Dominik von
Gozzi, Alessandro
- DOI
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10.1016/j.neuroimage.2019.116278
- URN
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urn:nbn:de:bsz:25-freidok-1552268
- Rechteinformation
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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25.03.2025, 13:50 MEZ
Datenpartner
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Beteiligte
- Grandjean, Joanes
- Bienert, Thomas
- Hübner, Neele
- Karataş, Meltem
- Mechling, Anna
- Elverfeldt, Dominik von
- Gozzi, Alessandro
- Universität
Entstanden
- 2020
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