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Title: Head motion during fMRI tasks is reduced in children and adults if participants take breaks
Authors: Meissner, Tobias W
Walbrin, Jon 
Nordt, Marisa
Koldewyn, Kami
Weigelt, Sarah
Keywords: Movement; Data quality; Pediatric neuroimaging; Mock scanner training; Study design; Development
Issue Date: Aug-2020
Publisher: Elsevier
Project: PhD scholarship of the Konrad- Adenauer-Foundation and an International Realization Budget of the Ruhr University Bochum Research School PLUS through funds of the German Research Foundation’s Universities Excellence Initiative (GSC 98/3) to TWM 
Bangor School of Psychology funded PhD Scholarship 
PhD scholarship of the German Academic Scholarship Foundation 
ERC Starting Grant (Becoming Social, 716974) 
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project number WE 5802/1-1 and project number 316803389 – SFB 1280 project A16) 
Mercator Research Center Ruhr (AN-2014-0056) 
Volkswagen Foundation (Lichtenberg Professorship, 97 079) 
Serial title, monograph or event: Developmental Cognitive Neuroscience
Volume: 44
Abstract: Head motion remains a challenging confound in functional magnetic resonance imaging (fMRI) studies of both children and adults. Most pediatric neuroimaging labs have developed experience-based, child-friendly standards concerning e.g. the maximum length of a session or the time between mock scanner training and actual scanning. However, it is unclear which factors of child-friendly neuroimaging approaches are effective in reducing head motion. Here, we investigate three main factors including (i) time lag of mock scanner training to the actual scan, (ii) prior scan time, and (iii) task engagement in a dataset of 77 children (aged 6-13) and 64 adults (aged 18-35) using a multilevel modeling approach. In children, distributing fMRI data acquisition across multiple same-day sessions reduces head motion. In adults, motion is reduced after inside-scanner breaks. Despite these positive effects of splitting up data acquisition, motion increases over the course of a study as well as over the course of a run in both children and adults. Our results suggest that splitting up fMRI data acquisition is an effective tool to reduce head motion in general. At the same time, different ways of splitting up data acquisition benefit children and adults.
ISSN: 18789293
DOI: 10.1016/j.dcn.2020.100803
Rights: openAccess
Appears in Collections:FPCEUC - Artigos em Revistas Internacionais

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