Neural signatures of online and offline motor learning: An ALE meta-analysis

• Published in: Imaging neuroscience (Cambridge, Mass.) Mass.), 2025-01, Vol.3
• Main Authors: Byczynski, Gabriel, Arulchelvan, Elva, Grootjans, Yvette, Scarlat, Iulia-Mara, Brady, Simone, Kamdar, Sophie, Vanneste, Sven
• Format: Article
• Language: English
• Subjects: fMRI; meta-analysis; motor learning; motor sequence; motor task; offline learning; online learning; sequence learning; visuomotor learning
• ISSN: 2837-6056; 2837-6056
• DOI: 10.1162/imag_a_00457

Neural activation patterns underlying motor learning that are captured using functional imaging can only reflect the patterns occurring at a given moment. Motor learning is known to comprise many processes which are variably biologically or temporally distinct. In order to improve the understanding of how regional activation patterns may vary across different mechanisms of motor learning, we performed an ALE meta-analysis of imaging studies that directly compares online and offline motor learning. Using coordinate-based meta-analysis methods and independent review, 1777 studies were returned from 3 databases. Thirty-eight studies investigating motor task learning met the inclusion criteria, were allocated as either online or offline learning based on their scanning placement, and revealed both unique and overlapping regional activation/deactivation patterns. We identify activation changes in regions that are consistent for online learning and offline learning. Our findings concur with those of previous meta-analyses investigating online motor learning, and find support for previous theories surrounding the networks involved in consolidation and offline processes in motor learning. Shared activation between online and offline motor learning was found in the supplemental motor area and somatosensory cortex, highlighting regions which are continually involved in both processes, and identifying those which may be differentially modulated to alter motor learning outcomes.