Byczynski Gabriel, Arulchelvan Elva, Grootjans Yvette, Scarlat Iulia-Mara, Brady Simone, Kamdar Sophie, Vanneste Sven
School of Psychology, Trinity College Dublin, Dublin, Ireland.
Lab for Clinical & Integrative Neuroscience, Trinity Institute for Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland.
Imaging Neurosci (Camb). 2025 Jan 24;3. doi: 10.1162/imag_a_00457. eCollection 2025.
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.
利用功能成像捕捉到的运动学习背后的神经激活模式仅能反映给定时刻出现的模式。已知运动学习包含许多在生物学或时间上各不相同的过程。为了更好地理解区域激活模式在不同运动学习机制中可能如何变化，我们对直接比较在线和离线运动学习的成像研究进行了激活可能性估计（ALE）元分析。使用基于坐标的元分析方法和独立评审，从3个数据库中检索到1777项研究。38项调查运动任务学习的研究符合纳入标准，根据其扫描位置被分配为在线学习或离线学习，并揭示了独特和重叠的区域激活/失活模式。我们确定了在线学习和离线学习中一致的区域激活变化。我们的研究结果与之前调查在线运动学习的元分析结果一致，并为之前围绕运动学习中巩固和离线过程所涉及网络的理论提供了支持。在线和离线运动学习之间的共同激活出现在辅助运动区和体感皮层，突出了持续参与这两个过程的区域，并确定了那些可能被不同调节以改变运动学习结果的区域。
