A quantitative meta-analysis and review of motor learning in the human brain.
A quantitative meta-analysis and review of motor learning in the human brain.
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DOI：
10.1016/j.neuroimage.2012.11.020
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发表时间：
2013-02-15
期刊：
影响因子：
5.7
通讯作者：
Eickhoff SB
中科院分区：
文献类型：
--
作者：
Hardwick RM;Rottschy C;Miall RC;Eickhoff SB
神经影像学研究提高了我们对哪些大脑结构参与运动学习的理解。尽管如此，问题仍然存在的领域，有助于一贯跨范式与不同的任务要求。例如，感觉运动任务专注于学习新的运动学和动力学，而串行响应时间任务（SRTT）的变体专注于序列学习。这些不同的任务需求可能会在潜在一致的核心网络之上引发可量化的不同神经活动模式。当前的研究使用激活可能性估计（ALE）荟萃分析在70个运动学习实验中发现了一致的激活。对所有任务的全局分析显示，双侧皮质-皮质下网络始终是跨任务运动学习的基础。在背侧运动前皮质、辅助运动皮质、初级运动皮质、初级躯体感觉皮质、上级顶叶、丘脑、壳核和小脑中发现了会聚激活。这些激活在分离感觉运动任务和SRTT变体的任务特异性分析中大致一致。对比分析表明，在基底神经节和小脑的活动显着更强的感觉运动任务，而在皮层结构和丘脑的活动显着更强的SRTT变体。附加的连接分析，然后表明，左背运动前皮层被激活在所有的分析考虑，即使在控制潜在的运动混淆。左侧背侧运动前皮层的高度一致激活表明它是运动学习网络中的关键节点。采用激活似然估计法对70个运动学习实验进行分析。神经网络分析揭示了运动学习的皮质-皮质下网络。在具有不同任务需求的亚组中发现了一致的激活。左侧背侧运动前区皮层是运动学习的关键结构。
Neuroimaging studies have improved our understanding of which brain structures are involved in motor learning. Despite this, questions remain regarding the areas that contribute consistently across paradigms with different task demands. For instance, sensorimotor tasks focus on learning novel movement kinematics and dynamics, while serial response time task (SRTT) variants focus on sequence learning. These differing task demands are likely to elicit quantifiably different patterns of neural activity on top of a potentially consistent core network. The current study identified consistent activations across 70 motor learning experiments using activation likelihood estimation (ALE) meta-analysis. A global analysis of all tasks revealed a bilateral cortical–subcortical network consistently underlying motor learning across tasks. Converging activations were revealed in the dorsal premotor cortex, supplementary motor cortex, primary motor cortex, primary somatosensory cortex, superior parietal lobule, thalamus, putamen and cerebellum. These activations were broadly consistent across task specific analyses that separated sensorimotor tasks and SRTT variants. Contrast analysis indicated that activity in the basal ganglia and cerebellum was significantly stronger for sensorimotor tasks, while activity in cortical structures and the thalamus was significantly stronger for SRTT variants. Additional conjunction analyses then indicated that the left dorsal premotor cortex was activated across all analyses considered, even when controlling for potential motor confounds. The highly consistent activation of the left dorsal premotor cortex suggests it is a critical node in the motor learning network. ► Activation likelihood estimation was used to analyze 70 motor learning experiments. ► Analysis revealed a cortico-subcortical network for motor learning. ► Consistent activations were found across subgroups with differing task demands. ► Left dorsal premotor cortex was identified as a key structure in motor learning.
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