抓取与放置物体共享皮层-小脑机制,但神经动态不同
Reach plans for grasping vs. placing objects evoke different neural dynamics within a shared cortico-cerebellar mechanism.
一项尚未完成同行评审的bioRxiv预印本报告,31名参与者交替完成对三维物体的抓取与放置动作,高密度EEG与运动追踪显示两者共享皮层-小脑机制但时空动态不同。依据摘要,放置动作启动更快、执行更慢且终点朝向精度更高;两者均出现从准备期后部负波/前部正波到执行期后部正波/前部负波的极性反转,该模式在放置准备期增强、执行期延长。SVM解码显示任务特异性信息主要编码在6 Hz以下低频EEG中。
Many reach studies treat grasping as the endpoint of a reach, but grasping often initiates a sequence of actions, ending with placing the object. Grasping and placing both require object-specific encoding, but placing has different computational demands, introduced by the intent, sensory feedback, and tolerance for spatial error when alignment is required. Recent neuroimaging work suggests that object placement shares similar cortico-cerebellar networks with grasp, with modest increases in network segregation and cerebellar activity. Here, we ask whether Grasp and Place are better distinguished by their spatiotemporal dynamics in both behaviour and scalp-recorded EEG activity. Using high-density EEG and motion tracking, 31 participants performed alternating Grasp/Place movements of a 3D object from/toward an oriented target/template. Place movements were initiated faster but executed more slowly and with greater endpoint-orientation precision than Grasp, indicating distinct control strategies. ERP and microstate analyses revealed that Grasp and Place shared a peri-movement polarity switch, from posterior negativity/frontal positivity during preparation to posterior positivity/frontal negativity during execution. This shared pattern was amplified during Place preparation and prolonged during Place execution, with stronger expression of preparatory medial frontal/cerebellar and execution-related posterior/cerebellar microstate dynamics. Finally, SVM decoding indicated that task-specific information was primarily encoded in low-frequency EEG activity (below 6 Hz). These results confirm that grasping and placing recruit similar cortico-cerebellar mechanisms, yet different spatiotemporal dynamics are employed to support the distinct computational demands of these behaviours.
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来源:bioRxiv · Neuroscience · biorxiv.org