End-point robot for the discovery of the neural correlates of memory consolidation in the human brain

基础研究有助于理解学习是如何改变大脑功能和结构的。目前还不清楚大脑中哪些区域是学习动作或存储这些记忆的关键。在某种程度上，这种知识的缺乏源于没有完全理解大脑在练习运动后如何随着时间的变化而变化。过去的研究提供了使用磁共振成像或MRI进行新运动后大脑功能可能发生变化的快照。但由于与核磁共振相关的时间延迟，这些信息不能解释大脑可能如何实时变化。目前，我们能够使用脑电(EEG)和非侵入性脑刺激(经颅磁刺激[TMS])同时测量和改变与运动学习相关的大脑活动模式。这一系列研究成功的关键是能够实时精确地控制和索引人类的运动。因此，本提案针对的是终端机器人KINARM，它能够测量双臂在3维空间中的运动和力，并通过力马达阻力操纵运动轨迹。这款机器人将能够在运动学习期间精确测量手臂的运动，并与我们现有的大脑测量(例如EEG)和脑刺激(例如TMS)系统相结合，促进对大脑功能如何支持新运动记忆形成的全面研究。

Basic research helps in the understanding of how learning changes brain function and structure. At present it is not clear which brain regions are key for learning movements or for storing these memories. In part this lack of knowledge stems from not fully understanding how the brain changes with time after a movement is practiced. Past work has provided snapshots of how brain function may change after a new movement is practiced using magnetic resonance imaging or MRI. But because of the time delays associated with MRI this information does not explain how the brain might change in real time. At present we are capable of both measuring and altering patterns of brain activity associated with motor learning using electroencephalography (EEG) and non-invasive brain stimulation (transcranial magnetic stimulation [TMS]) simultaneously. Critical for the success of this line of research is the ability to precisely control and index human movement in real time. Thus, the present proposal is for an End-Point robot, the KINARM, which enables the measurement of movement and force of both arms in 3-dimensional space as well as the manipulation of trajectories of movement via force motor resistance. This robot will allow precise measurement of arm movement during motor learning, and in combination with our existing brain measurement (e.g., EEG) and brain stimulation (e.g., TMS) systems, facilitate the comprehensive study of how brain function supports the formation of new motor memories.