Static and Dynamic Organization of Primate Motor Cortex

描述（由申请人提供）：我研究的长期目标是(1)了解皮层网络如何灵活地从感觉和认知信号中计算动作，(2)利用这些知识开发脑机接口（bci），恢复瘫痪患者执行有用动作的能力。该项目的具体目标是确定运动前皮层和运动皮层神经元的相互连接网络如何从不同类型的信号中计算、到达和掌握动作。额叶皮层的背侧前运动区（PMd）和腹侧前运动区（PMv）似乎代表了不同的处理流，这些处理流汇聚在初级运动皮层（MI），在初级运动皮层中，伸手和抓握是统一的。这种相互作用的电路似乎是通过动态地将各种线索与特定的手臂和手的动作联系起来，从而产生动作命令，但对处理的信号的性质、执行的感觉运动转换的类型或它们在手臂和手的运动中的作用进行了冲突研究。本研究介绍了几种新的方法来理解这些皮质网络的集体动力学如何提供一个灵活的基底来连接不同的信号和行为。长期植入PMv， PMd和MI的多电极阵列和全上肢运动捕捉将用于同时记录神经元尖峰（192个通道）并测量猴子在不同环境下执行任务时手臂，手腕和手指的动作。通过训练猴子执行四项不同的任务来改变环境，这些任务用于指导手臂动作的信号不同：(1)使用持续的感官反馈来捕捉摆动的物体，(2)根据视觉线索规划不同的抓取类型，(3)规划不同的到达目标（点或抓取），(3)做出感知判断来确定抓取类型。上下文相关的变化将通过同时记录每个任务的PMv、PMd和MI中的单细胞反应和群体表征（SA1）以及网络功能连接（SA2）来测量。在单个会话中记录两个或多个上下文将允许直接比较相同的集合，以确定上下文如何修改单个神经元中的编码，种群模型如何跨上下文进行推广，以及网络如何组合各种信号以实现协调到达和掌握。我们将通过比较PMv和PMd区域之间的神经编码特征和上下文敏感性来解决PMv和PMd形成独立信息处理通道的假设。最后，SA3将通过使用新兴的、高选择性的光遗传方法或电刺激破坏这些网络中的处理来测试特定感觉运动计算的需求。这些研究将揭示皮层回路执行感觉运动转换和灵活连接神经元组以产生自愿行为的机制。此外，它们将有助于确定运动前区域以及MI中可用的信号是否可以为BCI命令信号提供有用的来源。这样的信号可以让瘫痪的人重新获得复杂的功能，比如通过机械肢体，可以在各种情况下有效地操作。

DESCRIPTION (provided by applicant): The long-term goals of my research are (1) to understand how cortical networks flexibly compute actions from sensory and cognitive signals and (2) to use this knowledge to develop brain computer interfaces (BCIs) that restore the ability to perform useful actions to humans with paralysis. The specific objective of this project is to determine how interconnected networks of neurons in the premotor and motor cortex compute reach and grasp actions from different types of signals. Dorsal premotor (PMd) and ventral premotor (PMv) areas of frontal cortex appear to represent separate processing streams that converge on primary motor cortex (MI) where reach and grasp are unified. This interacting circuit appears to generate commands for actions by dynamically linking various cues to specific arm and hand actions, but studies conflict on the nature of the signals processed, the types of sensorimotor transforms performed, or their roles in arm and hand movement. The present study introduces several new approaches to understand how the collective dynamics of these cortical networks provide a flexible substrate to link different signals and actions. Chronically implanted multi-electrode arrays implanted in PMv, PMd and MI and full upper limb motion capture will be used to simultaneously record neuronal spiking (192 channels) and measure the actions of the arm, wrist and fingers while monkeys perform tasks in different contexts. Context will be varied by training monkeys to perform four tasks that differ in the signals used for to guide arm actions: (1) using ongoing sensory feedback to capture a swinging object, (2) planning different grasp types from visual cues, (3) planning different goals for reach (either point or grasp), (3) making a perceptual judgments to determine grasp-type. Context-dependent changes will be measured in single cell responses and population representation (SA1) and in network functional connectivity (SA2) in PMv, PMd and MI simultaneously recorded for each task. Recording two or more contexts within single sessions will allow direct comparison of the same ensembles to determine how context modifies coding in single neurons, how population models generalize across contexts, and how networks combine various signals to achieve coordinated reach and grasp. We will address the hypothesis that PMv and PMd form separate information processing channels by comparing neural coding features and context sensitivity between areas. Finally, SA3 will test the requirement for specific sensorimotor computations by disrupting processing in these networks using emerging, highly-selective optogenetic methods or electrical stimulation. These studies will reveal mechanisms by which cortical circuits perform sensorimotor transformations and flexibly link groups of neurons to generate voluntary behavior. In addition, they will help to determine whether signals available in premotor areas, as well as MI, can provide useful sources for BCI command signals. Such signals could allow people with paralysis to regain complex functions like reach and grasp through robotic limbs that could operate usefully across a range of contexts.