Static and Dynamic Organization of Primate Motor Cortex

描述(申请人提供)：我研究的长期目标是(1)了解皮质网络如何灵活地根据感觉和认知信号计算动作，以及(2)利用这一知识开发脑机接口(BCI)，以恢复对瘫痪患者执行有用动作的能力。这个项目的具体目标是确定运动前和运动皮质中相互连接的神经元网络是如何计算、到达和掌握不同类型信号的动作的。额叶皮质的背侧运动前区(PMD)和腹侧运动前区(PMV)似乎代表着汇聚在初级运动皮质(MI)的独立加工流，在那里，伸展和抓取是统一的。这种相互作用的电路似乎通过动态地将各种线索与特定的手臂和手动作联系起来来产生动作命令，但研究了所处理信号的性质、所执行的感觉运动转换的类型或它们在手臂和手运动中的角色的冲突。本研究介绍了几种新的方法来理解这些大脑皮层网络的集体动力学如何提供一个灵活的底物来连接不同的信号和行为。植入PMV、PMD和MI的长期植入的多电极阵列和完整的上肢运动捕捉将用于同时记录神经元尖峰信号(192个通道)，并测量猴子在不同环境中执行任务时手臂、手腕和手指的动作。通过训练猴子执行四种不同的任务来指导手臂动作，可以改变情境：(1)使用正在进行的感觉反馈来捕捉摆动的物体，(2)根据视觉线索规划不同的抓握类型，(3)计划不同的伸展目标(无论是指向还是抓握)，(3)进行感知判断以确定抓握类型。上下文相关的变化将在单细胞响应和总体表示(SA1)以及同时记录的PMV、PMD和MI中的网络功能连通性(SA2)中测量，用于每个任务。在单个会话中记录两个或更多上下文将允许对相同的整体进行直接比较，以确定上下文如何修改单个神经元中的编码，种群模型如何在上下文中泛化，以及网络如何组合各种信号以实现协调的到达和把握。我们将通过比较不同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来扰乱这些网络中的处理，来测试对特定感觉运动计算的需求。这些研究将揭示大脑皮层回路执行感觉运动转换和灵活连接神经元群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的可用信号以及MI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患者通过机械臂重新获得复杂的功能，比如伸手和抓握，这些机械臂可以在一系列背景下有效地操作。

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.