CRCNS Research Proposal: Collaborative Research: Neural Basis of Motor Expertise

一名篮球运动员如何才能可靠地将罚球投进篮下，但仍偶尔错失篮下？ 名义上相同的情况？虽然这些技能是运动技能的典范，即使看起来 平凡的行动也需要惊人的灵巧。当端满一杯咖啡时，我们会展示马达 远远超出了通常在实验室中研究的技能。具体地说，当与对象交互时 -任何工具使用的本质--成功的操作需要对相互作用力进行细粒度的控制 已经超出了神经科学的研究范围。这项拟议的研究检查了神经 通过将丰富的交互任务引入实验室，奠定了运动专业知识的基础。这两个PI将他们的 在计算机运动控制和神经生理学研究新的行为方面有长期的经验 人类和非人类灵长类动物的范例。在概念和计算重叠的基础上 他们各自的研究，其中技能与高维中的低维结构相关联 神经和行为的冗余空间，他们将检验神经模式的整体假设 活动表现出行为的许多特征。两个目标将研究电机的两个例子 技能：投掷物体和运送带有内部动力学的物体，两者都以虚拟方式渲染 环境。在人类和灵长类动物身上进行的平行实验将产生丰富的行为数据，这些数据将 与非人类灵长类动物大脑皮层的皮质内记录相匹配。到目前为止，非人类 灵长类动物的研究使动物有必要对简单的行为进行几乎相同的重复 促进神经活动的分析。现在，现代多神经元记录技术使之成为可能 拥抱更复杂的现实世界行为，并解决已发现的运动核心原则 在人类运动控制中：高维性、冗余性和无处不在的变异性。这项研究 将开发一套计算工具，用于分析行为和神经数据 与之相称的技术和复杂性。这项研究将是变革性的，因为它推动了 接受检查的运动挑战使皮质内神经生理学的见解更接近理解 人类运动方面的专业知识。这些科学见解将用于广泛的外联活动，以 对广大公众产生更广泛的影响。 相关性(请参阅说明)： 中风等神经系统疾病患者日常活动面临挑战，抓着杯子 带到嘴里喝水；这些动作本质上是交互式工具的使用。这项研究寻求 洞察在这些熟练的动作和互动中的神经激活，以更近距离地了解 与现实生活相关的任务中的神经活动。从皮巴蒂斯塔的经验来看，神经假体和 脑机接口是直接的临床应用，可能受益于我们的发现和恢复

How can a basketball player reliably land his free throw in the basket, and yet still miss occasionally under nominally identical circumstances? While such skills are a paragon of motor expertise, even seemingly mundane actions also require surprising dexterity. When carrying a full cup of coffee, we exhibit motor skill that is far beyond what is typically studied in the laboratory. Specifically, when interacting with objects - the essence of any tool use -, successful actions require fine-grained control of interaction forces that have been beyond the purview of neuroscience to date. The proposed research examines the neural basis of motor expertise by bringing rich interactive tasks into the laboratory. The two PIs combine their long-standing experience in computational motor control and neurophysiology to study novel behavioral paradigms both in humans and non-human primates. Building on conceptual and computational overlap in their respective research, where skill is associated with low-dimensional structure in high-dimensional neural and behavioral redundant spaces, they will test the overall hypothesis that patterns of neural activity exhibit many of the characteristics of the behavior. Two aims will study two examples of motor skill: throwing an object and transporting an object with internal dynamics, both rendered in virtual environments. Parallel experiments in humans and primates will generate rich behavioral data that will be matched with intracortical recordings in the cerebral cortex of non-human primates. To date, non-human primate studies have necessitated that animals perform near-identical repetitions of simple behaviors to facilitate the analysis of neural activity. Now, modern multi-neuronal recording techniques make it possible to embrace more sophisticated real-world behaviors and address core principles of movement discovered in human motor control: high dimensionality, redundancy, and the ever-present variability. This research will develop a suite of computational tools that afford the analysis of behavioral and neural data with commensurate techniques and sophistication. This research will be transformative as it advances the motor challenges examined and brings insights from intracortical neurophysiology closer to understanding of human motor expertise. These scientific insights will channel into a large range of outreach activities to achieve broader impacts for the general public. RELEVANCE (See instructions): Patients with neurological disorders such as stroke face challenges in their daily activities, grasping a cup to bring to their mouths to drink; these actions are essentially interactive tool use. This research seeks insights into neural activation during such skilled actions and interactions to get closer to understand neural activity in tasks relevant in real life. Extending from PI Batista’s experience, neuroprosthetics and brain-machine interfaces are direct clinical application that may benefit from our findings and recovery