Cortical Computations Underlying Planning, Generating, and Orchestrating Complex Cognitive-Motor Sequences

规划、生成和编排复杂认知运动序列的皮层计算

• 批准号: 10551724
• 负责人: Saurabh Vyas
• 金额: $ 6.95万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-16 至 2025-02-15
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10551724
• 关键词: Activities of Daily Living; Affect; Algorithms; Amyotrophic Lateral Sclerosis; Area; Behavior; Brain; Brain region; Clinical; Cognitive; Communication; Complex; Data; Data Analyses; Deep Brain Stimulation; Dimensions; Disease; Dorsal; Dystonia; Electrodes; Electrophysiology (science); Engineering; Excision; Feedback; Goals; Hygiene; Investigation; Knowledge; Measurement; Mentors; Methods; Modernization; Motor; Motor Cortex; Motor Neurons; Movement; Movement Disorders; National Institute of Neurological Disorders and Stroke; Nervous System Trauma; Neural Network Simulation; Neurons; Neurosciences; Outcome; Output; Parkinson Disease; Population; Population Analysis; Population Dynamics; Prefrontal Cortex; Privatization; Process; Production; Property; Prosthesis; Research; Series; Signal Transduction; Site; Specific qualifier value; Sterile coverings; Structure; System; Testing; Time; Tooth structure; Training; Universities; Work; arm; computer studies; design; dynamic system; motor control; multidimensional data; nervous system disorder; network models; neural; neural prosthesis; nonhuman primate; physical science; recurrent neural network; response; segregation; success; theories; therapeutic development; tool; transmission process

Project Summary Activities of daily living (e.g., brushing one’s teeth) require a slew of brain regions to rapidly coordinate their responses to drive sequences of movements over long timescales. Recent progress resulting from applying classical tools from physical science and engineering to develop theories regarding how neural activity evolves across time has led to a number of new treatment options for movement disorders (e.g., motor prosthetics, deep brain stimulation, etc.). Activities of daily living, however, require production of complex cognitive-motor sequences. For example, motor cortex, which is the primary site for a large number of investigations for neural prosthetics applications, is only sensitive to the upcoming movement. Even a simple movement involving two arm reaches performed in succession, requires input from upstream brain regions. Thus, if we hope to restore the ability to orchestrate long timescale actions, we need to expand our scientific focus to study network-level interactions between brain regions. Relevant upstream areas include the supplementary motor area (SMA), which has been implicated in tracking and coordinating action sequences, and dorsolateral prefrontal cortex (dlPFC), which has been hypothesized to specify the correct order in which movements should be performed. Despite decades of research in the function of these areas, we still lack a concrete theory that describes the computations of these areas, characterizes their interactions, and proposes a mechanism of how they work together to orchestrate movement sequences. This project will attempt to fill this gap. This project will test the central hypothesis that movement sequences arise from the coordinated action of cortical regions that divide computational labor in specific ways. In particular, this project will investigate two fundamental questions. First, how does the brain (hypothesis: dlPFC) choose the right order in which to perform a movement sequence. Second, how does a brain area upstream of motor cortex (hypothesis: SMA) convert an abstract sequence of actions into movement commands that can be transmitted downstream in the right way at the right time. This project will test these hypotheses through a combination of developing a complex cognitive- motor task, acquiring large-scale simultaneously recorded measurements of neural activity using state-of-the-art electrophysiology tools, performing high-dimensional data analysis, and developing sophisticated neural network models of interacting brain regions. This project will facilitate direct interdisciplinary interactions between experimental motor neurophysiologist and theoretical neuroscientists at Columbia University. Moreover, the long-term objectives of this proposal will contribute to the core goal of NINDS by acquiring fundamental knowledge about movement control as it relates to development of therapeutics. The outcome of this project will result in key computational principles that underlie how the interaction between cortical regions gives rise to our ability to plan, orchestrate, and guide movements over long timescales.

项目摘要 日常生活活动(如刷牙)需要一系列大脑区域来快速协调它们的 对在长时间尺度上驱动运动序列的反应。应用技术取得的最新进展 来自物理科学和工程的经典工具，以开发关于神经活动如何进化的理论 随着时间的推移，为运动障碍带来了许多新的治疗选择(例如，运动假体，深度 脑刺激等)。然而，日常生活活动需要产生复杂的认知运动 序列。例如，运动皮质，这是大量神经研究的主要地点 假肢的应用，只对即将到来的运动敏感。即使是两个简单的动作 ARM的伸展是连续进行的，需要上游大脑区域的输入。因此，如果我们希望恢复 协调长时间尺度行动的能力，我们需要将我们的科学重点扩展到研究网络层面 大脑区域之间的相互作用。相关的上游区域包括辅助运动区(SMA)， 与追踪和协调动作序列有关，以及背外侧前额叶皮质 (DLPFC)，它被假设为指定应该执行的动作的正确顺序。 尽管几十年来对这些区域的功能进行了研究，但我们仍然缺乏一个具体的理论来描述 对这些区域的计算，描述它们之间的相互作用，并提出它们如何工作的机制 一起来编排动作序列。这个项目将试图填补这一空白。 这个项目将检验运动序列产生于协调动作的中心假设 以特定方式划分计算劳动的皮质区域。特别是，该项目将调查两个 基本问题。首先，大脑(假设：DLPFC)如何选择正确的执行顺序 一个动作序列。第二，运动皮质上游的大脑区域(假设：SMA)如何将 将动作序列抽象为可向下游以正确方式向下传输的移动命令 恰逢其时。这个项目将通过开发复杂的认知-组合来测试这些假设- 运动任务，使用最先进的技术获取大规模同时记录的神经活动测量 电生理学工具，执行高维数据分析，开发复杂的神经网络 相互作用的大脑区域的模型。该项目将促进两国之间的直接跨学科互动。 哥伦比亚大学的实验运动神经生理学家和理论神经学家。此外， 该计划的长期目标将通过获取基本信息，为NINDS的核心目标做出贡献 关于运动控制的知识，因为它与治疗学的发展有关。 这个项目的结果将导致关键的计算原则，这些原则是相互作用的基础 大脑皮层之间的运动提高了我们在长时间尺度上计划、协调和指导运动的能力。