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（例如，刷牙）需要大量的大脑区域来快速协调它们的活动。 在长时间尺度上驱动运动序列的反应。最近的进展， 从物理科学和工程学的经典工具来发展关于神经活动如何进化的理论 随着时间的推移已经产生了许多用于运动障碍的新的治疗选择（例如，运动修复术，深部 脑刺激等）。然而，日常生活活动需要产生复杂的认知运动， 序列的例如，运动皮层，这是大量神经系统研究的主要部位， 假肢的应用，只对即将到来的运动敏感。即使是一个简单的动作， 手臂连续伸展，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，我们需要扩大我们的科学重点，研究网络级 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）， 与跟踪和协调动作序列有关， （dlPFC），其被假设为指定应当执行的运动的正确顺序。 尽管对这些区域的功能进行了数十年的研究，但我们仍然缺乏一个具体的理论来描述这些区域的功能。 这些领域的计算，其相互作用的特点，并提出了一个机制，他们如何工作 共同协调动作序列。本项目将试图填补这一空白。 这个项目将测试中心的假设，运动序列产生的协调行动 大脑皮层区域以特定的方式划分计算工作。特别是，该项目将调查两个 根本问题。首先，大脑（假设：dlPFC）如何选择正确的执行顺序 动作序列。第二，运动皮层上游的大脑区域（假设：SMA）如何将运动皮层转化为运动皮层。 将一系列动作抽象成运动命令，这些命令可以以正确的方式在下游传输， 正确的时间这个项目将通过开发一个复杂的认知- 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值 电生理学工具，进行高维数据分析，并开发复杂的神经网络 相互作用的大脑区域的模型。该项目将促进直接跨学科的互动， 哥伦比亚大学的实验运动神经生理学家和理论神经科学家。而且 本建议书的长期目标将有助于实现国家信息化战略的核心目标， 关于运动控制的知识，因为它涉及到治疗的发展。 这个项目的结果将导致关键的计算原则，基础如何相互作用 大脑皮层区域之间的相互作用增强了我们在长时间内计划、协调和引导运动的能力。