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.

项目概要 日常生活活动（例如刷牙）需要大量大脑区域来快速协调它们 长时间尺度内驱动一系列运动的响应。申请取得的最新进展 物理科学和工程学中的经典工具，用于开发有关神经活动如何进化的理论 随着时间的推移，出现了许多针对运动障碍的新治疗方案（例如运动假肢、深部假肢） 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，运动皮层，它是大量神经研究的主要部位 假肢应用，只对即将到来的运动敏感。即使是两个人共同参与的简单动作 手臂的伸展是连续进行的，需要来自上游大脑区域的输入。因此，如果我们希望恢复 协调长期行动的能力，我们需要扩大我们的科学重点来研究网络级别 大脑区域之间的相互作用。相关上游区域包括辅助运动区（SMA）、 它与跟踪和协调动作序列以及背外侧前额叶皮层有关 （dlPFC），假设它指定了执行运动的正确顺序。 尽管对这些区域的功能进行了数十年的研究，但我们仍然缺乏描述这些区域的具体理论。 这些区域的计算，描述它们的相互作用，并提出它们如何工作的机制 一起编排动作序列。该项目将试图填补这一空白。 该项目将测试中心假设，即运动序列是由协调动作产生的 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 一个运动序列。其次，运动皮层上游的大脑区域（假设：SMA）如何将 将动作序列抽象为运动命令，可以以正确的方式向下游传输 正确的时间。该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结果 电生理学工具，执行高维数据分析，并开发复杂的神经网络 相互作用的大脑区域的模型。该项目将促进跨学科之间的直接互动 哥伦比亚大学实验运动神经生理学家和理论神经科学家。此外， 该提案的长期目标将通过获得基本的知识来促进 NINDS 的核心目标 有关运动控制的知识，因为它与治疗方法的开发有关。 该项目的成果将产生关键的计算原理，这些原理是交互作用的基础 皮质区域之间的相互作用增强了我们长期计划、协调和指导运动的能力。