CRCNS: Deconstructing dynamics of motor cortex in freely moving behavior

项目总结（见说明）： 哺乳动物的中枢神经系统负责协调和指挥哪些操作 自愿运动？运动系统神经科学试图了解这些神经机制。的 在过去的二十年里，随着多电极记录的使用， 以及统计估计和建模技术。这些技术进步产生了丰富的， 低维神经动力学，暗示了行为背后的机制。到 最大限度地减少混淆，这些研究中的绝大多数利用行为约束，以隔离公正 学习感兴趣的行为。虽然有效地产生许多行为相似的试验，这可能 有一个无意的后果，人为地限制神经动力学的一个子集，其全部 范围 这个项目旨在更好地了解在一个自由移动的设置和模式的行为的全部剧目 这种神经活动使用新的计算工具。这个项目结合了两个 神经科学家，具有跨越系统和计算神经科学的互补技能。这 该项目将涉及利用深度成像的最新进展获取新颖的、自由移动的数据 摄像机和建模的动态标记的神经数据与创新的开关动态 模型 这种结合的专业知识将被应用于研究运动的开始与持续， 步行周期分解成不同的动态制度，并分析觅食 行为 总之，这些研究将进一步加深我们对神经动力学如何无约束地驱动 运动行为这一见解对开发移动式脑机接口具有启示意义 并且可以为患有运动障碍如中风的个体的治疗提供信息。

PROJECT SUMMARY (See instructions): What operations are performed by the mammalian central nervous systems to coordinate and conduct voluntary movement? Motor systems neuroscience seeks to understand these neural mechanisms. The last two decades have witnessed a transformation in this field with the use of multielectrode recordings and statistical estimation and modeling techniques. These technological advances have yielded rich, low-dimensional neural dynamics that are suggestive of the mechanisms underlying behavior. To minimize confounds, the overwhelming majority of these studies utilize behavioral constraint to isolate just the behaviors of interest for study. While effective for generating many behaviorally similar trials, this may have the unintentional consequence of artificially constraining neural dynamics to a subset of its full range. This project seeks to better understand the full repertoire of behavior in a freely-moving setting and model this neural activity using novel computational tools. This project combines the expertise of two neuroscientists with complemenary skillsets spanning systems and computational neuroscience. This project will involve acquiring novel, freely-moving data using the recent advances in depth imaging cameras and modeling the dynamics of the labelled neural data with innovative switching dynamical models. TThis combined expertise will be applied to the investigation of the initiation vs sustaining of movement, the decomposition of walking periods into distinct dynamical regimes, and an analysis of foraging behavior. Taken together, these studies will further our understanding of how neural dynamics drive unconstrained motor behavior. This insight has implications for the development of ambulatory brain-machine interfaces and may inform the treatment of individuals with motor disorders such as stroke.