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执行哪些操作来协调和进行 自愿行动？运动系统神经科学试图了解这些神经机制。这个 在过去的二十年里，随着多电极记录的使用，见证了这一领域的变化 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，它暗示了潜在的行为机制。至 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来隔离 有兴趣学习的行为。虽然这对产生许多行为相似的试验是有效的，但这可能 有人为地将神经动力学限制在其完整的子集的无意后果 射程。 这个项目寻求更好地理解在自由移动的环境和模型中行为的完整剧目 这种神经活动使用新的计算工具。这个项目结合了两家公司的专业知识 拥有跨越系统和计算神经科学的互补技能的神经科学家。这 该项目将使用深度成像的最新进展来获取新的、自由移动的数据 摄像机和标记的神经数据的动力学建模 模特们。 这一综合的专门知识将用于研究运动的启动和维持， 步行周期分解为不同的动力机制和觅食分析 行为。 综上所述，这些研究将进一步加深我们对神经动力学如何不受约束地驱动的理解 运动行为。这一见解对可移动的脑机接口的发展具有重要意义 并可为中风等运动障碍患者的治疗提供信息。

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.