Dissecting circuit and cellular mechanisms for limb motor control

运动神经元与肌肉相连，构成神经系统的主要输出。模式： 运动神经元中的神经活动导致短暂精确的肌肉收缩，产生协调的 和灵活的行为。这些模式是由运动前电路的连通性和生理学决定的 在脊髓中与运动神经元发生突触。前置电机电路结合下行电机 带有感觉反馈信号的命令，以驱动运动神经元活动。前置马达网络如何 控制马达输出的结构还不是很清楚，部分原因是脊椎的库存不完整 细胞类型，以及记录动物行为中的神经活动的困难。为了解决这一差距，这 该项目旨在使用黑腹果蝇作为研究运动控制和运动前期的模型 神经回路。拥有易于接近和数字紧凑的神经系统，一个不断扩大的大型套间 在遗传工具和敏捷的四肢运动中，果蝇有潜力提供对 电机控制的基本问题。我们介绍了一个任务，在这个任务中，苍蝇学习生成特定的 在不同目标中定位股骨-胫骨关节的力的大小。关节由十二个人控制 可以被基因标记的神经元，用于定向神经记录。电生理记录 将揭示完整的运动神经元群体如何共同发挥作用，以动态定位 腿和维持给定力输出。这些数据将解决长期存在的关于如何 运动前回路招募运动神经元的子集，以及这种控制的灵活程度。然后, 一种新的电子显微镜水平的中央运动回路重建将允许识别关键 运动前神经元。在行为任务中对这些运动前神经元的电生理记录 将揭示它们在处理感觉反馈和控制腿部力量方面的贡献。这些结果 将为理解下行命令如何与 控制运动的身体状态，这是实现设计长期目标的关键一步 神经肌肉疾病的干预措施和控制工程系统的算法。

Motor neurons connect to muscles and comprise the major output of the nervous system. Patterns of neural activity in motor neurons cause temporally precise muscle contractions, producing coordinated and flexible behavior. These patterns are shaped by the connectivity and physiology of premotor circuits in the spinal cord that synapse onto the motor neurons. Premotor circuits combine descending motor commands with sensory feedback signals to drive motor neuron activity. How premotor networks are structured to control motor output is not well understood, due in part to an incomplete inventory of spinal cell types, and to the difficulties of recording neural activity in behaving animals. To address this gap, this project aims to use Drosophila melanogaster as a model for investigating motor control and premotor neural circuits. With an accessible and numerically compact nervous system, a large and growing suite of genetic tools, and agile, limbed locomotion, Drosophila has the potential to provide insight into fundamental problems of motor control. We introduce a task in which flies learn to generate specific amounts of force to position the femur-tibia joint in different targets. The joint is controlled by twelve neurons which can be genetically labeled for targeted neural recordings. Electrophysiological recordings will reveal how the complete population of motor neurons function together to dynamically position the leg and to sustain a given force output. These data will address long-standing hypotheses about how premotor circuits recruit subsets of motor neurons and the degree to which that control is flexible. Then, a new electron-microscopy level reconstruction of central locomotor circuits will allow identification of key premotor neurons. Electrophysiological recordings of those premotor neurons during the behavioral task will reveal their contributions to processing sensory feedback and to controlling leg force. These results will provide a foundation for understanding how descending commands interact with internal models of body state to control locomotion, a critical step toward achieving the long-term goals of designing interventions for neuromuscular disorders and algorithms for controlling engineered systems.