Neural control of skilled movements: an ethological dissection of genetically tractable mammalian motor circuits

项目摘要 在哺乳动物运动技能的不同特征中，熟练的肢体运动已经成为一些 更令人印象深刻和不可或缺的与环境互动的方式。这些病毒的易感性 神经退行性疾病和损伤的运动强调了更好地理解如何 神经回路协调这些灵巧的行为。这一目标需要复杂的实验审查。 在神经和行为层面上，虽然用于监测和操纵的遗传工具的出现 小鼠的神经回路已经发生了变化，运动行为分析的发展并没有跟上 佩斯。通常，单一的行为测试应用于手头的问题，从而排除了更全面的 描述为什么相关的神经回路进化出其特定的解剖和功能属性。 此外，在肢体运动控制的研究中，灵长类动物启发的行为范式倾向于应用于 默认情况下，可能会忽略对运动回路功能的更完整、更自然的描述。 行为学强调对自然条件下的行为进行公正的研究。这份提案描述了 一种用于量化和分类小鼠熟练肢体运动的行为学方法，使 行为分析的深度和广度与潜在神经的复杂性更紧密地一致 电路。小鼠肢体运动无偏行为量化的几种互补方法 在丰富的环境中将并行开发：一套光学技术，使自动化的三个 肢体和手指姿势和轨迹的三维重建；以及一种利用先进技术的方法 在用于无摄像头肢体跟踪的运动传感器的微型化中，可以与 神经和肌电(EMG)记录。通过迭代改进，这一多方面的策略应该 突出每种跟踪方法的优点并缓解其潜在缺点，提供一套 互为补充的量化工具。通过不同的行为收集运动学、运动学、肌电和神经数据 上下文将用于指导基于机器学习的肢体运动中自然结构的分类 以及它们潜在的神经回路中。作为这些自然主义行为分析如何 与神经回路功能的遗传解剖相结合，一组分子定义的马达回路 将使用新的光遗传工具进行探索，这些工具允许在定义的轴突侧支终末选择性抑制。 这种投射特有的遗传扰动和行为学驱动的行为分析的组合将 提供了一个强大的镜头，通过它来观察哺乳动物运动的细粒度功能组织 电路。更广泛地说，这种分子和系统神经科学方法的融合将提供一种新颖的 探索和比较跨物种精细电机控制的方法，为现场配备更全面的 和标准化的方法来研究熟练的行为，并帮助为更好的诊断和 治疗与神经回路功能障碍相关的行为缺陷。

Project Summary Of the diverse features of the mammalian motor repertoire, skilled limb movements have become some of the more impressive and indispensable ways of interacting with the environment. The susceptibility of these movements to neurodegenerative disease and injury underscores the need for a better understanding of how neural circuits orchestrate these dexterous behaviors. This goal demands sophisticated experimental scrutiny at both neural and behavioral levels, and while the emergence of genetic tools for monitoring and manipulating neural circuits in mice has been transformative, the development of motor behavioral assays has not kept pace. Typically, a single behavioral test is applied to the question at hand, precluding a more comprehensive description of why relevant neural circuits have evolved their particular anatomical and functional attributes. Moreover, in the study of limb motor control, primate-inspired behavioral paradigms tend to be applied to the mouse by default, risking neglect of a more complete and naturalistic account of motor circuit function. Ethology emphasizes an unbiased study of behavior under natural conditions. This proposal describes an ethological approach for the quantification and categorization of skilled limb movements in mice, enabling a depth and breadth of behavioral analysis that more closely aligns with the complexity of the underlying neural circuits. Several complementary approaches for unbiased behavioral quantification of mouse limb movements in enriched environments will be developed in parallel: a set of optical techniques enabling automated three- dimensional reconstruction of limb and digit posture and trajectory; and an approach that leverages advances in the miniaturization of motion sensors for camera-free limb tracking that can be integrated seamlessly with neural and electromyography (EMG) recordings. Through iterative refinement, this multifaceted strategy should highlight the strengths and mitigate potential drawbacks of each tracking method, providing a suite of complementary quantitative tools. Kinematic, kinetic, EMG and neural data collected across diverse behavioral contexts will be used to guide machine learning-based classification of natural structure in limb movements and in their underlying neural circuits. As a proving ground for how these naturalistic behavioral analyses can be integrated with the genetic dissection of neural circuit function, a set of molecularly defined motor circuits will be probed using novel optogenetic tools that permit selective inhibition at defined axon collateral terminals. This combination of projection specific genetic perturbation and ethologically driven behavioral analyses will provide a powerful lens through which to view the fine-grained functional organization of mammalian motor circuits. More generally, this merging of molecular and systems neuroscience approaches will offer a novel way to explore and compare fine motor control across species, equipping the field with a more comprehensive and standardized approach to study skilled behavior, and helping lay the foundation for better diagnosis and treatment of behavioral deficits associated with neural circuit dysfunction.