Combining Physiological, Genetic, and Computational Approaches with Naturalistic Climbing Behavior to Elucidate the Functional Elements of Descending Motor Control

项目摘要 许多哺乳动物以其肢体运动的多样性和敏捷性而著称。这些品质 对某些运动赋予的适应性至关重要，因此对许多物种的进化成功至关重要。而 对于肢体控制重要的大脑区域已经被确定，即最终控制的神经信号处理区域 发送到肌肉的运动指令仍然顽固地不透明。运动系统的力学模型 因此缺少在运动期间的真实的操作。这掩盖了运动缺陷的病因， 神经系统疾病和中风，这反过来又阻碍了有效治疗的发展。 运动系统处理的这种不透明性的主要原因是基本功能的模糊性。 包括相关神经回路的元件。一种新兴的观点认为，这些元素可能是神经元 亚型由轴突靶区域、靶细胞身份和基因表达等特征定义。然而 什么样的细胞特征适合定义功能单位的基本问题仍然存在 无人回应这种模糊性源于一系列技术限制。我们认为， 神经元亚型将对运动的特定阶段做出特征性贡献。然而传统的方法 用于沉默神经活动以评估功能的方法缺乏辨别这种特定影响的时间分辨率。我们 我还预计，功能突出的亚型将表现出不同的活动模式和相互作用，与其他 神经元群体。但是测量神经放电的经典方法通常对关键的细胞特征视而不见。 此外，用于运动系统研究的行为范式没有捕捉到运动的基本方面。 自然的哺乳动物运动，运动系统的组织可能已经适应了进化。 幸运的是，系统神经科学目前正在被生理学、 基因和计算技术。我计划利用其中的许多进步， 解决模型运动系统人群中的基本功能要素的方法-大脑下 投射神经元（SPNs）发现在运动区的新皮质。我们将采用一种自然主义的攀爬模式 在我的实验室里设计的小鼠克服了以前运动行为模式的局限性。新基因- 介导的靶向策略将为活性测量提供潜在的功能亚型， 扰动我们将新颖地耦合光遗传学探针，肌电图，和自动化行为 分解以区分神经元亚型影响的精确阶段。大规模、多区域活动 记录、光遗传学识别和机器学习将通过它们的活动和相互作用来解析亚型。 与其他神经元群体。我们的工作将阐明一个跨学科的方法适用于 其他神经系统中功能单位的基本问题。我们的工作开始于机械论的洞察力 将有助于阐明ALS和亨廷顿舞蹈症等疾病引起的运动缺陷的病因 疾病，中风后。

PROJECT SUMMARY Many mammals are distinguished by the exceptional diversity and agility of their limb movement. These qualities are critical to the fitness certain movements confer, and so to the evolutionary success of many species. While brain regions important for limb control have been identified, the neural signal processing that ultimately governs motor commands sent to muscles has remained stubbornly opaque. Mechanistic models of motor system operation in real time during movement are thus lacking. This obscures the etiology of motor deficits caused by neurological disease and stroke, which in turn stymies the development of effective treatments. A primary cause of this opacity of motor system processing is the ambiguity of the basic functional elements comprising relevant neural circuits. An emerging view posits that these elements may be neuronal subtypes defined by features like axonal target region, target cell identity, and gene expression. Yet the fundamental question of what are the appropriate cellular features for defining functional units remains unanswered. This ambiguity stems from a host of technical limitations. We expect that functionally salient neuronal subtypes will make characteristic contributions to specific phases of movement. Yet traditional methods for silencing neural activity to assess function lack the temporal resolution to discern such specific influence. We also expect that functionally salient subtypes will exhibit distinct activity patterns and interactions with other neuronal populations. But classical methods for measuring neural firing are typically blind to key cellular features. Moreover, the behavioral paradigms used for motor system studies have not captured essential aspects of natural mammalian movement, for which motor system organization may have been adapted over evolution. Fortunately though, systems neuroscience is currently being revolutionized by advances in physiological, genetic, and computational techniques. I plan to leverage many of these advances and pursue an innovative approach to resolve the basic functional elements within a model motor system population – the subcerebral projection neurons (SPNs) found in motor areas of the neocortex. We will employ a naturalistic climbing paradigm for mice engineered in my lab to overcome limitations of previous motor behavior paradigms. New genetically- mediated targeting strategies will provide access to potential functional subtypes for activity measurement and perturbation. We will novelly couple optogenetic probes, electromyography, and automated behavior decomposition to distinguish precise phases of neuronal subtype influence. Large-scale, multi-area activity recording, optogenetic identification, and machine learning will parse subtypes by their activity and interactions with other neuronal populations. Our work will articulate an interdisciplinary approach applicable to the fundamental question of functional units in other neural systems as well. The mechanistic insight our work begins to build will help elucidate the etiology of movement deficits stemming from conditions like ALS and Huntington’s disease, and following stroke.