Touching on locomotion: an anatomical and functional analysis of spinal cord circuits that shape the way we move

触及运动：对塑造我们运动方式的脊髓回路进行解剖学和功能分析

• 批准号: 10094597
• 负责人: Victoria Eugenia Guadalupe Abraira
• 金额: $ 43.33万
• 依托单位: RUTGERS, THE STATE UNIV OF N.J.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10094597
• 关键词: Address; Affect; Afferent Neurons; Anatomy; Behavior; Behavioral Assay; Biological Assay; Biomedical Research; Complex; Computer Vision Systems; Coupled; Cutaneous; Data; Disease; Electrophysiology (science); Environment; Extensor; Flexor; Foundations; Genetic; Hindlimb; Individual; Injury; Interneurons; Investigation; Joints; Lateral; Length; Limb structure; Link; Locomotion; Machine Learning; Mechanics; Modality; Motor; Motor Activity; Motor Neurons; Motor Pathways; Motor output; Movement; Muscle; Muscle Contraction; Neurons; Neurosciences; Organ; Output; Parvalbumins; Pathway interactions; Pattern; Positioning Attribute; Property; Proprioception; Proprioceptor; Quality of life; Reflex action; Research; Resolution; Sensorimotor functions; Sensory; Shapes; Skin; Slice; Speed; Spinal; Spinal Cord; Spinal cord posterior horn; Structure; Synapses; Technology; Testing; Touch sensation; Walking; Work; behavioral study; cutaneous sensory neurons; electrical property; genetic approach; improved; in vivo; insight; interdisciplinary approach; motor behavior; motor function improvement; mouse genetics; multimodality; nervous system disorder; neural circuit; novel; novel strategies; novel therapeutics; programs; receptor; response; sensory input; sensory stimulus; somatosensory; tool; vibration

Project Summary/Abstract A central challenge in neuroscience biomedical research is to define the neural circuits that underlie behavior. Investigations of spinal cord circuits are ideally suited to answer these questions: the direct link between sensory input and motor output affords an exquisite experimental tractability that has been leveraged since Sherrington’s pioneering work on the proprioceptive reflex pathway1. Indeed, great progress has been made since then in understanding how proprioceptors (i.e., muscle sensory neurons) shape motor activity. Touch receptors in skin (i.e., cutaneous sensory neurons) encoding sensory modalities like vibration, indentation, and slip, are also critical for adapting the way we walk in response to changes in our environment. However, spinal cord integration of touch pathways that sculpt motor activity remains profoundly poorly understood. To address key conceptual and technical challenges in this field, we have built an extensive mouse genetic toolbox to visualize, quantify and manipulate touch-specific spinal cord circuits. In addition, we merge these powerful genetic tools with motor assays involving high-speed cameras, computer vision, and machine learning to quantify somatosensory behavior with unprecedented sensitivity. Combining these technologies, we identified a novel touch-specific premotor network important for sensorimotor function. Our overall hypothesis is that this network represents a critical node for integrating touch information to influence specific patterns of muscle groups that facilitate both corrective movements during locomotion and motor ‘switching’ during naturalistic behaviors. We interrogate this novel network to address fundamental questions whose answers will enable a deeper understanding of how touch pathways converge in the spinal cord to shape movement. In Aims 1 and 2 we combine genetic approaches, high-resolution synaptic analysis, slice electrophysiology and in-vivo muscle recordings to test the hypothesis that this network integrates multimodal sensory information to coordinate specific muscles in response to cutaneous input. Aim 3 combines joint and muscle activity recordings to test the hypothesis that this network shapes cutaneous responses to facilitate corrective movements during locomotion. We extend these behavioral studies by implementing computer vision and machine learning to parse out naturalistic behaviors into sub- second movements to test the hypothesis that touch-specific premotor networks sculpt how micro-movements are pieced together into complex motor behaviors . By understanding the final path for movement organization (i.e., the spinal cord) our research will lead to new therapies aimed at improving the quality of life of people suffering from a variety of neurological disorders. Thus, this research lays the critical foundation for novel ways to modulate spinal circuits for improving motor function.

项目摘要/摘要 神经科学生物医学研究中的一个核心挑战是定义行为基础的神经学。 对脊髓电路的调查非常适合回答以下问题：感官之间的直接联系 输入和电动机输出提供了自Sherrington的独家实验性障碍。 关于本体感受反射途径的开创性工作1。确实，从那以后取得了巨大进步 了解本体感受器（即肌肉感觉神经元）如何塑造运动活动。皮肤中的触摸受体 （即皮肤感觉神经元）编码振动，压痕和滑动等感觉方式 对于适应我们对环境变化的回应方式至关重要。但是，脊髓整合 雕刻运动活动的触摸途径仍然深刻了解。解决关键概念 以及该领域的技术挑战，我们建立了一个广泛的鼠标基因工具箱来可视化，量化和 操纵触摸特异性的脊髓电路。此外，我们将这些强大的遗传工具与电动机合并 涉及高速相机，计算机视觉和机器学习以量化体感的测定 具有前所未有的灵敏度的行为。结合了这些技术，我们确定了一种新颖的触摸特异性 前感觉网络对感觉运动功能很重要。我们的总体假设是该网络代表 集成触摸信息以影响肌肉群体的特定模式的关键节点 自然行为期间的运动和电动机“切换”期间的矫正运动。我们询问这个 解决基本问题的新颖网络，其答案将使他们能够更深入地了解如何 接触路径在脊髓中汇聚以形成运动。在目标1和2中，我们结合了遗传方法， 高分辨率合成分析，切片电生理学和体内肌肉记录以检验假设 该网络集成了多模式感官信息，以协调特定的肌肉 皮肤输入。 AIM 3结合了关节和肌肉活动记录，以测试该网络的假设 皮肤反应在运动过程中促进矫正运动。我们扩展了这些行为 通过实施计算机视觉和机器学习来将自然主义行为解析为子研究 测试触摸特异性前网络雕刻微动物的第二个动作以测试假设 将碎片拼成复杂的运动行为 。通过了解运动组织的最终道路 （即脊髓）我们的研究将导致新的疗法，以改善人们的生活质量 患有多种神经系统疾病。这是这项研究为新颖方式的关键基础 调节脊柱以改善运动功能。