Markerless Tracking of 3D Posture to Reveal the Sensory Origins of Body Schema

3D 姿势无标记跟踪揭示身体图式的感官起源

• 批准号: 10216941
• 负责人: Kyle Scott Severson
• 金额: $ 6.64万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10216941
• 关键词: 3-Dimensional; Address; Affect; Amputation; Anatomy; Animals; Area; Awareness; Behavior; Behavioral; Body part; Brain; Clinical; Code; Cognitive; Collaborations; Communities; Computer Analysis; Computer Vision Systems; Data Analyses; Deafferentation procedure; Disease; Educational workshop; Electrophysiology (science); Elements; Engineering; Environment; Excision; Experimental Models; Faculty; Feedback; Goals; Head; Health; Human; Individual; Intervention; Knowledge; Label; Learning; Limb Prosthesis; Limb structure; Locomotion; Machine Learning; Maintenance; Medical; Mentorship; Methodology; Methods; Modeling; Monitor; Motor; Movement; Mus; Neurobiology; Neurons; Operative Surgical Procedures; Parietal Lobe; Positioning Attribute; Posture; Process; Proxy; Reporting; Research; Research Training; Self Perception; Sensory; Somatosensory Cortex; Specialist; Speed; Stroke; System; Tactile; Talents; Technical Expertise; Techniques; Technology; Testing; Touch sensation; Training; Universities; Update; Vertebral column; base; brain machine interface; career; computational neuroscience; convolutional neural network; deep learning; design; experimental study; meetings; motor control; neural circuit; neural correlate; neuromechanism; novel; novel strategies; optogenetics; professor; relating to nervous system; research to practice; sensory input; skills; social cognition; somatosensory; stroke recovery; symposium; tenure track; tool

The goal of this proposed research is to reveal the sensory origins underlying the body schema representation. Body schema is the brain's internal model of the body's spatial configuration. This internal representation is critical for sensorimotor processing, movement control, and self-awareness, and is continuously updated during movement. Body schema representations are disrupted when somatosensory input is lost. The first step toward discover the neural correlates of body schema is to uncover neural mechanisms that generate body posture representation. We hypothesize that sensory inputs from primary somatosensory cortex (S1) and secondary somatosensory cortex (S2) to the posterior parietal cortex (PPC) are transformed to construct a body posture representation. To delineate the mechanisms underlying the neural coding of body posture, this project will utilize large- scale monitoring, apply interventional tools, develop new data analysis tools, and integrate new approaches. Our approach is to perform large-scale electrophysiological recording and novel markerless tracking of 3D posture in freely moving mice. To track posture, the first aim is to adapt a markerless tracking pipeline comprised of a deep 3D convolutional neural network to process high-speed videography of mouse behavior from multiple cameras. The second aim is to perform large-scale recording of neurons in S1, S2, and PPC and use advanced computational approaches to determine which postural features best explain the activity of neurons in these cortical areas. Finally, the third aim is to use optogenetic and projection-specific manipulations to address the causal impact of proprioceptive inputs from S1 and S2 on coding of posture in PPC. This research promises to uncover how sensory inputs are involved in generating the body schema representation and guiding behavior. Extensive training will be required to carry out this project and achieve my goal of earning a tenure-track professor position. The rigorous methodological and intellectual environment in Dr. Fan Wang’s lab and the Duke Neurobiology community will advance my conceptual knowledge and technical skills. I will implement deep learning techniques through training and collaboration with specialists. I will learn new techniques by attending Neuropixel and computational neuroscience courses. Finally, I will develop my professional skills by frequent attendance of seminars, workshops, and meeting with a postdoctoral mentorship committee. The proposed project will be conducted in the Department of Neurobiology at the Duke University Medical Campus. This interdisciplinary community at Duke will bolster the research and training included in this application through frequent interaction with talented and collaborative faculty, organization of seminars and symposia, numerous opportunities to practice research talks and receive valuable feedback, formation of a personalized postdoctoral mentorship committee, extensive career and professional training, and invaluable support from the postdoctoral association.

这项拟议的研究的目的是揭示身体模式的感官起源 表示。人体模式是大脑的内部模型的空间配置。这个内部 表示对于感觉运动处理，运动控制和自我意识至关重要，并且是 运动过程中不断更新。体内表述输入时，身体模式表示会破坏 迷路了。发现身体模式的神经相关性的第一步是发现神经机制 产生身体姿势表示。我们假设来自原发性体感皮质的感觉输入 （S1）和次级体感皮质（S2）到后顶叶皮层（PPC）被转化为 构建身体姿势表示。 为了描述身体姿势神经编码的基础机制，该项目将利用大量 比例监测，应用介入工具，开发新的数据分析工具并集成新方法。我们的 方法是进行大规模的电生理记录和3D姿势的新颖无标记跟踪 在自由移动的老鼠中。为了跟踪姿势，第一个目的是调整完整的无标记跟踪管道 深3D卷积神经网络，以处理来自多个鼠标行为的高速摄影 相机。第二个目的是在S1，S2和PPC中对神经元进行大规模记录，并使用Advanced 确定哪种姿势特征最好解释神经元活动的计算方法 皮质区域。最后，第三个目的是使用光遗传学和特定于投影的操作来解决 S1和S2的本体感受输入对PPC姿势编码的因果影响。这项研究有望 揭示感官输入在产生身体模式表示和指导行为时如何涉及。 需要进行大量培训才能执行此项目并实现我的目标 教授职位。范·王（Fan Wang）实验室和公爵 神经生物学社区将提高我的概念知识和技术技能。我将深入实施 通过与专家进行培训和合作学习技术。我会通过参加 神经胶质和计算神经科学课程。最后，我将按频率发展我的专业技能 半少数，讲习班和与博士后心态委员会会面。 拟议的项目将在杜克大学医学的神经生物学系进行 校园。杜克大学的这个跨学科社区将加强此处包括的研究和培训 通过与才华横溢和协作的教师，精液组织以及 座谈会，许多练习研究谈判的机会并获得宝贵的反馈，形成了 个性化博士后心态委员会，广泛的职业和专业培训以及宝贵的 博士后协会的支持。