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Collaborative Research: Deconstructing the contributions of muscle intrinsic mechanics to the control of locomotion using a novel Muscle Avatar approach

合作研究：使用新颖的肌肉化身方法解构肌肉内在力学对运动控制的贡献

基本信息

批准号：
2016049
负责人：
Monica Daley
金额：
$ 54.93万
依托单位：
University of California-Irvine
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016049&HistoricalAwards=false
关键词：
Collaborative Research Deconstructing contributions muscle

项目摘要

Moving animals achieve impressive athletic feats of endurance, speed, and agility in complex environments. Animal locomotion is particularly impressive in contrast to that of human-engineered machines. The stability, agility and energy economy of current robots, prostheses and exoskeletons remains poor compared to animals. This pronounced gap between animal performance and technology stems, in part, from fundamental gaps in the understanding of muscle physiology and mechanical function. Muscle is the only actively controlled tissue in animal musculoskeletal systems, and therefore plays a central role in enabling and controlling movement. Yet, developments over the past 20 years have led to growing recognition that important problems in muscle physiology and movement sciences remain unsolved and the theoretical foundation of the field remains incomplete. In particular, the ability to model and predict muscle function under dynamic and perturbed locomotor conditions remains poor. This project will combine innovative experimental techniques with modeling approaches to develop new muscle models that can explain and predict muscle movement under a broad range of conditions. The findings have potential to transform numerous fields— enabling neuroscientists, biologists, clinicians and biomedical engineers to ask questions about human and animal behavior, control of motion, function of muscles and bones, and capacity of the nervous system and muscles to change. The research team will collaborate with colleagues in clinical and engineering fields to translate the findings into applications in human rehabilitation, treatment of disease and injury, and the design and control of assistive technology such as prosthetics and exoskeleton devices.In the field of animal neuromechanics, a pronounced gap exists between ‘top down’ approaches — those that focus on whole-animal behavior but lack insight into underlying mechanisms— vs ‘bottom-up’ approaches — those that characterize mechanisms but lack insight into their contributions to animal behavior. The team will develop new tools to bridge this gap: 1) predictive muscle models that include intrinsic viscoelastic properties; and 2) experimental approaches that integrate across levels. This project’s novel ‘muscle avatar’ approach will help bridge this gap, and enable rigorous analysis of intrinsic muscle property and neural activation contributions to control of locomotion. Aim 1 tests the ability of the muscle avatar approach to replicate steady and perturbed in vivo work loop patterns in mouse and guinea fowl muscles. In Aim 2, in vivo muscle strain, activation, and force will be measured during steady and perturbed running in guinea fowl muscles, and the muscle avatar will be used to quantitatively assess how intrinsic muscle properties and neural drive each contribute to stabilizing responses. In Aim 3, alternative muscle models will be developed, and the ability of each model to predict in vivo muscle function in high strain and perturbed contraction conditions will be compared. Computationally tractable muscle models are essential for closed loop neuromechanical simulations of locomotion, which are increasingly used to understand how muscle function and sensorimotor control change in response to aging, injury and neuromuscular disorders. The findings could inform clinical rehabilitation strategies and the design of assistive devices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

移动的动物在复杂的环境中实现了令人印象深刻的耐力、速度和敏捷性的运动壮举。与人类工程机器相比，动物的运动尤其令人印象深刻。与动物相比，目前的机器人、假肢和外骨骼的稳定性、敏捷性和能源经济性仍然很差。动物性能和技术之间的这种明显差距，部分源于对肌肉生理学和机械功能理解的根本差距。肌肉是动物肌肉骨骼系统中唯一受主动控制的组织，因此在使能和控制运动方面起着核心作用。然而，过去20年的发展使人们越来越认识到，肌肉生理学和运动学中的重要问题仍然没有解决，该领域的理论基础仍然不完整。特别是，在动态和扰动的运动条件下对肌肉功能进行建模和预测的能力仍然很差。这个项目将结合创新的实验技术和建模方法来开发新的肌肉模型，可以解释和预测在广泛条件下的肌肉运动。这些发现有可能改变许多领域--使神经科学家、生物学家、临床医生和生物医学工程师能够就人类和动物的行为、运动的控制、肌肉和骨骼的功能以及神经系统和肌肉的变化能力提出问题。研究团队将与临床和工程领域的同事合作，将这些发现转化为人类康复、疾病和损伤治疗以及假肢和外骨骼设备等辅助技术的设计和控制方面的应用。在动物神经力学领域，“自上而下”的方法和“自下而上”的方法之间存在着明显的差距。“自上而下”的方法关注整个动物的行为，但缺乏对潜在机制的洞察。“自下而上”的方法描述了机制，但缺乏对它们对动物行为的贡献的洞察。该团队将开发新的工具来弥补这一差距：1)包括固有粘弹性特性的预测性肌肉模型；2)跨水平集成的实验方法。该项目新颖的“肌肉化身”方法将有助于弥合这一差距，并使严格分析内在肌肉属性和神经激活对运动控制的贡献成为可能。目的1测试肌肉替身方法在小鼠和豚鼠家禽肌肉中复制稳定和扰动的活体工作环模式的能力。在目标2中，将测量在体豚鸡肌肉在稳定和扰动运动中的肌肉应变、激活和力量，并将使用肌肉头像来定量评估内在肌肉属性和神经驱动各自如何对稳定反应做出贡献。在目标3中，将开发不同的肌肉模型，并比较每种模型在高应变和扰动收缩条件下预测活体肌肉功能的能力。易于计算的肌肉模型对于运动的闭环神经力学模拟是必不可少的，这些模型越来越多地被用于了解肌肉功能和感觉运动控制是如何随着年龄、损伤和神经肌肉疾病的反应而改变的。这些发现可以为临床康复战略和辅助设备的设计提供参考。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。