CAREER: Unifying Neuroscience and Biomechanics Paradigms for Modeling Brain and Muscle Responses to Mechanical Impacts

创伤性脑损伤（TBI）仍然是一个日益严重的公共卫生问题，仅在美国，每年的发病率约为170万例，每年的费用约为406亿美元。尽管在生物力学和神经科学领域对脑损伤进行了大量的研究，但在脑损伤力学和相关运动损伤方面仍有很多进展要做。特别是，关于机械力如何以及在多大程度上影响大脑神经元活动的基本知识，以及脑损伤如何以及在多大程度上影响颈部肌肉反应的基本知识仍然未知。因此，这个教师早期职业发展（Career）项目旨在开发一个突破性的计算框架，可以模拟真实的脑肌肉激活动力学，并支持发现关于TBI力学和相关干预的基础知识。这项研究需要来自不同学科的方法和知识，包括神经科学、生物力学、人为因素和控制工程，从而影响工程与医学的融合。该项目的协同教育和推广活动概述了一项计划，通过课程开发、研究生和本科生参与研究活动以及K-12推广活动，加强生物工程、工业工程、机械工程和化学工程中神经生物力学的跨学科领域。此外，通过网络研讨会和视频博客的推广将提高广大受众，包括急救人员和创伤性脑损伤患者对创伤性脑损伤的科学素养水平。研究者的长期目标是发现脑多物理场和神经肌肉动力学之间的基本关系，以便开发工程技术（例如，头盔技术，神经假肢等）和治疗干预措施（例如，以TBI为重点的康复，手术治疗等），以减少运动，工作场所和日常活动中的TBI。为了实现这一愿景，该项目将提供一个脑-肌肉相互作用框架，称为bmi框架，这是一个由多尺度脑神经元模型、头颈有限元（FE）结构、比例-积分-导数（PID）算法和神经网络（NN）代理组成的闭环框架。这一目标将通过三个具体任务来实现：1)研究机械冲击对大脑神经元信号的影响，2)识别神经网络代理来预测大脑和肌肉PID增益参数，以及3)表征大脑和肌肉对机械冲击的反应。任务1侧重于开发和验证脑机电模型，以了解大脑神经元对各种（亚）创伤影响的反应。任务2将探索新的神经网络算法，以便以最小的迭代次数和循环延迟准确地调整大脑信号和个体颈部肌肉激活。任务3的重点是通过探索脑-肌相互作用在各种（亚）创伤性机械冲击和TBI条件下的动态反应来验证bmi -框架平台。这项研究是一项突破性的创新，因为它将脑肌相互作用动力学转化为基于数学的工程框架，目的是创造前所未有的科学知识，了解（次）创伤性机械冲击如何导致脑神经动力学的机电干扰，以及脑神经干扰如何影响颈部肌肉反应。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Traumatic brain injury (TBI) remains a growing public health concern, with an annual prevalence of about 1.7 million cases and a yearly cost of about $40.6 billion in the United States alone. Despite an extensive body of work on TBI in biomechanics and neuroscience domains, there is still much progress to be made to advance the knowledge of TBI mechanics and associated motor impairments. In particular, fundamental knowledge of how and to what extent mechanical force impacts brain neuronal activity and, in turn, how and to what extent brain impairment affects neck muscle responses remains unknown. Therefore, this Faculty Early Career Development (CAREER) project seeks to develop a breakthrough computational framework that can mimic realistic brain-muscle activation dynamics and support discovering fundamental knowledge about TBI mechanics and associated interventions. This research requires methods and knowledge from various disciplines, including neuroscience, biomechanics, human factors, and control engineering, thus impacting the convergence of engineering and medicine. The project’s synergistic education and outreach activities outline a plan to strengthen the interdisciplinary field of neuro-biomechanics in bioengineering, industrial engineering, mechanical engineering, and chemical engineering through course development, involvement of graduate and undergraduate students in the research activities, and K-12 outreach activities. In addition, the outreach through webinars and video blogging will enhance scientific literacy levels about TBI among broad audiences, including first responders and TBI patients.The investigator’s long-term goal is to discover the fundamental relationship between brain multiphysics and neuromuscular dynamics in order to develop engineering technologies (i.e., helmet technologies, neuroprosthetics, etc.) and therapeutic interventions (e.g., TBI-focused rehabilitation, surgical treatments, etc.) to reduce TBI in sports, workplaces, and daily activities. In pursuit of this vision, this project will provide a Brain-Muscle-Interaction framework, called BMI-frame, a closed-loop framework composed of multiscale brain neuronal models, head-neck finite-element (FE) structures, proportional-integral-derivative (PID) algorithms, and neural network (NN) agents. This objective will be accomplished through three specific tasks: 1) investigate the effects of mechanical impacts on brain neuronal signals, 2) identify NN agents to predict brain and muscle PID gain parameters, and 3) characterize brain and muscle responses to mechanical impacts. Task 1 focuses on developing and validating brain electromechanical models to understand brain neuronal response to various (sub) traumatic impacts. Task 2 will explore novel NN algorithms in order to accurately tune brain signals and individual neck muscle activations with a minimal number of iterations and loop delays. Task 3 focuses on validating the BMI-frame platform by exploring the dynamics of brain-muscle interactions in response to various (sub) traumatic mechanical impacts and TBI conditions. The research is a breakthrough innovation as it transforms brain-muscle interaction dynamics into a mathematically-grounded engineering framework, with the purpose of creating unprecedented scientific knowledge about how (sub) traumatic mechanical impacts cause electromechanical disruptions of brain neuronal dynamics and, in turn, how brain neuronal disruptions affect neck muscle responses.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.