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

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.