Mathematical Modeling of Motor Neuron Activity: Integrating Biophysical and Empirical Gait Data for Enhanced Understanding of Motor Function Throughout the Lifespan

This project aims to develop comprehensive mathematical models to better understand the cellular mechanisms underlying motor neuron activity in normal and pathological conditions. The core objective is to establish a general central pattern generator (CPG) model using ordinary differential equations (ODEs) which captures the dynamics of normal walking. This model will incorporate relevant inputs from key neural regions integral to motor control. Additionally, tailored ODE-based models will be created to represent motor neuron activity as affected by the expected aging process and pathologies of Parkinson's disease. These models will be grounded in biophysical and anatomical findings from existing literature. To validate and refine these models, empirical data on motor neuron activity and motor function will be utilized that has been collected from young adults, older adults, and adults with Parkinson’s disease through the Center for Balance and Aging Studies (CBAS). This data will be instrumental in understanding how the modeled neural activity translates into functional outcomes, such as gait, balance, and multitasking abilities during movement. By integrating theoretical modeling with empirical data, this project aims to provide a comprehensive framework for understanding the neurophysiological basis of motor function across different life stages and disease states.