In Vivo Neuromechanics: Decoding Causal Motor Neuron Behavior with Resulting Musculoskeletal Function

Area of Science:

• Neuroscience
• Biomechanics
• Human Physiology

Background:

• Human motor function relies on complex neuromuscular and musculoskeletal interactions.
• Understanding the neuro-mechanical interplay in the human neuro-musculo-skeletal system remains a significant challenge.

Purpose of the Study:

• To propose a novel paradigm for investigating spinal motor neuron contribution to skeletal joint mechanical function in humans.
• To bridge the gap between neural control and mechanical output in human movement.

Main Methods:

• Utilized multi-muscle spatial sampling and deconvolution of high-density electrical activity to decode alpha-motor neuron discharges.
• Drove subject-specific musculoskeletal models using complete alpha-motor neuron discharge series in an open-loop system.
• Performed validation tests by estimating mechanical moments without reference data.

Main Results:

• Accurately estimated ankle function solely from motor neuron information in a blinded manner.
• Observed direct causal associations between spinal motor neuron activity and joint moment control.
• Demonstrated the capability to predict mechanical joint function from neural signals.

Conclusions:

• Developed a new class of neural data-driven musculoskeletal modeling formulations.
• Provided a method for linking neural and mechanical levels of movement in vivo.
• Implications for understanding motor physiology, pathology, and rehabilitation strategies.