Neuromuscular information transmission patterns for human motor identification on non-invasive tFUS brain signal.

This study investigates neuromuscular information transmission patterns facilitated by non-invasive transcranial focused ultrasound (tFUS), a novel neuromodulation technique. The research explores how neuromodulation via tFUS influences motor unit action potentials (MUAPs) and their coherence with synchronized EEG signals during varying motor tasks. EEG and surface electromyography (sEMG) signals were recorded from nine healthy subjects performing motor tasks at 15 % and 30 % maximum voluntary contraction (MVC). Morphological decomposition and template reconstruction were applied to decompose sEMG signals into their fundamental components. MUAP features-amplitude, quantity, and firing rate-were extracted and analyzed. The study employed Transfer Entropy to measure the coherence between MUAP features and EEG signals, assessing the impact of tFUS on cortical-muscle interactions. The analysis revealed that MUAP features, particularly amplitude, were significantly enhanced at higher grip strength levels (30 % MVC). The MUAP amplitude emerged as the most responsive feature, reflecting cortical activity peaks and troughs with high sensitivity. Unlike prior studies focusing on overall muscle electrical signals, this research used sEMG decomposition to obtain granular MUAP features, offering richer insights into neuromuscular dynamics. The findings align with the "size principle" of motor unit recruitment, confirming that larger MUAPs are recruited at higher force levels. Moreover, the use of tFUS, an emerging NIBS modality, extends previous research by demonstrating its efficacy in modulating brain-muscle interactions and enhancing the coupling between cortical and muscular systems.