Frequency-specific intermuscular coherence of synergistic muscles during an isometric force generation task

Motor tasks require the flexible selection and coordination of multiple muscles, which may be achieved through the organization and combination of muscle synergies. Although multiple muscles may receive a shared neural drive, and each muscle may also receive distinct neural inputs, there is ongoing debate about whether synergies accurately reflect shared neural drives. This study aimed to compare the spectral characteristics of the common drive shared among muscles within the same synergy to those shared among muscles belonging to different synergies.

Electromyographic signals were recorded from upper limb muscles during an isometric multi-directional force generation task. Synergies were identified using non-negative matrix factorization (NMF), and coherence analysis was conducted to evaluate common drives among muscles within and across synergies. A methodological limitation of previous studies was to segment muscle activity into standard frequency bands. Here, we overcome it by proposing to automatically detect subject-specific and physiologically relevant frequency layers. The application of NMF on the coherence spectra of muscle pairs as a method for automatically detecting physiologically relevant frequency bands sheds light into the neural basis of muscle coordination.

Six frequency layers were identified, and muscle recruited within the same synergy showed a higher coherence within layers in the delta, alpha, and low-beta bands.

Our findings enhance the understanding of physiological mechanisms of motor coordination by elucidating the relationship between muscle synergies and the spectral characteristics of intermuscular coherence.