Quantifying the diverse contributions of hierarchical muscle interactions to motor function

Abstract

The muscle synergy concept suggests that the human motor system is organised into functional modules comprised of muscles working together towards common task-goals. This study offers a nuanced computational perspective to muscle synergies, where muscles interacting across multiple scales have functionally-similar, - complementary and -independent roles. Making this viewpoint implicit to a methodological approach applying Partial Information Decomposition to large-scale muscle activations, we unveiled nested networks of functionally diverse inter- and intra-muscular interactions with distinct functional consequences on task performance. This approachs effectiveness is demonstrated using simulations and by extracting generalisable muscle networks from benchmark datasets of muscle activity. Specific network components are shown to correlate with a) balance performance and b) differences in motor variability between young and older adults. By aligning muscle synergy analysis with leading theoretical insights on movement modularity, the mechanistic insights presented here suggest the proposed methodology offers enhanced research opportunities towards health and engineering applications.