Networks of respiratory-muscular coupling in exercise and fatigue in young adults

Respiratory and muscular systems must integrate ventilation, oxygen delivery, and muscle activation to meet exercise demands. While decades of research have provided understanding of how these systems function individually, the principles regulating their dynamic coupling as a network remain unexplored. Our goal was to investigate how respiratory dynamics synchronize and integrate as a network with the activity of muscles during exercise, and assess how it responds to fatigue. Nine adults performed two graded cycling tests until exhaustion, starting at 0 W with 25 W·min^-1 increments. Continuous synchronous recordings included electromyography (EMG) from right and left vastus lateralis and erector spinae, and respiration waveform via chest belt. Respiratory-muscular coupling was measured using the amplitude-amplitude cross-frequency coupling (ACFC) method. First, breathing rate was extracted from the respiration waveform. Second, EMG signals were decomposed into ten frequency bands [F1-F10], representing distinct neuromuscular processes. Last, cross-correlation coefficients (C) were computed as the ACFC outcome. We uncover novel network maps of respiratory-muscular dynamic interactions. We find that respiratory-muscular networks exhibit a complex hierarchical structure which depends on the role muscles play during exercise. Further, cross-correlations significantly increase with fatigue accumulation during exercise, indicating stronger integration between breathing and muscle activation under rising metabolic demand. This network-level adaptation shows that physiological responses to exercise arise not only from isolated systems, but also from their dynamic interactions as an integrated network. The network physiology approach utilized here contributes to the development of a new class of network-based markers to quantify multisystem interactions underlying human function during exercise.