Author(s): ABENZA, Ó., GARCIA-RETORTILLO, S., PINZON-ARENAS, J., POSADA-QUINTERO, H., IVANOV, P.C., Institution: UNIVERSITAT DE BARCELONA, Country: SPAIN, Abstract-ID: 321

INTRODUCTION:
Human performance during exercise arises from coordinated interactions among multiple physiological systems operating as an integrated network. Cardiovascular, respiratory, and muscular systems must synchronize ventilation, oxygen delivery, and muscle activation to meet exercise demands. While extensive research has characterized how these systems function individually, the mechanisms regulating their dynamic coupling as a network – and their reorganization with exercise and fatigue – remain not understood. We introduce three novel network-based markers to quantify multisystem coordination between: (i) cardiovascular and muscular systems (cardio-muscular coupling); (ii) respiratory and muscular systems (respiratory-muscular coupling); and (iii) multiple muscles (inter-muscular coupling). The aim was to characterize multisystem coordination during exercise and fatigue. We hypothesized that fatigue would induce a reorganization of multisystem coordination to sustain performance.
METHODS:
Eleven males (21.9 ± 2.7 yrs) and twenty-seven females (22.5 ± 3.9 yrs) completed a graded cycling test to exhaustion, starting at 0 W with 25 W·min-1 increments. Continuous synchronous recordings included three-lead electrocardiography (ECG), respiration waveform (chest belt), and electromyography (EMG) from the bilateral vastus lateralis (VL) and erector spinae (ES). Multisystem coordination was quantified using the Amplitude-Amplitude Cross-Frequency Coupling (ACFC) method. Heart rate and respiratory rate were extracted from ECG and respiration, respectively, and EMG signals were decomposed into ten frequency bands. Pearson correlation coefficients (C) were computed as the ACFC outcome between: (i) heart rate and EMG bands (cardio-muscular); respiratory rate and EMG bands (respiratory-muscular), and (iii) EMG bands across all muscle pairs (inter-muscular). Fatigue was assessed by comparing the Beginning (first third) and End (last third) segments.
RESULTS:
All network-based markers exhibited moderate C values, indicating coordinated multisystem activity (cardio-muscular C = 0.45 ± 0.12; respiratory-muscular C = 0.56 ± 0.05; inter-muscular C = 0.34 ± 0.16). With fatigue, C values increased for cardio-muscular (0.33 ± 0.12 vs. 0.42 ± 0.19; p < 0.05) and respiratory-muscular coupling (0.15 ± 0.12 vs 0.50 ± 0.09; p < 0.01). Inter-muscular coupling exhibited a reorganization pattern, with reduced C between bilateral VL muscles (0.35 ± 0.15 vs. 0.25 ± 0.08; p < 0.05), and increased C for VL-ES and ES-ES (0.18 ± 0.07 vs. 0.31 ± 0.04; p < 0.05).
CONCLUSION:
Fatigue induces a reorganization of multisystem coordination during exercise, characterized by increased cardio-muscular and respiratory-muscular coupling and heterogeneous inter-muscular changes. These findings indicate compensatory network-level adjustments that sustain performance under increasing demands, highlighting that exercise responses emerge not only from individual systems but also from their dynamic coupling as an integrated network.