Dynamics of cardio‐muscular networks in exercise and fatigue

A fundamental question in cardiovascular and muscle physiology is how the heart operates in synchrony with distinct muscles to regulate homeostasis, enable movement and adapt to exercise demands and fatigue. Here we investigate how autonomic regulation of cardiac function synchronizes and integrates as a network with the activity of distinct muscles during exercise. Further, we establish how the network of cardio-muscular interactions reorganizes with fatigue. Thirty healthy young adults performed two body weight squat tests until exhaustion. Simultaneous recordings were taken of a 3-lead electrocardiogram (EKG) along with electromyography (EMG) signals from the left and right vastus lateralis, and left and right erector spinae. We first obtained instantaneous heart rate (HR) derived from the EKG signal and decomposed the EMG recordings in 10 frequency bands (F1-F10). We next quantified pair-wise coupling (cross-correlation) between the time series for HR and all EMG spectral power frequency bands in each leg and back muscle. We uncovered the first profiles of cardio-muscular network interactions, which depend on the role muscles play during exercise and muscle fibre histochemical characteristics. Additionally, we observed a significant decline in the degree of cardio-muscular coupling with fatigue, characterized by complex transitions from synchronous to asynchronous behaviour across a range of timescales. The network approach we utilized introduces new avenues for the development of novel network-based markers, with the potential to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes. KEY POINTS: The heart operates in synchrony with muscles to regulate homeostasis, enable movement, and adapt to exercise demands and fatigue. However, the precise mechanisms regulating cardio-muscular coupling remain unknown. This study introduces a pioneering approach to assess cardio-muscular network interactions by examining the synchronization of cardiac function with muscle activity during exercise and fatigue. We uncover the first profiles of cardio-muscular interactions characterized by specific hierarchical organization of link strength. We observe a significant decline in the degree of cardio-muscular coupling with fatigue, marked by complex transitions from synchronous to asynchronous behaviour. This network approach offers new network-based markers to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes.

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Publication Details

Journal
The Journal of Physiology
Published
2024-10-11
DOI
https://doi.org/10.1113/jp286963
Citations
13
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
5.23

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article

Dynamics of cardio‐muscular networks in exercise and fatigue

Sergi García‐Retortillo, Plamen Ch. Ivanov
13 citations
The Journal of Physiology
Heart Rate Variability and Autonomic Control
5.23
article

Dynamics of cardio‐muscular networks in exercise and fatigue

Sergi García‐Retortillo, Plamen Ch. Ivanov
article en
13 citations

Abstract

A fundamental question in cardiovascular and muscle physiology is how the heart operates in synchrony with distinct muscles to regulate homeostasis, enable movement and adapt to exercise demands and fatigue. Here we investigate how autonomic regulation of cardiac function synchronizes and integrates as a network with the activity of distinct muscles during exercise. Further, we establish how the network of cardio-muscular interactions reorganizes with fatigue. Thirty healthy young adults performed two body weight squat tests until exhaustion. Simultaneous recordings were taken of a 3-lead electrocardiogram (EKG) along with electromyography (EMG) signals from the left and right vastus lateralis, and left and right erector spinae. We first obtained instantaneous heart rate (HR) derived from the EKG signal and decomposed the EMG recordings in 10 frequency bands (F1-F10). We next quantified pair-wise coupling (cross-correlation) between the time series for HR and all EMG spectral power frequency bands in each leg and back muscle. We uncovered the first profiles of cardio-muscular network interactions, which depend on the role muscles play during exercise and muscle fibre histochemical characteristics. Additionally, we observed a significant decline in the degree of cardio-muscular coupling with fatigue, characterized by complex transitions from synchronous to asynchronous behaviour across a range of timescales. The network approach we utilized introduces new avenues for the development of novel network-based markers, with the potential to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes. KEY POINTS: The heart operates in synchrony with muscles to regulate homeostasis, enable movement, and adapt to exercise demands and fatigue. However, the precise mechanisms regulating cardio-muscular coupling remain unknown. This study introduces a pioneering approach to assess cardio-muscular network interactions by examining the synchronization of cardiac function with muscle activity during exercise and fatigue. We uncover the first profiles of cardio-muscular interactions characterized by specific hierarchical organization of link strength. We observe a significant decline in the degree of cardio-muscular coupling with fatigue, marked by complex transitions from synchronous to asynchronous behaviour. This network approach offers new network-based markers to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes.

The Journal of PhysiologyVol. 603(18)
Boston University (US), Bulgarian Academy of Sciences (BG), Institute of Biophysics and Biomedical Engineering (BG), Institut Nacional d'Educació Física de Catalunya (ES), Wake Forest University (US), Universitat de Barcelona (ES)
W. M. Keck Foundation, Wake Forest University
Good health and well-being
Openalex Percentile: Top 4%
Heart Rate Variability and Autonomic Control
5.23
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