Network Physiology of Exercise: A New Lens to Understand Aging and Falls

Falls are major public health problems, affecting an estimated 26.5% of older adults globally. They result from dysfunction across multiple systems - e.g., neuromuscular, cardiovascular, respiratory - particularly in the context of movement and exercise. While extensive research has shown how aging impairs individual physiological systems, emerging evidence suggests that coordination between skeletal muscles and organ systems is essential for preserving function, potentially reducing vulnerability to functional decline and falls.

Despite significant advances in aging research, a crucial knowledge gap remains: how do distinct muscles and organ systems dynamically coordinate as a network during exercise, and how does this coordination deteriorate with aging? Addressing this question is key to understand multisystem disruption in aging, and to develop network-based markers that detect the early functional decline commonly associated with falls.

The field of Network Physiology emerged to address this gap, offering a conceptual and analytical framework to study the human organism as a dynamic, adaptive network of muscles and organ systems. By leveraging tools from statistical physics and nonlinear dynamics, the branch of Network Physiology of Exercise provides unique insights into physiological coordination that cannot be captured by traditional aging markers (e.g., muscle strength, balance, heart rate variability, oxygen consumption). Recent studies in older adults have revealed a consistent breakdown in network coordination during distinct exercise modes. Since balance requires precise coordination of muscle activity, cardiovascular output, respiration, and others, disruption of these interactions may represent a key mechanism linking aging to functional decline and fall risk.

This Research Topic invites researchers from diverse disciplines to contribute work advancing our knowledge of how multisystem network coordination deteriorates with aging, especially in the context of exercise and movement. We welcome original research articles that apply dynamic network-based approaches to study physiological coordination in older adults, including but not limited to: inter-muscular, cortico-muscular, cardio-muscular, respiratory-muscular networks, and others. Perspectives, opinion, and methodological papers introducing novel analytical frameworks, network markers, or computational tools are welcome. Contributions that bridge disciplines—such as neuroscience, exercise physiology, geriatrics, rehabilitation, or complex systems science—are particularly encouraged. This Research Topic aims to establish a foundation for network-based markers of functional decline, and to stimulate cross-disciplinary efforts that inform strategies to reduce fall risk and promote healthy aging.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Network Physiology, Falls, Frailty, Sarcopenia, Functional Decline, Older Adults, Training, Fatigue, Exercise Testing, Muscle Networks, Complex Systems, Physiological Interactions, Synchronization, Coupling, Dynamic systems, Functional connectivity, Nonlinear Dynamics, Computational Physiology, Adaptive Dynamic Networks

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.