About this Research Topic

Background

The emerging field of Network Physiology integrates empirical and theoretical knowledge from various disciplines to gain insights into the dynamic interactions of physiological systems as a network. These interactions between organs are fundamental for maintaining homeostasis and ensuring overall health. Investigating these interactions is highly relevant in both clinical and foundational research, as disruptions in these mechanisms can lead to diseases linked to organ dysfunction. The widespread availability of easy-to-use wearable devices has facilitated a more comprehensive study of physiological interactions due to their ability to non-invasively acquire synchronous signals from multiple physiological systems.

Physiological interactions can be classified as occurring either within a single system or between different systems. In the former case, the human brain is one of the most studied systems. As the control center of the body, analyzing brain connectivity—how different regions of the brain communicate—enhances our understanding of cognitive, emotional, and sensorimotor processes. In the latter case, recent evidence highlights the importance of investigating functional interactions between the brain and the heart, as these interactions underlie the activity of both the autonomic and central nervous systems, which are interconnected through anatomical and functional links. Beyond brain-heart interactions, the network that regulates homeostasis involves other physiological rhythms, including respiratory activity, cardiovascular and baroreflex functions, and other less-studied yet significant indicators like muscular and ocular activities.

However, a key challenge remains: developing novel data-driven approaches and time-series analysis techniques capable of reliably quantifying interactions within and between different physiological systems based on biomedical signals recorded from various organs.

This Research Topic aims to address this gap by introducing new methods and mathematical tools to study and characterize the internal dynamics of individual physiological systems (e.g., brain, heart, muscles) as well as the dynamic couplings between the brain, cardiac, respiratory, and vascular systems. Additionally, it seeks to uncover emergent behaviors arising from higher-order interactions, i.e., interactions involving three or more physiological systems.

Furthermore, this research highlights the application of established methods to study brain connectivity and brain-body interactions in various physiological conditions (e.g., stress, sleep, cognitive workload) and pathological states (e.g., chronic diseases, stroke, depression, Parkinson’s disease). A promising frontier in this area is the application of Network Physiology to brain-machine interactions, where modulation of physiological network links can serve as a key feature. These interactions hold potential for advanced neurorehabilitation treatments, allowing for adaptive interventions that target specific physiological couplings. By studying how the dynamic coupling between different brain regions and other bodily systems can be harnessed, brain-machine interfaces could be fine-tuned to support motor recovery and cognitive rehabilitation, especially in patients with neurological impairments.

Through this Research Topic, we hope to deepen our understanding of brain connectivity and brain-body interactions in both healthy and pathological conditions, while providing evidence of how these interactions modulate across different physiological states. Focusing on Network Physiology, this research welcomes contributions that explore brain networks, cardiovascular and cardiorespiratory systems, as well as broader system interactions and organ networks.

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
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

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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
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Brain-Machine Interfaces, Network Physiology, Data-driven approaches, Brain connectivity, Brain-Heart interactions, Time series analysis, Higher-order interactions

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