Network Physiology and Feedback Control, Vol II

Network Physiology is an emerging interdisciplinary field dedicated to uncovering the complexity of physiological interactions across diverse organ systems in health and disease. Submissions to this Research Topic should be framed within the context of Network Physiology.

Physiological systems often rely on multiple negative feedback loops that operate simultaneously to maintain homeostasis. These multiple feedback mechanisms provide redundancy and thereby robustness, and enable both fast and slow regulatory actions by virtue of different time delays. Both network physiology and control theory thus provide very suitable conceptual frameworks for studying such systems.

Over the past decades, mathematical modeling has been instrumental in analyzing such self-regulated systems, revealing complex dynamics, including the potential emergence of chaos. However, the translation of such theoretical results into clinically relevant scenarios is still underexplored. For instance, a potential clinically relevant application of such research lies in the interaction between patients and medical devices that themselves function based on feedback control principles. Examples include temperature regulation in infant incubators, mechanical ventilation in critically ill patients, and blood glucose management in diabetics using insulin pumps integrated with continuous glucose monitors. Despite the growing prevalence of such devices in healthcare, little attention has been given to the temporal evolution of the physiological variables being regulated—such as core body temperature, oxygen saturation, or blood glucose concentration—within the dynamic interplay of both biological and artificial control mechanisms.

This Research Topic aims to expand our understanding of complex networked physiological systems by integrating approaches from mathematical modeling, computer simulation, and control theory. It seeks to clarify whether chaos and other complex dynamic behaviors result primarily from the interaction of multiple feedback control mechanisms, from different time delays inherent to such mechanisms, or from their joint interplay. Additionally, it aims to establish clearer links between theoretical insights and practical clinical scenarios, particularly scenarios in which medical devices and patients interact via feedback control mechanisms. A key area of interest is understanding how the system's behavior changes as the patient recovers or transitions toward a stable, healthy state, potentially reaching a point where the external regulation provided by the device is no longer necessary. Studying these transitions could inform new methodologies for designing smarter, more adaptive control systems that improve patient outcomes and minimize side effects.

To gather further insights, this Research Topic encompasses studies investigating theoretical, computational, experimental, and clinical aspects of feedback control within network physiology. We specifically encourage original research, reviews, and perspectives related to:
• Theoretical understanding and analysis of multiple feedback loops in physiological networks.
• Impact of time delays in physiological feedback systems and resulting dynamic behaviors, including chaotic phenomena and synchronization.
• Patient-device interaction scenarios, focusing on feedback control devices for clinical interventions such as mechanical ventilation, thermoregulatory control, and glucose management.
• Characterization of dynamical transitions during patient recovery or deterioration, and how such transitions might signal appropriate device withdrawal.
• Improved medical device designs leveraging insights from network physiology, resulting in enhanced therapeutic outcomes and reduced side effects.
• Clinical applications and case studies demonstrating successful translation and validation of theoretical network physiology insights into medical practice.

We particularly invite contributions bridging theoretical formulations with clinical practice, highlighting indications where network physiological insights have tangible clinical impact.

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: chaos, time delayed feedback, nonlinear dynamics, Feedback control, control theory, network physiology, multiple negative feedback loops

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.