Education for Network Physiology

The multidisciplinary field of Network Physiology offers a valuable opportunity to explore the human body by shifting the focus from individual systems to the network of physiological interactions. The field has been inspired by quantitative approaches in statistical physics, complex systems, and information theory, and aims to address fundamental questions about physiological states in both health and disease. While these efforts have been fruitful, significant barriers to collaboration remain for researchers from different academic communities: for example, those with quantitative backgrounds (such as physics and applied mathematics) and those from more experimental disciplines (such as physiology and biomedical sciences). Often, these barriers arise from differences in terminology and approaches to scientific problems, and from the difficulty physiologists and clinicians face when trying to apply advanced analytical methods developed in quantitative fields.

Optimizing multidisciplinary collaboration requires educational resources that breaks down complex concepts into simpler steps, using shared terminology, thereby facilitating the merging of disciplines. Such resources could be used to update undergraduate, graduate and postgraduate curricula, introducing physiology and biomedical students to the theoretical framework of Network Physiology and to modern methodologies derived from complex systems, nonlinear dynamics, information theory, stochastic processes, data science, networks of dynamical systems, AI, and other topics that are highly relevant to explore how physiological systems cross-communicate and integrate as a network, and would shape the new frontier in medical and basic science education. Likewise, curricula in physics, engineering, and mathematics could be expanded to highlight the complex questions faced by physiologists, emerging methodologies for recording and analysing physiological signals, as well as current understanding of physiological systems in health and disease.

This Research Topic aims to encourage researchers and educators from diverse disciplines to contribute educational resources that support the advancement of network physiology. This may include review articles that explain complex topics and clarify analytical approaches in accessible language to broaden access across disciplines, reports on educational practices (such as experiments or practical sessions) that help in teaching or understanding physiological networks, or examples of effective teaching strategies at different educational levels. We welcome reviews, original research, opinion pieces, perspectives, and technology or code contributions that help train the next generation of scientists who will shape the future developments and frontiers in Network Physiology towards building the Human Physiolome.