About this Research Topic
Self-organization processes play a fundamental role in the animate and inanimate world. Subtle parameter changes may induce nonequilibrium phase transitions, giving rise to qualitatively different patterns of activity and structure. Intriguingly, while networks can be very different in terms of size as well as underlying units, they may share very similar dynamical principles. Interdisciplinary research from different fields, ranging from computational modeling using non-linear dynamics and statistical physics to sophisticated data analysis techniques, enables to understand and control complex networks. Historically, one branch of this type of research is Synergetics, a self-organization theory that originated from laser quantum physics, initially developed to describe nonequilibrium phase transitions in the laser and, later, extended to numerous applications in physics, physiology, neuroscience, neurology and psychology.
The Research Topic is to honor the memory of Hermann Haken, a pioneer of laser quantum physics and the founder of Synergetics, who passed away on August 14, 2024.
This Research Topic aims at providing a comprehensive overview of current computational modeling and data analysis techniques that are used to cope with complex physiological networks and their range of potential applications. For instance, articles will explain how concepts of nonequilibrium phase transitions and bifurcations may be used for the study and control of physiological networks. Articles will highlight and tackle open questions related to the underlying mathematical methods and dynamic principles, e.g., low-dimensional representations of complex networks and critical fluctuations close to bifurcation points. In addition, articles will explain how these dynamical principles, that evolved in an interdisciplinary framework, ultimately got established for the study and control in various fields ranging from physiology to neuroscience, neurology and psychology.
The articles in this collection can be either review articles or original research articles. They should address one or more of the following broad themes;
• Methods from nonlinear dynamics and statistical physics for modelling complex systems, in a general context and specifically as it relates to humans and animals and their complex physiological networks.
• Modeling studies related to bifurcations and nonequilibrium phase transitions in complex physiological networks.
• Data analysis tools designed to capture and detect self-organization processes and phase transitions in physiological networks.
• Studies inspired by both methods and the spirit of synergetics, in particular, in the field of network physiology, neuroscience, neurology, and psychology.
• Articles about how the understanding of self-organization unfolded and shaped the study of complex physiological networks.
The Research Topic is to honor the memory of Hermann Haken, a pioneer of laser quantum physics and the founder of Synergetics, who passed away on August 14, 2024.
This Research Topic aims at providing a comprehensive overview of current computational modeling and data analysis techniques that are used to cope with complex physiological networks and their range of potential applications. For instance, articles will explain how concepts of nonequilibrium phase transitions and bifurcations may be used for the study and control of physiological networks. Articles will highlight and tackle open questions related to the underlying mathematical methods and dynamic principles, e.g., low-dimensional representations of complex networks and critical fluctuations close to bifurcation points. In addition, articles will explain how these dynamical principles, that evolved in an interdisciplinary framework, ultimately got established for the study and control in various fields ranging from physiology to neuroscience, neurology and psychology.
The articles in this collection can be either review articles or original research articles. They should address one or more of the following broad themes;
• Methods from nonlinear dynamics and statistical physics for modelling complex systems, in a general context and specifically as it relates to humans and animals and their complex physiological networks.
• Modeling studies related to bifurcations and nonequilibrium phase transitions in complex physiological networks.
• Data analysis tools designed to capture and detect self-organization processes and phase transitions in physiological networks.
• Studies inspired by both methods and the spirit of synergetics, in particular, in the field of network physiology, neuroscience, neurology, and psychology.
• Articles about how the understanding of self-organization unfolded and shaped the study of complex physiological networks.
Keywords: synergetics, self-organization, nonequilibrium phase transitions, dynamic networks, activity patterns, emergence, control, synchronization, nonlinear dynamics, neuroscience, neurology, Network Physiology
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.
