Structural–Dynamical Coupling in Neuronal Models: Integrating Geometry, Topology, and Dynamics from Development to Function

Precision modeling is a rapidly expanding field within the domain of complex biological systems, focusing on understanding and predicting intricate system behaviors through advanced computational and mathematical approaches. This area employs techniques such as chaos theory and agent-based modeling to unravel the nonlinear and dynamic interactions characteristic of biological systems. By leveraging these innovative approaches, researchers have begun addressing longstanding challenges associated with the inherent complexity and unpredictability of biological processes, ultimately driving progress in disciplines including systems biology, ecology, and biomedical sciences.Recent developments underscore the effectiveness of chaos theory in elucidating the seemingly erratic dynamics observed within biological systems. This has opened new avenues for understanding stability, oscillations, and bifurcations in such systems. Simultaneously, agent-based modeling has proven crucial for simulating the behavior and interactions of individual entities, yielding valuable insights into emergent phenomena and system-level outcomes. Despite these advances, challenges remain, notably in enhancing the precision of these models and ensuring their applicability across diverse biological contexts.This Research Topic aims to explore and develop precision modeling techniques intended to dissect and predict the behavior of complex biological systems. Through the refinement of mathematical and computational tools, the overarching goal is to deepen understanding of complex system dynamics and improve predictive capabilities.To gather further insights into precision modeling within complex systems, we welcome articles addressing, but not limited to, the following themes:• Application of chaos theory in biological systems modeling• Advances in agent-based modeling for complex system analysis• Dynamics of nonlinear interactions and emergent behavior in biological systems• Real-world case studies demonstrating precision modeling applications• Challenges and innovations in computational approaches to complex system predictionsArticle types accepted include original research, reviews, and perspectives that focus on refining and applying mathematical and computational models to better understand and predict the behaviors of complex biological systems. Topic editors: Ali H Rafati, Paul Bogdan Source: https://www.frontiersin.org/research-topics/80955/structural-dynamical-coupling-in-neuronal-models-integrating-geometry-topology-and-dynamics-from-development-to-function