Breath–Autonomic–Oscillatory Feedback Loops

Breath–Autonomic–Oscillatory Feedback Loops (BAOFL) is a mechanistic framework describing how breathing rhythms interact with autonomic control circuits to shape physiological state, emotional regulation, and cognitive performance. The model integrates respiratory physiology, vagal pathways, interoceptive signaling, and oscillatory dynamics into a single systems‑level architecture. Rather than treating breathwork or autonomic regulation as isolated techniques, BAOFL maps the underlying feedback loops that couple respiration, heart rate variability, sympathetic–parasympathetic balance, and cortical control. This approach clarifies why specific breathing patterns produce reliable shifts in autonomic state, how oscillatory entrainment emerges, and which intervention parameters matter most for stability and resilience. The framework is designed to be reviewer‑safe, mechanism‑first, and cross‑disciplinary, bridging physiology, neuroscience, psychophysiology, and complex systems. It provides a coherent structure for interpreting empirical findings, generating testable predictions, and guiding the design of targeted interventions for stress, anxiety, and autonomic dysregulation. This OSF project hosts the preprint, figures, and supplementary materials associated with the BAOFL model, along with ongoing updates as the framework expands into multiscale modeling, clinical translation, and computational implementation.