A Neurodynamic Manifold of Autonomic Function: Integrating Magnitude and Dynamical Regimes in Heart Rate Variability

The vagal paradox—where elevated vagal activity indexes both safety and shutdown—persists because conventional autonomic metrics quantify fluctuation magnitude while remaining insensitive to the structural organization of underlying dynamics. To address this conceptual gap, I introduce the Neurodynamic Manifold, a topological framework that recontextualizes fluctuation magnitude. By jointly integrating fractal scaling (DFA α 1 ), entropy (Sample Entropy), and Poincaré geometry (SD2/SD1) within a unified dynamical space, the framework maps autonomic activity onto distinct regulatory regimes. It theoretically delineates a quasicritical zone of adaptive complexity, flanked by subcritical and supercritical attractors associated with rigidity and instability. Importantly, it reveals that identical magnitudes may arise from fundamentally opposing dynamical organizations, resolving the vagal paradox and clarifying the interpretative limits of amplitude-based metrics such as RMSSD. By synthesizing clinical physiology, statistical physics, complexity science, and dynamical systems theory, the Neurodynamic Manifold reconceptualizes autonomic health and regulation as the metastable capacity to sustain and navigate the quasicritical regime, providing a unified foundation for translational research and psychophysiological assessment across health, dysfunction, and performance.