This paper establishes a unified, mathematically rigorous framework that bridges computational psychiatry, theoretical biophysics, and contemplative neuroscience. It formalizes the interactions between cortical sensory perception Ip (t), physical signal propagation latency taud, the vegetative drives of the biological will Rw (t), and the minimization of variational free energy F (t). Grounded in the principles of active inference, this framework mathematically dismantles the classical assumption of static hedonic states, proving that emotional valence is defined as the negative first temporal derivative of free energy, V (t) = -dF (t) /dt, while emotional acceleration and curvature map to the second temporal derivative, d²F (t) /dt². Introducing the paradigm of Relativistic Active Inference, it is proven that the rate of free energy updates is fundamentally bounded by the conduction velocity of the neural substrate. The analysis demonstrates that a total collapse of sensory fluctuation (where the variance of Ip (t) approaches 0) forces free energy to diverge to infinity, triggering an asymptotic vegetative feedback drive (lim Rw (t) → ∞) which acts as an essential evolutionary pacemaker. Furthermore, affective states are formalized as an allostatic energy buffer governed by the Wundt curve, demonstrating that all action policies intrinsically possess a positive teleological intention directed at maximizing subjective fitness via Expected Free Energy (EFE). Finally, the dynamics of hedonic collapse (the ABC Loop) are integrated through the lens of Allostatic Self-Efficacy (ASE), and the Closed-Loop Precision Governor is formalized. This mechanism shows how valence dynamically dampens or facilitates sensory precision to shield the cortical hierarchy from latency-induced error cascades, providing a mechanistic explanation for clinical derealization, meditative dissolution (bhanga), and the pre-attentive neural acceptance of mortality.
David Foremny (Wed,) studied this question.