Perturbation-Response Dynamic Boundary Emergence (PRDBE): A Dynamical-Systems Framework for Phenomenal Consciousness

This work presents PRDBE (Perturbation-Response Dynamic Boundary Emergence), a process-oriented dynamical-systems framework for phenomenal consciousness, originally inspired by aesthetic perceptual phenomena and generalized to the general problem of con- sciousness science. PRDBE does not attempt to solve the hard problem by reducing qualia to physical processes (as in Dennett’s illusionism), nor does it posit qualia as fundamental properties (as in Chalmers’ property dualism). Instead, it asks under what dynamical condi- tionsa system’sboundary dynamicswill exhibitirreversible, temporally-extended qualitative features associated with subjective experience. The core state variable B denotes the strength of the dynamically-maintained phenom- enal boundary, governed by a dimensionless ordinary differential equation extended with resource-limiting cubic nonlinearity, yielding saddle-node fold bifurcations and hysteresis loopsaccountingfordiscontinuousonsetandcollapseofawareness. Anhour-glasstopological schema maps phenomenological notions such as intentionality onto perturbation-coupling- boundary dynamical processes. Five jointly-necessary criteria define the conditions for gen- uine phenomenal emergence. We derive falsifiable empirical predictions across established experimental paradigms: anaesthesia-awakening transitions, binocular rivalry, psychedelic perturbation, and TMS brain stimulation. A key discriminative prediction distinguishes PRDBE from Integrated Information Theory (IIT): causal integration Φ and phenomenal boundary strength B can decouple, such that high Φ may co-occur with vanishing subjective awareness. This framework bridges static structural measures (e.g. IIT-Φ) and neural correlates of consciousness (NCC), offering a unified mathematical language to translate phenomenolog- ical concepts (intentionality, inner-time-consciousness) into testable dynamical statements. Implications for Carbon-based Intelligence (CBI) are briefly outlined.