Resonant closure: consciousness as a dynamically self-stabilized informational state.

Summary

Phenomenal consciousness arises when an information-processing system achieves a dynamic state of entropic closure, where internal predictions and sensory signals are coupled to minimize informational entropy exchange with the environment while maintaining high internal dynamics. This leads to coherent inference loops that create a persistent pattern of awareness. The framework offers formal constructs and empirical predictions for neurophysiology, distinguishing itself from existing theories like Integrated Information Theory.

Study at a glance

Abstract

Why some physical systems are accompanied by subjective experience remains unresolved in neuroscience and philosophy of mind. Building on predictive processing and the Free Energy Principle, I propose that phenomenal consciousness (what-it-is-like-ness) arises when an information-processing system enters a regime of dynamic entropic closure: a metastable condition in which (i) internally generated predictions and (ii) incoming sensory signals are recursively coupled such that net informational entropy exchange with the environment is minimized while internal informational dynamics remain high. In this regime, inference loops become phase-coherent and self-referential, producing a persistent informational pattern-resonant closure-that constitutes awareness. The framework is compatible with, but conceptually distinct from, Integrated Information Theory and global-workspace style accounts. I formalize core constructs at the level of operational constraints, address objections regarding trivial closure and "stationarity," and derive falsifiable empirical predictions for neurophysiology.

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