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

## TL;DR

This paper proposes that consciousness arises from a self-stabilized informational state where predictions and sensory input are dynamically balanced.

## Contribution

The paper introduces the concept of resonant closure as a novel framework for understanding the emergence of consciousness.

## Key findings

- Resonant closure minimizes entropy exchange while maintaining high internal informational dynamics.
- The framework is distinct from existing theories like Integrated Information Theory.
- The model generates falsifiable predictions for neurophysiological studies.

## 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.