Consciousness as an Identity-Preserving Process A Formal State-Space Theory of Self, Anesthesia, and Recovery

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Authors: Christopher E. Keel
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Abstract

This paper presents a formal, dynamical definition of consciousness as an identity-preserving process rather than a phenomenological state, behavioral capacity, or scalar quantity. Using the Recursive Harmonic Collapse Matrix (RHCM), consciousness is defined in terms of the persistence of identity-stabilizing attractor dynamics under native system evolution. The framework separates identity coherence, recurrence density, boundary integrity, access, and experience as distinct but interacting dimensions. This separation resolves long-standing paradoxes surrounding anesthesia, coma, disorders of consciousness, amnesia, recovery integrity, and death without invoking phenomenology, metaphysics, or behavioral proxies. Through formal definitions, simulation results, and falsification criteria, the paper demonstrates that: anesthesia suppresses access without damaging identity, coma degrades identity coherence itself, disorders of consciousness reflect distinct structural failure modes, recovery quality depends on identity drift rather than wakefulness, and death corresponds to irreversible identity attractor collapse. The model is explicitly falsifiable, clinically interpretable, and applicable to biological and artificial systems that exhibit recurrence and attractor dynamics. Consciousness, under this account, is neither mysterious nor reducible to experience alone—it is the dynamical condition that makes identity persistence possible. Subjects / Communities Cognitive Science Computational Neuroscience Systems Neuroscience Complex Systems Dynamical Systems Artificial Intelligence Philosophy of Mind (formal / non-phenomenological)

Fields of Study & Subjects

Philosophy and Theoretical Science Cognitive Science and Education Research Embodied and Extended Cognition

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 February 2026
Document type
Preprint