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Updated: Sep 27, 2026

Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
Published on: March 31, 2022
RIFT: A Fractal-Holographic Theory of Consciousness and Autopoietic Control
1Department of Physiology, College of Medicine, University of Kentucky, 741 South Limestone Street BBSRB Room 269, Lexington, KY 40536, USA.
Abstract:
Background/Objectives: Consciousness remains poorly understood as a causative force. Existing theories describe neural correlates or information processing but do not explain how a unified inner experiential space is physically generated or acts back upon its substrate. Recurrent Integration Fractal Theory (RIFT) proposes a three-step mechanism that reconstructs the spatial relationships of the outer world (exospace) within the experiential space of the Self (endospace) and enables autopoietic feedback. Methods: RIFT was examined through six computational modules representing successive transformations from recurrent network activity to endospace generation and feedback. Recurrent loops through fractal dendritic trees generated temporally organized excitatory postsynaptic potentials (EPSPs) and dynamic information integration. Coincident EPSPs programmed somatic multifractals composed of ion channels and membrane lipid domains, producing a fractal Self-attractor (fractal enfolding, Step 1). Coherent point sources derived from this attractor generated a holographic endospace that preserved exospace relationships (holographic unfolding, Step 2), and the reconstructed field modulated lipid-channel coupling and channel opening (autopoietic feedback, Step 3). Generational Fractal Mapping (GFM), in which new EPSPs are mapped onto the compressed fractal seed of the prior state, enables incremental updating, temporal continuity, and Self-attractor transfer. Results: The architecture was validated computationally against three properties specified by RIFT as requirements of consciousness: irreducibility, information integration, and holographic encoding. The simulations also reproduced signatures consistent with conscious access and low-dimensional volitional control. Conclusions: RIFT provides a testable computational framework linking neural activity, endospace generation, and feedback. It predicts effects of lipid-substrate disruption in Alzheimer's disease, fractal signatures of conscious states, and structural criteria for artificial consciousness.
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