RIFT: A Fractal-Holographic Theory of Consciousness and Autopoietic Control

Area of Science:

• Neuroscience
• Cognitive Science
• Theoretical Physics

Background:

• Current consciousness theories often view it as an epiphenomenal correlate of neural activity.
• A significant gap exists in explaining how subjective experience causally influences its neural substrate.

Purpose of the Study:

• To present Recurrent Integration Fractal Theory (RIFT) as a novel framework for understanding consciousness.
• To propose a mechanism by which consciousness acts as a causally efficacious force, rather than being merely epiphenomenal.

Main Methods:

• RIFT posits consciousness emerges from fractal compression of sensory information, creating a holographic 'endospace'.
• Neural networks with fractal dendritic trees facilitate information integration via coincidence-based synaptic selection.
• Multifractals, Ising lattices of ion channels and lipids, encode a fractal 'Self-attractor' that generates the endospace.

Main Results:

• The RIFT model computationally validates against core consciousness properties: irreducibility, information integration, and holographic encoding.
• Generational Fractal Mapping allows for incremental updating of experience and temporal continuity of the Self.
• The Self modulates neural activity through lipid domains, influencing ion channel function and action potential generation.

Conclusions:

• RIFT provides a testable model where consciousness is causally efficacious, emerging from fractal information processing.
• The theory generates predictions regarding lipid disruption in Alzheimer's disease and fractal signatures of conscious states.
• RIFT offers criteria for assessing consciousness in artificial systems exhibiting autopoietic feedback.