State Space Theory as a Unifying Framework for Consciousness.

Area of Science:

• Neuroscience
• Cognitive Science
• Theoretical Physics

Background:

• Consciousness science lacks a unified mechanistic framework, with theories operating at disparate explanatory levels.
• A principled account linking conscious experience to specific neural computations is absent.
• Existing theories struggle to integrate diverse aspects of conscious experience.

Purpose of the Study:

• To propose State Space Theory (SST) as a unifying mechanistic framework for consciousness science.
• To demonstrate how SST provides a computational foundation for understanding consciousness.
• To mechanistically ground existing cognitive theories within a single architecture.

Main Methods:

• Utilizing hierarchical delay coordinate embedding (DCE) as the core mechanism for consciousness.
• Implementing DCE through recurrent cortical circuits ('DCE engines') with gain modulation.
• Drawing on empirical evidence of recurrent networks learning via embedding and mathematical links between recurrent dynamics and embedding theory.

Main Results:

• SST posits consciousness arises from DCE, not merely correlates.
• Major cognitive theories map onto the SST architecture mechanistically (e.g., competing drafts, global broadcasting).
• SST resolves theoretical challenges like the unfolding argument and temporal paradox.

Conclusions:

• SST offers a unifying, process-based computational framework for consciousness.
• The theory generates falsifiable predictions regarding perceptual dynamics and temporal vulnerability.
• SST provides a foundation for integrating diverse theories and guiding future empirical research in consciousness science.