Delay Coordinate Embedding as Neuronally Implemented Information Processing: The State Space Theory of Consciousness

Despite intensive effort, a satisfactory scientific theory of consciousness remains elusive. This paper introduces the State Space Theory, aiming to meet key criteria for a theory of consciousness while providing a satisfactory framework consistent with neurobiological and philosophical considerations. The theory posits that the cortex processes information through delay coordinate embedding within recurrent neural networks. These networks create state space representations of reality, forming hierarchical, pseudo-hierarchical, and parallel pathways. Under this theory, consciousness is posited to arise at the highest-order engines in this hierarchy, with complex behavioral options competing within these engines. The theory emphasizes that consciousness is a dynamic process, not representable within a static neuronal state, and develops uniquely in each individual due to history-dependent development of the processing engines.Neuronally, these delay coordinate embedding engines are posited to form recurrent networks that process information by integrating current and past data to reconstruct models of reality, leveraging the power of Takens' Theorem. These engines would themselves exhibit nonlinear dynamics sensitive to initial conditions. This mechanism aligns with the subjective and emergent properties of consciousness, explaining phenomena like binocular rivalry and ambiguous figures. The theory also addresses cortical plasticity and the heuristic nature of cortical processing, aligning with neurobiological evidence supporting the idea that the cortex's information processing is generic rather than specialized.The State Space Theory aligns with and expands upon major theories like Higher-Order Theories, Global Workspace Theories, Integrated Information Theory, and Predictive Processing Theories by providing a computational mechanism for hierarchical integration and recurrent processing. Philosophically, it reconciles dualist intuitions with a monist perspective, positing that consciousness emerges from dynamic brain processes rather than static states. The theory addresses the unity of consciousness and the privacy of subjective experiences, offering a new framework to understand free will within deterministic systems. Future work will refine this theory, exploring its neural mechanisms and validating its predictions, advancing our understanding of consciousness.