Theoretic Model of Consciousness

 

Abstract:

A Set-Theoretic Model of Consciousness Theories

This diagram presents a set-theoretic conceptualization of the relationship between two prominent theories of consciousness: Global Workspace Theory (GWT) and Integrated Information Theory (IIT).

The visualization employs concentric circles to represent the model, positing that GWT encompasses IIT. Specifically, the large outer blue circle represents the Global Workspace Theory, which argues for the broadcasting of information across a distributed cerebral network. The inner blue circle, contained entirely within the GWT set, represents Integrated Information Theory, which posits consciousness is a function of the system's intrinsic irreducible cause-effect power. The diagram illustrates the relationship that all states or processes governed by IIT are also included within the broader scope of GWT processes.

Furthermore, the diagram introduces the concept of 'Consciousness' (C), represented by the orange cloud shape. Arrows indicate that C is not simply equivalent to either set alone, but rather emerges specifically from the overlap between them. This emergent relationship is formally expressed by the red equation at the bottom: the intersection of the Global Workspace Theory set (GWT) and the Integrated Information Theory set (IIT) results in a functional set equivalent to Consciousness (C). Thus, the model suggests that the substrate of conscious experience requires the simultaneous satisfaction of both global broadcasting (GWT) and integrated information (IIT) principles.

Improved image and theory

Critique of Current Limitations

While the set-theoretic model provides a clean integration between Global Workspace Theory (GWT) and Integrated Information Theory (IIT), several theoretical gaps and conceptual limitations exist:

• Ontological Incompatibility: GWT is primarily a functionalist and computational model focusing on information routing and broadcasting, whereas IIT is fundamentally phenomenological and intrinsic (based on physical causality and information geometry). Merging them into simple set intersections () glosses over deep foundational contradictions.
• The Overlap Paradox (Concentric vs. Intersecting Sets): The diagram depicts IIT as a strict subset nested entirely inside GWT. However, many IIT proponents argue that high integrated information () can occur in localized or recurrent cortical circuits without global broadcast, meaning IIT could extend outside GWT. Conversely, GWT processes can occur without the high degree of irreducible integration demanded by IIT. A proper Venn diagram with overlapping or mutually exclusive regions would more accurately reflect these tensions.
• Causality and Dynamics: The model is static (set-theoretic). It fails to capture the dynamic, temporal aspects of consciousness—such as how a global workspace dynamically recruits integrated complexes over time.
• Vagueness of the Emergent Set (): The orange cloud () acts as an external entity pointing to the intersection, but in a rigorous scientific framework, consciousness should be an intrinsic property of the system rather than a separate derived set.

Proposed Improvements

To strengthen and mature this theoretical framework, the model can be expanded and refined in the following ways:

• Transition from Static Sets to Dynamic Phase Spaces: Replace static set intersections with a dynamical systems model. Consciousness can be framed as a trajectory where GWT provides the network topology for routing, and IIT provides the metric of integration () across that topology over time.
• Revise Set Geometry (Venn Diagram): Modify the structural layout from concentric circles to intersecting sets to accurately reflect three zones:
1. GWT-exclusive processes: Non-conscious or pre-conscious global broadcasting (e.g., automated motor routines).
2. IIT-exclusive processes: Localized, highly integrated processing that does not reach global availability.
3. The Intersection (): The true zone of conscious access and phenomenological reportability.
• Incorporate Empirical Markers: Ground the theoretical sets in measurable neural correlates, such as distinguishing feedback connectivity (associated with IIT) from feedforward and frontoparietal synchronization (associated with GWT).