Explaining Consciousness: Two Leading Neurological Models
John Doyle
Preprints.org March 10, 2026 preprint DOI: 10.20944/preprints202603.0738.v1 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper |
|---|---|
| Key points | Argues that IIT and GWT offer distinct explanations of consciousness—one based on intrinsic informational structure, the other on functional accessibility—and contends that recent adversarial testing shows both face substantial empirical challenges, suggesting fundamental conceptual questions must be resolved before either theory can be definitively judged superior. |
Abstract
The question of how consciousness arises from physical systems remains one of the most profound challenges in neuroscience and philosophy. This essay examines two leading models that attempt to explain the emergence of consciousness from both biological and synthetic neural networks: Integrated Information Theory (IIT) and Global Workspace Theory (GWT). Each offers a distinct approach—one grounded in intrinsic informational structure, the other in functional accessibility and cognitive architecture. By comparing their principles, empirical support, and criticisms, this essay aims to clarify how these models contribute to our understanding of consciousness and its potential replication in artificial systems. Recent adversarial testing reveals that both theories face substantial empirical challenges, suggesting the field may need to resolve fundamental conceptual questions before definitive adjudication between theories becomes possible.