Explaining Consciousness: Two Leading Neurological Models

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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.

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