Qualia as a Universal Principle: A Unified Mathematical Framework for Consciousness, AI, and Cosmic Information

Qualia—the subjective, felt aspect of consciousness—are explained through a new framework that combines neuroscience, AI, thermodynamics, quantum information theory, and cosmic principles. The authors propose that qualia arise from processes of genesis, integration, and optimization driven by entropy minimization, information self-organization, and dynamic feedback that promotes equilibrium. A mathematical model called the qualia equation captures these dynamics as neural, informational, and somatic interactions. The framework includes empirical validation strategies such as AI simulations, neurophysiological studies, neuromorphic computing, and astrophysical research, and incorporates the Self-Organizing Meta-Adaptive (SOMA) model to emphasize the embodied and adaptive nature of qualia. This provides a testable foundation for future consciousness research.

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Abstract

The study of qualia—the subjective, phenomenal aspect of consciousness—remains a major challenge in cognitive science and philosophy. This paper introduces a unified framework integrating neuroscience, artificial intelligence, thermodynamics, quantum information theory, and cosmic principles to explain qualia. We propose that qualia emerge through genesis, integration, and optimization processes driven by entropy minimization, information self-organization, and dynamic feedback mechanisms promoting equilibrium. An advanced mathematical model, the qualia equation, captures the dynamics of qualia as neural, informational, and somatic interactions. We outline empirical validation strategies, including AI-based simulations, neurophysiological studies, neuromorphic computing, and astrophysical research. Incorporating the Self-Organizing Meta-Adaptive (SOMA) model emphasizes the embodied and adaptive nature of qualia. This framework provides a comprehensive, testable foundation for future consciousness research, bridging theoretical philosophy, empirical science, and emerging technologies.