The Book of Consciousness: A Comparative Study of Consciousness Theories from an Interdisciplinary Perspective

This project was released by NoushinN on GitHub on May 24, 2026. Its core goal is to critically compare major consciousness theories from interdisciplinary perspectives including neuroscience, philosophy, cognitive science, artificial intelligence, and physics. Consciousness is one of the deepest puzzles in science and philosophy. By integrating tools and frameworks from different disciplines, the project aims to comprehensively understand the nature of consciousness and provide interdisciplinary insights to solve the puzzle of consciousness.

The core of consciousness research lies in the 'easy problems' and 'hard problem' proposed by Chalmers: easy problems involve functions that can be studied through scientific methods, such as information integration and behavior generation; the hard problem is why physical processes are accompanied by subjective experience (qualia), with an explanatory gap between objective description and subjective experience. The main positions on the mind-body problem include dualism (mind and body are separate), physicalism (mind is brain state), functionalism (mind is defined by functional roles), and emergentism (consciousness is an emergent property of complex systems).

Different disciplines propose various theoretical approaches: Neuroscience has the Global Workspace Theory (GWT, information broadcasting model), Integrated Information Theory (IIT, Φ value measures integrated information), and Higher-Order Theory (consciousness is defined by higher-order representations); Philosophy has the phenomenological tradition (description of first-person experience); Cognitive science has computational functionalism (consciousness is a computational process) and predictive processing theory (the brain is a prediction machine); Physics has quantum consciousness theory (Orch OR, quantum processes in microtubules) and information physics (information as a fundamental element of the universe), etc.

GWT has brain imaging evidence (conscious stimuli activate the prefrontal and parietal lobes, while unconscious stimuli are limited to the sensory cortex); IIT quantifies integrated information through Φ value and predicts that simple systems may have a low degree of consciousness; Higher-Order Theory is supported by research on the role of the prefrontal cortex but faces criticism for its explanation of qualia; Quantum consciousness theory (Orch OR) is highly controversial because the duration of quantum coherence in the brain environment is short; Predictive processing theory explains the relationship between consciousness and prediction accuracy.

The criteria for evaluating consciousness theories include empirical adequacy (explaining neuroscience, psychology, etc., data), explanatory power (unifying consciousness features such as subjectivity, choice, and reportability), simplicity and consistency (compatibility with existing scientific theories), and predictive power (e.g., IIT's predictions about brain regions). Each theory has its strengths and weaknesses; interdisciplinary integration is needed to fully understand consciousness.

Current challenges include objectively measuring subjective experience, determining the scope of consciousness (biology, AI, etc.), explaining altered states (sleep, meditation, etc.), and integrating first-person and third-person perspectives. In the future, we need to advance interdisciplinary methodologies, explore new measurement technologies, pay attention to ethical issues of artificial consciousness, and maintain an open and critical research attitude.