The relationship between matter and spirit is one of the oldest and most profound puzzles in philosophy. Cartesian dualism separates them into two substances, materialism reduces spirit to a property of matter, and idealism regards matter as a manifestation of spirit—none of which provide a self-consistent ontological account. This paper develops a solution within the framework of Energy-Efficiency Theory (EET) based on three axioms. We propose Hierarchical Monism: matter is the steady-state structure of energy under low-level constraints (bound state), information is the texture of energy distribution, and spirit is the inertial consolidation of information in cognitive systems—a higher-order constraint state. All three are manifestations of the same energy ontology, differing only in organizational level and constraint strength. The core innovations are: (1) a hierarchical nested model of "matter-information-spirit" with a quantitative definition of spirit M = k·τ·Eb/Ėₘain, connecting to EET's core parameters; (2) a dynamical pathway for spirit-matter interaction grounded in Yang's Ben-Shi Sliding equation, resolving the interaction problem of dualism; (3) a deep dialogue with Integrated Information Theory (IIT), Global Workspace Theory (GWT), the Chinese Room Argument, the Hard Problem of Consciousness, and quantum consciousness theories (Orch-OR), clarifying the academic contribution of energy ontology; (4) quantitative boundaries and transition conditions across physical, biological, and cognitive layers via constraint barrier Eb and energy dissipation rate Ė, with three falsifiable predictions including statistical power validation. The framework is compatible with existing neuroscientific data on synaptic constraint strength and conscious access mechanisms. This paper ends the millennia-old mind-body dichotomy and provides a unified foundation for cognitive science, psychology, and medicine, establishing "energy ontology" as a systematic position in the philosophy of mind.
Building similarity graph...
Analyzing shared references across papers
Loading...
Hongpu Yang (Thu,) studied this question.
synapsesocial.com/papers/69cb6526e6a8c024954b939f — DOI: https://doi.org/10.5281/zenodo.19301632
Hongpu Yang
Building similarity graph...
Analyzing shared references across papers
Loading...