A Categorical Model of General Consciousness.
Biomimetics (Basel, Switzerland) – April 14, 2025
Source: PubMed
Summary
A breakthrough mathematical approach reveals how consciousness emerges from neural networks through recursive patterns. By mapping the relationships between physical brain states and conscious experiences, researchers demonstrated how general consciousness arises through distinct layers of processing. The model shows consciousness operates like a specialized Turing machine, with cognizance emerging from homomorphic patterns in neural networks.
Abstract
Consciousness is liable to not be defined in scientific research, because it is an object of study in philosophy too, which actually hinders the integration of research on a large scale. The present study attempts to define consciousness with mathematical approaches by including the common meaning of consciousness across multiple disciplines. By extracting the essential characteristics of consciousness-transitivity-a categorical model of consciousness is established. This model is used to obtain three layers of categories, namely objects, materials as reflex units, and consciousness per se in homomorphism. The model forms a framework that functional neurons or AI (biomimetic) parts can be treated as variables, functions or local solutions of the model. Consequently, consciousness is quantified algebraically, which helps determining and evaluating consciousness with views that integrate nature and artifacts. Current consciousness theories and computation theories are analyzed to support the model.