On Human Consciousness
arXiv Preprint Archive September 11, 2016 Peter Grindrod
Mathematical analysis of small-scale strongly connected neural networks shows they naturally perform non-binary information processing, enabling multiple hypothesis decision-making at the brain's lowest architectural level. Building on this, a proposed "dual hierarchy model"—comprising external physical elements of increasing complexity and internal mental experiences—supports a learning, evolving consciousness. Because the brain can re-conjure subjective feelings at will, these feelings cannot depend on internal noise or instability-driven activity. A consequence is that finite human brains must always be learning or forgetting, and any subjective feeling with a countable infinity of facets can never be learned by zombies or automata, though an evolving brain can experience it increasingly fully, never in totality.