Consciousness Simulation: Constructing an Ontological Framework

Abstract

This paper proposes a novel approach to understanding consciousness by constructing an ontological framework – a first-person "ontology" – derived from simulating the information processing mechanisms within biological neural systems. The core claim is that consciousness, fundamentally, is an emergent property of complex information processing. We advocate for a bottom-up approach, utilizing large-scale neuron models and dynamic network simulations to progressively build a knowledge graph that reflects an individual's subjective experience. This framework moves beyond merely describing the surface manifestations of consciousness and instead attempts to capture the underlying structure of conscious states and their content. This work outlines the key components of this simulation, focusing on the iterative construction of the ontology through the dynamic evolution of the simulated neural network. The paper introduces the core mechanisms and provides a preliminary theoretical outline for this simulation, highlighting the potential for future research in bridging the gap between neuroscience and the philosophical problem of consciousness. The resulting knowledge graph will represent the subjective experience as a network of interconnected concepts, relationships, and sensory data, offering a potentially quantifiable and testable model of consciousness.