Emergent Consciousness Simulation (SIM)

Abstract

This paper proposes a novel approach to understanding consciousness, termed Emergent Consciousness Simulation (SIM). The core claim is that consciousness emerges from the specific scale and interaction patterns within neural networks. SIM leverages large-scale parallel computing to construct a simulated neural network incorporating self-organizing modules and feedback loops, mirroring hypothesized neural structures involved in consciousness. The simulation aims to capture the dynamic states within this network, allowing for the inference of key characteristics associated with conscious experience. Unlike existing cognitive models which often focus on functional intelligence, SIM directly addresses the underlying mechanisms driving consciousness, prioritizing a fundamental understanding of its nature. This approach utilizes a system of equations to model key aspects of the simulated network, including neuronal firing rates, synaptic plasticity, and feedback dynamics. The simulation's primary output will be a dynamic state representation of the network, which will then be analyzed to identify patterns consistent with known correlates of consciousness. This research offers a new paradigm for investigating the nature of consciousness, moving beyond purely computational models of intelligence to a simulation-based approach focused on the emergence of subjective experience.