Dynamic Multi-Modal Neuron Models and Consciousness Simulation

Abstract

This paper proposes a novel approach to simulating consciousness by developing dynamic multi-modal neuron models. The core idea is to replicate the underlying mechanisms of consciousness by simulating the intricate interactions and information integration between diverse neuronal populations. We construct a model incorporating visual, auditory, and motor modalities, dynamically modeling the connections and information transfer between them. Utilizing feedback loops and synaptic plasticity, the model aims to capture the subjective experience and cognitive processes associated with consciousness. This research represents a significant departure from existing neuron models by explicitly incorporating dynamic multi-modality and the simulation of consciousness itself. The model's architecture and operational principles are detailed, providing a framework for future research into the fundamental origins of consciousness. Ultimately, this work seeks to establish a computational foundation for understanding how subjective experience arises from the complex dynamics of the brain.