Integrating predictive coding with reservoir computing in spiking neural network model of cultured neurons

Abstract

The field of physical reservoir computing, which harnesses the dynamics of physical systems for information processing, is undergoing continuous development. The use of cultured neuronal networks as a physical system within physical reservoir computing has played a crucial role in clarifying the connection between neuronal network structure and information processing. In this study, we introduce a model that combines predictive coding and reservoir computing within cultured neurons, serving as a model for sensory information processing. Our findings indicate that the interplay between neuronal network structure and the number of neurons has a significant influence on sensory information processing. This research lays the groundwork for future inquiries into information processing within biological neuronal networks.