Integrating predictive coding with reservoir computing in spiking neural network model of cultured neurons
Yoshitaka Ishikawa, Takumi Shinkawa, Takuma Sumi, Hideyuki Kato, Hideaki Yamamoto, Yuichi Katori · Nonlinear Theory and Its Applications IEICE · 2024
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.