Dissociated Neuronal Cultures as Model Systems for Self-Organized Prediction

Amit YaronZhuo ZhangDai AkitaTomoyo Isoguchi ShiramatsuZenas C ChaoHirokazu Takahashi^*

• The University of Tokyo, Bunkyo, Japan

Dissociated neuronal cultures provide a powerful, simplified model for investigating selforganized prediction and information processing in neural networks. This review synthesizes and critically examines research demonstrating their fundamental computational abilities, including predictive coding, adaptive learning, goal-directed behavior, and deviance detection. A unique contribution of this work is the integration of findings on network self-organization, such as the development of critical dynamics optimized for information processing, with emergent predictive capabilities, the mechanisms of learning and memory, and the relevance of the free energy principle within these systems. Building on this, we discuss how insights from these cultures inform the design of neuromorphic and reservoir computing architectures, aiming to enhance energy efficiency and adaptive functionality in artificial intelligence. Finally, this review outlines promising future directions, including advancements in three-dimensional cultures, multi-compartment models, and brain organoids, to deepen our understanding of hierarchical predictive processes in both biological and artificial systems, thereby paving the way for novel, biologically inspired computing solutions. excels in spatial coverage and cellular-level detail, with ongoing advancements continually improving its temporal capabilities.While these in vitro systems offer unparalleled control, accessibility for high-resolution recording and stimulation, and a simplified environment to study fundamental principles of selforganization and computation, it is crucial to acknowledge their inherent limitations. These include the absence of native brain architecture, the lack of structured sensory input experienced in vivo, and patterns of spontaneous activity that can differ from those in intact brains. A careful consideration of these factors is essential when translating findings from dissociated cultures to more complex biological systems, a theme that will be revisited throughout this review.Research using these systems has revealed several fundamental properties of neural network organization and function. As cultures develop, they demonstrate a remarkable capacity for selforganization, evolving from random collections of cells into functional networks that exhibit critical dynamics optimized for information (