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ORIGINAL RESEARCH article

Front. Neural Circuits

Volume 19 - 2025 | doi: 10.3389/fncir.2025.1584322

This article is part of the Research TopicNeuro-inspired computationView all 9 articles

Deviance Detection and Regularity Sensitivity in Dissociated Neuronal Cultures

Provisionally accepted
  • The University of Tokyo, Bunkyo, Japan

The final, formatted version of the article will be published soon.

Understanding how neural networks process complex patterns of information is crucial for advancing both neuroscience and artificial intelligence. To investigate fundamental principles of neural computation, we studied dissociated neuronal cultures, one of the most primitive living neural networks, on high-resolution CMOS microelectrode arrays and tested whether the dissociated culture exhibits regularity sensitivity beyond mere stimulus-specific adaptation and deviance detection. In oddball electrical stimulation paradigms, we confirmed that the neuronal culture produced mismatch responses (MMRs) with true deviance detection beyond mere adaptation. These MMRs were dependent on the N-methyl-D-aspartate (NMDA) receptors, similar to mismatch negativity (MMN) in humans, which is known to have true deviance detection properties. Crucially, we also showed sensitivity to the statistical regularity of stimuli, a phenomenon previously observed only in intact brains: the MMRs in a predictable, periodic sequence were smaller than those in a commonly used sequence in which the appearance of the deviant stimulus was random and unpredictable. These results challenge the traditional view that a hierarchically structured neural network is required to process complex temporal patterns, suggesting instead that deviant detection and regularity sensitivity are inherent properties arising from the primitive neural network. They also suggest new directions for the development of neuro-inspired artificial intelligence systems, emphasizing the importance of incorporating adaptive mechanisms and temporal dynamics in the design of neural networks.

Keywords: neuronal culture, deviance detection, CMOS microelectrode array, neural computation, NMDA receptor, plasticity

Received: 27 Feb 2025; Accepted: 04 Aug 2025.

Copyright: © 2025 Zhang, Yaron, Akita, Shiramatsu, Chao and Takahashi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Hirokazu Takahashi, The University of Tokyo, Bunkyo, Japan

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