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Associative learning, a key higher-order function of biological synapses, remains challenging to implement in hardware due to limitations in existing memristor architectures. Here we develop a four-terminal TiO2-x memristor enabling two-dimensional control of oxygen vacancy distributions, exhibiting stable non-filamentary resistive switching accompanied by visible electrocoloring with voltages. Using a single four-terminal device, we demonstrate bidirectional Pavlovian conditioning encompassing both learning and forgetting processes. Furthermore, by arranging multiple memristors based on this architecture, multidimensional associative learning of two-dimensional image data is realized without involving any external circuits or computing units. These findings indicate that the proposed memristor architecture functions as a self-contained physical learning element capable of acquiring and updating associations between stimuli. This work thus provides a conceptual framework for neuromorphic hardware that implements higher-order associative functions, advancing beyond conventional software-based artificial neural networks.

権利情報:

• Creative Commons BY Attribution 4.0 International
  

キーワード: memristor

刊行年月日: 2026-09-09

出版者: Wiley

掲載誌:

• physica status solidi (a) (ISSN: 18626319) vol. 223 issue. 17 e70507

研究助成金:

• Japan Society for the Promotion of Science JP19K04468
• Japan Society for the Promotion of Science JP20H00248
• Japan Society for the Promotion of Science JP21K18723
• Japan Society for the Promotion of Science JP23H01687
• Japan Society for the Promotion of Science JP23K26380
• Japan Society for the Promotion of Science JP24K00926
• Japan Society for the Promotion of Science JP24K21620

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1002/pssa.70507

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更新時刻: 2026-09-16 16:06:29 +0900

MDRでの公開時刻: 2026-09-16 18:26:07 +0900