Embedding Operant Conditioning Functions in a Four-Terminal Memristor

We present an all-in-one operant conditioning (OC) implementation in a single four-terminal memristor, requiring no external circuits or logic. Unlike conventional two-terminal devices, our multi-terminal architecture enables true co-localization of learning functions, supporting both heterosynaptic plasticity and synaptic competition. The operant training process can be scheduled via controlled dopant-ion migration, precisely modulated by a bulk-switching mechanism of our device. This process is visualized via electrochromism, enhancing the interpretability of brain-inspired computation in our device. Our work offers a compact, higher-order functional hardware platform for neuromorphic computing, paving the way toward large-scale neuromorphic systems with embedded learning functionality.

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Publication Details

Journal
ACS Applied Electronic Materials
Published
2026-06-27
DOI
https://doi.org/10.1021/acsaelm.6c00586
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Embedding Operant Conditioning Functions in a Four-Terminal Memristor

Yusuke Hayashi, Tetsuya Tohei, Ryohei Yamamoto, Zhuo Diao et al.
ACS Applied Electronic Materials
Advanced Memory and Neural Computing
article

Embedding Operant Conditioning Functions in a Four-Terminal Memristor

Yusuke Hayashi, Tetsuya Tohei, Ryohei Yamamoto, Zhuo Diao, Akira Sakai, Hayato Kamitsuna, Zijie Meng
article en

Abstract

We present an all-in-one operant conditioning (OC) implementation in a single four-terminal memristor, requiring no external circuits or logic. Unlike conventional two-terminal devices, our multi-terminal architecture enables true co-localization of learning functions, supporting both heterosynaptic plasticity and synaptic competition. The operant training process can be scheduled via controlled dopant-ion migration, precisely modulated by a bulk-switching mechanism of our device. This process is visualized via electrochromism, enhancing the interpretability of brain-inspired computation in our device. Our work offers a compact, higher-order functional hardware platform for neuromorphic computing, paving the way toward large-scale neuromorphic systems with embedded learning functionality.

ACS Applied Electronic Materials
Toneyama National Hospital (JP), The University of Osaka (JP)
Kyoto Technoscience Center, Japan Society for the Promotion of Science
Openalex Percentile: Top 10%
Advanced Memory and Neural Computing
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