journal article·2024-07-17

Artificial Multimodal Neuron with Associative Learning Capabilities: Acquisition, Extinction, and Spontaneous Recovery

Sangheon Kim, Unhyeon Kang, Jiyoung Gu, Jaewook Kim, Jongkil Park, Gyu Weon Hwang, Seongsik Park, Hyun Jae Jang, Tae-Yeon Seong, Suyoun Lee

ACS Applied Materials & Interfaces· Volume 16· Issue 28
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Abstract

Associative multimodal artificial intelligence (AMAI) has gained significant attention across various fields, yet its implementation poses challenges due to the burden on computing and memory resources. To address these challenges, researchers have paid increasing attention to neuromorphic devices based on novel materials and structures, which can implement classical conditioning behaviors with simplified circuitry. Herein, we introduce an artificial multimodal neuron device that shows not only the acquisition behavior but also the extinction and the spontaneous recovery behaviors for the first time. Being composed of an ovonic threshold switch (OTS)-based neuron device, a conductive bridge memristor (CBM)-based synapse device, and a few passive electrical elements, such observed behaviors of this neuron device are explained in terms of the electroforming and the diffusion of metallic ions in the CBM. We believe that the proposed associative learning neuron device will shed light on the way of developing large-scale AMAI systems by providing inspiration to devise an associative learning network with improved energy efficiency.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neural dynamics and brain function · Transition Metal Oxide Nanomaterials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Rep. of Korea

Department of Materials Science and Engineering, Korea University, Seoul 02841, Rep. of Korea

Materials Science & Engineering, Seoul National University, Seoul 08826, Rep. of Korea

Department of Materials Science & Engineering, Seoul National University of Science and Technology, Seoul 01811, Rep. of Korea

Division of Nano & Information Technology, Korea University of Science and Technology, Daejon 34316, Rep. of Korea

Funding

National Research Foundation of Korea · Korea Institute of Science and Technology

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