Kim, Sangheon Kang, Unhyeon Gu, Jiyoung Kim, Jaewook Park, Jongkil Hwang, Gyu Weon Park, Seongsik Jang, Hyun Jae Seong, Tae-Yeon Lee, Suyoun 2024-07-11T06:30:26Z 2024-07-11T06:30:26Z 2024-07-11 2024-07 1944-8244 https://pubs.kist.re.kr/handle/201004/150219 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. English American Chemical Society Artificial Multimodal Neuron with Associative Learning Capabilities: Acquisition, Extinction, and Spontaneous Recovery Article 10.1021/acsami.4c02343 1 ACS Applied Materials & Interfaces, v.16, no.28, pp.36519 - 36526 ACS Applied Materials & Interfaces 16 28 36519 36526 N scie scopus 001260668000001 2-s2.0-85197433059 Nanoscience & Nanotechnology Materials Science, Multidisciplinary Science & Technology - Other Topics Materials Science Article multimodal associative learning classicalconditioning artificial neuron neuromorphic device