Short-term synaptic plasticity in emerging devices for neuromorphic computing

• Published in: iScience 2023-04, Vol.26 (4), p.106315-106315, Article 106315
• Main Authors: Li, Chao, Zhang, Xumeng, Chen, Pei, Zhou, Keji, Yu, Jie, Wu, Guangjian, Xiang, Du, Jiang, Hao, Wang, Ming, Liu, Qi
• Format: Article
• Language: English
• Subjects: Applied computing; Devices; Engineering
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2023.106315

Neuromorphic computing is a promising computing paradigm toward building next-generation artificial intelligence machines, in which diverse types of synaptic plasticity play an active role in information processing. Compared to long-term plasticity (LTP) forming the foundation of learning and memory, short-term plasticity (STP) is essential for critical computational functions. So far, the practical applications of LTP have been widely investigated, whereas the implementation of STP in hardware is still elusive. Here, we review the development of STP by bridging the physics in emerging devices and biological behaviors. We explore the computational functions of various STP in biology and review their recent progress. Finally, we discuss the main challenges of introducing STP into synaptic devices and offer the potential approaches to utilize STP to enrich systems’ capabilities. This review is expected to provide prospective ideas for implementing STP in emerging devices and may promote the construction of high-level neuromorphic machines. [Display omitted] Applied computing; Engineering; Devices