Short-term synaptic plasticity in emerging devices for neuromorphic computing

Chao Li; Xumeng Zhang; Pei Chen; Keji Zhou; Jie Yu; Guangjian Wu; Du Xiang; Hao Jiang; Ming Wang; Qi Liu

iScience (Apr 2023)

Short-term synaptic plasticity in emerging devices for neuromorphic computing

Chao Li,
Xumeng Zhang,
Pei Chen,
Keji Zhou,
Jie Yu,
Guangjian Wu,
Du Xiang,
Hao Jiang,
Ming Wang,
Qi Liu

Affiliations

Chao Li: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Key Laboratory of Microelectronics Device & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
Xumeng Zhang: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China; Shanghai Qi Zhi Institute, Shanghai 200232, China; Corresponding author
Pei Chen: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
Keji Zhou: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China; Shanghai Qi Zhi Institute, Shanghai 200232, China
Jie Yu: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
Guangjian Wu: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China; Shanghai Qi Zhi Institute, Shanghai 200232, China
Du Xiang: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China; Shanghai Qi Zhi Institute, Shanghai 200232, China; Corresponding author
Hao Jiang: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China; Shanghai Qi Zhi Institute, Shanghai 200232, China
Ming Wang: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China; Shanghai Qi Zhi Institute, Shanghai 200232, China
Qi Liu: State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China; Shanghai Qi Zhi Institute, Shanghai 200232, China; Corresponding author

Journal volume & issue: Vol. 26, no. 4
p. 106315

Abstract

Read online

Summary: 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.

Published in iScience

ISSN: 2589-0042 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Science
Website: http://www.cell.com/iscience/home

About the journal

Abstract

Keywords