Origin of the efficiency of spike timing-based neural computation for processing temporal information

doi:10.1016/j.neunet.2022.12.017

	Origin of the efficiency of spike timing-based neural computation for processing temporal information
	Jiang, Zhiwei 1,3; Xu, Jiaming2,3 ; Zhang, Tielin2,3 ; Poo, Mu-ming 1,3,4; Xu, Bo2,3
发表期刊	NEURAL NETWORKS
ISSN	0893-6080
	2023-03-01
卷号	160 页码:84-96
通讯作者	Poo, Mu-ming(mpoo@ion.ac.cn) ; Xu, Bo(xubo@ia.ac.cn)
摘要	Although the advantage of spike timing-based over rate-based network computation has been recog-nized, the underlying mechanism remains unclear. Using Tempotron and Perceptron as elementary neural models, we examined the intrinsic difference between spike timing-based and rate-based computations. For more direct comparison, we modified Tempotron computation into rate-based computation with the retention of some temporal information. Previous studies have shown that spike timing-based computation are computationally more powerful than rate-based computation in terms of the number of computational units required and the capability in classifying random patterns. Our study showed that spike timing-based and rate-based Tempotron computations provided similar capability in classifying random spike patterns, as well as in text sentiment classification and spam text detection. However, spike timing-based computation is superior in performing a task involving discriminating forward vs. reverse sequence of events, i.e., information mainly temporal in nature. Further studies revealed that this superiority required the asymmetry in the profile of the postsynaptic potential (PSP), and that temporal sequence information was converted to biased spatial distribution of synaptic weight modifications during learning. Thus, the intrinsic PSP asymmetry is a mechanistic basis for the high efficiency of spike timing-based computation for processing temporal information.(c) 2022 Elsevier Ltd. All rights reserved.
关键词	Postsynaptic potential Spiking neural network Sequence learning Temporal information processing
DOI	10.1016/j.neunet.2022.12.017
关键词[WOS]	NETWORKS ; PLASTICITY ; NEURONS ; CODE
收录类别	SCI
语种	英语
资助项目	Key Research Program of Frontier Sciences, China, Chinese Academy of Sciences, China[QYZDY-SSW-SMCO01] ; Strategic Priority Research Program of Chinese Academy of Sciences, China[XDB32070100] ; International Partnership Program of Chinese Academy of Sciences, China[153D31KYSB20170059] ; Shanghai Municipal Science and Technology Major Project, China[2018SHZDZX05] ; Shanghai Key Basic Research Project, China[16JC1420201] ; Shanghai Key Basic Research Project, China[18JC1410100]
项目资助者	Key Research Program of Frontier Sciences, China, Chinese Academy of Sciences, China ; Strategic Priority Research Program of Chinese Academy of Sciences, China ; International Partnership Program of Chinese Academy of Sciences, China ; Shanghai Municipal Science and Technology Major Project, China ; Shanghai Key Basic Research Project, China
WOS研究方向	Computer Science ; Neurosciences & Neurology
WOS类目	Computer Science, Artificial Intelligence ; Neurosciences
WOS记录号	WOS:000923418600001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/51414
专题	复杂系统认知与决策实验室
通讯作者	Poo, Mu-ming; Xu, Bo
作者单位	1.Chinese Acad Sci, Inst Neurosci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 4.Shanghai Ctr Brain Sci & Brain Inspired Intelligen, Lingang Lab, Shanghai 200031, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Jiang, Zhiwei,Xu, Jiaming,Zhang, Tielin,et al. Origin of the efficiency of spike timing-based neural computation for processing temporal information[J]. NEURAL NETWORKS,2023,160:84-96.
APA	Jiang, Zhiwei,Xu, Jiaming,Zhang, Tielin,Poo, Mu-ming,&Xu, Bo.(2023).Origin of the efficiency of spike timing-based neural computation for processing temporal information.NEURAL NETWORKS,160,84-96.
MLA	Jiang, Zhiwei,et al."Origin of the efficiency of spike timing-based neural computation for processing temporal information".NEURAL NETWORKS 160(2023):84-96.