Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks

doi:10.1126/sciadv.abh0146

	Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks
	Zhang, Tielin1,2 ; Cheng, Xiang 1,2; Jia, Shuncheng 1,2; Poo, Mu-Ming 2,3,4,5; Zeng, Yi1,2,4 ; Xu, Bo1,2,4
发表期刊	SCIENCE ADVANCES
ISSN	2375-2548
	2021-10-01
卷号	7 期号:43 页码:11
通讯作者	Xu, Bo(xubo@ia.ac.cn)
摘要	Many synaptic plasticity rules found in natural circuits have not been incorporated into artificial neural networks (ANNs). We showed that incorporating a nonlocal feature of synaptic plasticity found in natural neural networks, whereby synaptic modification at output synapses of a neuron backpropagates to its input synapses made by upstream neurons, markedly reduced the computational cost without affecting the accuracy of spiking neural networks (SNNs) and ANNs in supervised learning for three benchmark tasks. For SNNs, synaptic modification at output neurons generated by spike timing-dependent plasticity was allowed to self-propagate to limited upstream synapses. For ANNs, modified synaptic weights via conventional backpropagation algorithm at output neurons self-backpropagated to limited upstream synapses. Such self-propagating plasticity may produce coordinated synaptic modifications across neuronal layers that reduce computational cost.
DOI	10.1126/sciadv.abh0146
关键词[WOS]	LONG-TERM POTENTIATION ; PROPAGATION ; NEURONS ; MEMORY ; MODEL
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2020AAA0104305] ; National Natural Science Foundation of China[61806195] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA27010404] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB32070000] ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences[QYZDY-SSW-SMCO01] ; International Partnership Program of Chinese Academy of Sciences[153D31KYSB20170059] ; Shanghai Municipal Science and Technology Major Project[2018SHZDZX05] ; Shanghai Key Basic Research Project[18JC1410100]
项目资助者	National Key R&D Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences ; International Partnership Program of Chinese Academy of Sciences ; Shanghai Municipal Science and Technology Major Project ; Shanghai Key Basic Research Project
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000711845800010
出版者	AMER ASSOC ADVANCEMENT SCIENCE
七大方向——子方向分类	类脑模型与计算
引用统计	被引频次：23[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/173211/46360
专题	复杂系统认知与决策实验室_听觉模型与认知计算脑图谱与类脑智能实验室_类脑认知计算
通讯作者	Xu, Bo
作者单位	1.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Neurosci, State Key Lab Neurosci, Shanghai 200031, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 5.Shanghai Ctr Brain Sci & Brain Inspired Intellige, Shanghai 201210, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Tielin,Cheng, Xiang,Jia, Shuncheng,et al. Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks[J]. SCIENCE ADVANCES,2021,7(43):11.
APA	Zhang, Tielin,Cheng, Xiang,Jia, Shuncheng,Poo, Mu-Ming,Zeng, Yi,&Xu, Bo.(2021).Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks.SCIENCE ADVANCES,7(43),11.
MLA	Zhang, Tielin,et al."Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks".SCIENCE ADVANCES 7.43(2021):11.