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Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks

文献类型：期刊论文

作者Zeng, Guanxiong2,3,4; Huang, Xuhui2,4,5; Jiang, Tianzi1,2,3,4; Yu, Shan1,2,3,4
刊名NEURAL NETWORKS
出版日期2019-10-01
卷号118页码:140-147
关键词Reservoir computing Sequence learning and retrieval Short-term depression Synaptic heterogeneity Self-organized criticality Optimal information processing
ISSN号0893-6080
DOI10.1016/j.neunet.2019.06.002
通讯作者Huang, Xuhui(xuhui.huang@ia.ac.cn) ; Yu, Shan(shan.yu@nlpr.ia.ac.cn)
英文摘要The brain is highly plastic, with synaptic weights changing across a wide range of time scales, from hundreds of milliseconds to days. Changes occurring at different temporal scales are believed to serve different purposes, with long-term changes for learning and memory and short-term changes for adaptation and synaptic computation. By studying the performance of reservoir computing (RC) models in a memory task, we revealed that short-term synaptic plasticity is fundamentally important for long-term synaptic changes in neural networks. Specifically, short-term depression (STD) greatly expands the operational range of a neural network in which it can accommodate long-term synaptic changes while maintaining system performance. This is achieved by dynamically adjusting neural networks close to a critical state. The effects of STD can be further strengthened by synaptic weight heterogeneity, resulting in networks that can tolerate very large, long-term changes in synaptic weights. Our results highlight a potential mechanism used by the brain to organize plasticity at different time scales, thereby maintaining optimal information processing while allowing internal structural changes necessary for learning and memory. (C) 2019 Elsevier Ltd. All rights reserved.
WOS关键词SELF-ORGANIZED CRITICALITY ; NEURONAL AVALANCHES ; CORTICAL NETWORKS ; SYNAPSES ; COMPUTATION ; DEPRESSION ; CAPACITY ; CHAOS ; EDGE
资助项目National Key Research and Development Program of China[2017YFA0105203] ; Natural Science Foundation of China[81471368] ; Natural Science Foundation of China[11505283] ; Natural Science Foundation of China[91732305] ; Natural Science Foundation of China[31620103905] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB32040200] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB32030200] ; Hundred-Talent Program of CAS ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-SMC019]
WOS研究方向Computer Science ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000483920500012
出版者PERGAMON-ELSEVIER SCIENCE LTD
资助机构National Key Research and Development Program of China ; Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) ; Hundred-Talent Program of CAS ; Key Research Program of Frontier Sciences, CAS
源URL[http://ir.ia.ac.cn/handle/173211/27196]  
专题自动化研究所_脑网络组研究中心
通讯作者Huang, Xuhui; Yu, Shan
作者单位1.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Brainnetome Ctr, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
5.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zeng, Guanxiong,Huang, Xuhui,Jiang, Tianzi,et al. Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks[J]. NEURAL NETWORKS,2019,118:140-147.
APA Zeng, Guanxiong,Huang, Xuhui,Jiang, Tianzi,&Yu, Shan.(2019).Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks.NEURAL NETWORKS,118,140-147.
MLA Zeng, Guanxiong,et al."Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks".NEURAL NETWORKS 118(2019):140-147.

入库方式： OAI收割

来源：自动化研究所

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