Different propagation speeds of recalled sequences in plastic spiking neural networks

	Different propagation speeds of recalled sequences in plastic spiking neural networks
	Huang, Xuhui1,2,3 ; Zheng, Zhigang 1; Hu, Gang 1; Wu, Si 4,5,6; Rasch, Malte J.4,5,6
刊名	NEW JOURNAL OF PHYSICS
	2015-03-06
卷号	17
关键词	sequential activity recall spiking neural network spike-timing dependent plasticity
英文摘要	Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.
WOS标题词	Science & Technology ; Physical Sciences
类目[WOS]	Physics, Multidisciplinary
研究领域[WOS]	Physics
关键词[WOS]	TIMING-DEPENDENT PLASTICITY ; VISUAL-CORTEX ; FEEDFORWARD NETWORKS ; SYNCHRONOUS SPIKING ; SYNAPTIC PLASTICITY ; STABLE PROPAGATION ; HIPPOCAMPAL REPLAY ; SYNFIRE CHAINS ; SPARSE CODE ; MEMORY
收录类别	SCI
语种	英语
WOS记录号	WOS:000352899100005
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/10739]
专题	自动化研究所_脑网络组研究中心
作者单位	1.Beijing Normal Univ, Dept Phys, Beijing 100875, Peoples R China 2.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing, Peoples R China 3.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China 4.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China 5.Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China 6.Beijing Normal Univ, Ctr Collaborat & Innovat Brain & Learning Sci, Beijing 100875, Peoples R China
推荐引用方式 GB/T 7714	Huang, Xuhui,Zheng, Zhigang,Hu, Gang,et al. Different propagation speeds of recalled sequences in plastic spiking neural networks[J]. NEW JOURNAL OF PHYSICS,2015,17.
APA	Huang, Xuhui,Zheng, Zhigang,Hu, Gang,Wu, Si,&Rasch, Malte J..(2015).Different propagation speeds of recalled sequences in plastic spiking neural networks.NEW JOURNAL OF PHYSICS,17.
MLA	Huang, Xuhui,et al."Different propagation speeds of recalled sequences in plastic spiking neural networks".NEW JOURNAL OF PHYSICS 17(2015).