Latching chains in K-nearest-neighbor and modular small-world networks

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 海洋信息技术装备中心

	Latching chains in K-nearest-neighbor and modular small-world networks
	Song SM(宋三明); Yao HX(姚鸿勋); Simonov, Alexander Yurievich
刊名	NETWORK-COMPUTATION IN NEURAL SYSTEMS
	2015
卷号	26 期号:1 页码:1-24
关键词	Associative retrieval latching chain modular structure Potts network sequential activity small-world
ISSN号	0954-898X
通讯作者	宋三明
产权排序	1
中文摘要	Latching dynamics retrieve pattern sequences successively by neural adaption and pattern correlation. We have previously proposed a modular latching chain model in Song et al. (2014) to better accommodate the structured transitions in the brain. Different cortical areas have different network structures. To explore how structural parameters like rewiring probability, threshold, noise and feedback connections affect the latching dynamics, two different connection schemes, K-nearest-neighbor network and modular network both having modular structure are considered. Latching chains are measured using two proposed measures characterizing length of intra-modular latching chains and sequential inter-modular association transitions. Our main findings include: (1) With decreasing threshold coefficient and rewiring probability, both the K-nearest-neighbor network and the modular network experience quantitatively similar phase change processes. (2) The modular network exhibits selectively enhanced latching in the small-world range of connectivity. (3) The K-nearest-neighbor network is more robust to changes in rewiring probability, while the modular network is more robust to the presence of noise pattern pairs and to changes in the strength of feedback connections. According to our findings, the relationships between latching chains in K-nearest-neighbor and modular networks and different forms of cognition and information processing emerging in the brain are discussed.
WOS标题词	Science & Technology ; Technology ; Life Sciences & Biomedicine
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Neurosciences
研究领域[WOS]	Computer Science ; Engineering ; Neurosciences & Neurology
关键词[WOS]	NEURAL-NETWORKS ; ASSOCIATIVE MEMORY ; CORTICAL ACTIVITY ; FRONTAL-CORTEX ; BRAIN NETWORKS ; MODELS ; NEURONS ; LANGUAGE ; DYNAMICS
收录类别	SCI
语种	英语
WOS记录号	WOS:000352479200001
内容类型	期刊论文
源URL	[http://ir.sia.ac.cn/handle/173321/16129]
专题	沈阳自动化研究所_海洋信息技术装备中心
推荐引用方式 GB/T 7714	Song SM,Yao HX,Simonov, Alexander Yurievich. Latching chains in K-nearest-neighbor and modular small-world networks[J]. NETWORK-COMPUTATION IN NEURAL SYSTEMS,2015,26(1):1-24.
APA	Song SM,Yao HX,&Simonov, Alexander Yurievich.(2015).Latching chains in K-nearest-neighbor and modular small-world networks.NETWORK-COMPUTATION IN NEURAL SYSTEMS,26(1),1-24.
MLA	Song SM,et al."Latching chains in K-nearest-neighbor and modular small-world networks".NETWORK-COMPUTATION IN NEURAL SYSTEMS 26.1(2015):1-24.