This review describes the investigations of oscillatory complex networks consisting of excitable nodes, focusing on the target wave patterns or say the target wave attractors. A method of dominant phase advanced drivi...This review describes the investigations of oscillatory complex networks consisting of excitable nodes, focusing on the target wave patterns or say the target wave attractors. A method of dominant phase advanced driving （DPAD） is introduced to reveal the dynamic structures in the networks supporting osciUations, such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks. The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns. Therefore, the center （say node A） and its driver （say node B） of a target wave can be used as a label, （A, B）, of the given target pattern. The label can give a clue to conveniently retrieve, suppress, and control the target waves. Statistical investigations, both theoretically from the label analysis and numerically from direct simulations of network dynamics, show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large, and all these attractors can be labeled and easily controlled based on the information given by the labels. The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed.展开更多
This paper investigates antispiral wave breakup phenomena in coupled two-dimensional FitzHugh-Nagumo cells with self-sustained oscillation via Hopf bifurcation. When the coupling strength of the active variable decrea...This paper investigates antispiral wave breakup phenomena in coupled two-dimensional FitzHugh-Nagumo cells with self-sustained oscillation via Hopf bifurcation. When the coupling strength of the active variable decreases to a critical value, wave breakup phenomenon first occurs in the antispiral core region where waves collide with each other and spontaneously break into spatiotemporal turbulence. Measurements reveal for the first time that this breakup phenomenon is due to the mechanism of antispiral Doppler instability.展开更多
显露模式考虑模式在目标类与对立类数据集合中的支持度,首先必须是频繁模式,IncMine是著名的数据流频繁闭合模式挖掘算法。然而,现有的频繁模式挖掘算法面向事务数据流,项集没有类标约束,不能进一步挖掘显露模式用作数据流分类。本文提...显露模式考虑模式在目标类与对立类数据集合中的支持度,首先必须是频繁模式,IncMine是著名的数据流频繁闭合模式挖掘算法。然而,现有的频繁模式挖掘算法面向事务数据流,项集没有类标约束,不能进一步挖掘显露模式用作数据流分类。本文提出一种基于IncMine的显露模式挖掘方法(emerging patterns based on incMine,EPBIM)。EPBIM改进IncMine算法,挖掘带类值约束的频繁闭合项集,并获取显露模式用于贝叶斯分类。在MOA平台上运行多个真实与模拟数据流,实验结果验证了该方法的有效性。展开更多
Self-sustained oscillations in complex networks consisting of long-standing interest in diverse oscillations in random networks natural and social systems nonoscillatory nodes have attracted We study the self-sustaine...Self-sustained oscillations in complex networks consisting of long-standing interest in diverse oscillations in random networks natural and social systems nonoscillatory nodes have attracted We study the self-sustained periodic consisting of excitable nodes. We reveal the underlying dynamic展开更多
Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network,capturing a functional spectrum that ranges from perception and action to abstract cognition.However,how...Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network,capturing a functional spectrum that ranges from perception and action to abstract cognition.However,how this gradient pattern develops and whether its development is linked to cognitive growth,topological reorganization,and gene expression profiles remain largely unknown.Using longitudinal resting-state functional magnetic resonance imaging data from 305 children(aged 6-14 years),we describe substantial changes in the primary-to-transmodal gradient between childhood and adolescence,including emergence as the principal gradient,expansion of global topography,and focal tuning in primary and default-mode regions.These gradient changes are mediated by developmental changes in network integration and segregation,and are associated with abstract processing functions such as working memory and expression levels of calcium ion regulated exocytosis and synaptic transmission-related genes.Our findings have implications for understanding connectome maturation principles in normal development and developmental disorders.展开更多
Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the propertie...Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the properties of biological systems where the influences of excitatory nodes have been extensively investigated while those of inhibitory nodes have been studied much less. In this paper, we consider a model of oscillatory networks of excitable Boolean maps consisting of both excitatory and inhibitory nodes, focusing on the roles of inhibitory nodes. We find that inhibitory nodes in sparse networks （smM1 average connection degree） play decisive roles in weakening oscillations, and oscillation death occurs after continual weakening of oscillation for sufficiently high inhibitory node density. In the sharp contrast, increasing inhibitory nodes in dense networks may result in the increase of oscillation amplitude and sudden oscillation death at much lower inhibitory node density and the nearly highest excitation activities. Mechanism under these peculiar behaviors of dense networks is explained by the competition of the duplex effects of inhibitory nodes.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.11174034,11135001,11205041,and 11305112)the Natural ScienceFoundation of Jiangsu Province,China(Grant No.BK20130282)
文摘This review describes the investigations of oscillatory complex networks consisting of excitable nodes, focusing on the target wave patterns or say the target wave attractors. A method of dominant phase advanced driving （DPAD） is introduced to reveal the dynamic structures in the networks supporting osciUations, such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks. The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns. Therefore, the center （say node A） and its driver （say node B） of a target wave can be used as a label, （A, B）, of the given target pattern. The label can give a clue to conveniently retrieve, suppress, and control the target waves. Statistical investigations, both theoretically from the label analysis and numerically from direct simulations of network dynamics, show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large, and all these attractors can be labeled and easily controlled based on the information given by the labels. The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed.
基金Project supported by the National Natural Science Foundation of China (Grant No. 10675020)by the National Basic Research Program of China (973 Program) (Grant No. 2007CB814800)
文摘This paper investigates antispiral wave breakup phenomena in coupled two-dimensional FitzHugh-Nagumo cells with self-sustained oscillation via Hopf bifurcation. When the coupling strength of the active variable decreases to a critical value, wave breakup phenomenon first occurs in the antispiral core region where waves collide with each other and spontaneously break into spatiotemporal turbulence. Measurements reveal for the first time that this breakup phenomenon is due to the mechanism of antispiral Doppler instability.
文摘显露模式考虑模式在目标类与对立类数据集合中的支持度,首先必须是频繁模式,IncMine是著名的数据流频繁闭合模式挖掘算法。然而,现有的频繁模式挖掘算法面向事务数据流,项集没有类标约束,不能进一步挖掘显露模式用作数据流分类。本文提出一种基于IncMine的显露模式挖掘方法(emerging patterns based on incMine,EPBIM)。EPBIM改进IncMine算法,挖掘带类值约束的频繁闭合项集,并获取显露模式用于贝叶斯分类。在MOA平台上运行多个真实与模拟数据流,实验结果验证了该方法的有效性。
基金Acknowledgements This work was supported by the National Natural Science Foundation of China （Grant Nos. 10675020 and 10975015）, and the National Basic Research Program of China （973 Program） （Grant No. 2007CB814800）.
文摘Self-sustained oscillations in complex networks consisting of long-standing interest in diverse oscillations in random networks natural and social systems nonoscillatory nodes have attracted We study the self-sustained periodic consisting of excitable nodes. We reveal the underlying dynamic
基金supported by the National Natural Science Foundation of China(31830034,82021004,81620108016,31221003,31521063,81671767,82071998,81971690,32130045,and 61761166004)Changjiang Scholar Professorship Award(T2015027)+3 种基金the National Key Research and Development Project of China(2018YFA0701402)Beijing Nova Program(Z191100001119023)the Beijing Brain Initiative of Beijing Municipal Science&Technology Commission(Z181100001518003)the Fundamental Research Funds for the Central Universities(2020NTST29)。
文摘Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network,capturing a functional spectrum that ranges from perception and action to abstract cognition.However,how this gradient pattern develops and whether its development is linked to cognitive growth,topological reorganization,and gene expression profiles remain largely unknown.Using longitudinal resting-state functional magnetic resonance imaging data from 305 children(aged 6-14 years),we describe substantial changes in the primary-to-transmodal gradient between childhood and adolescence,including emergence as the principal gradient,expansion of global topography,and focal tuning in primary and default-mode regions.These gradient changes are mediated by developmental changes in network integration and segregation,and are associated with abstract processing functions such as working memory and expression levels of calcium ion regulated exocytosis and synaptic transmission-related genes.Our findings have implications for understanding connectome maturation principles in normal development and developmental disorders.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 10975015 and 11174034the Fundamental Research Funds for the Central Universities
文摘Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the properties of biological systems where the influences of excitatory nodes have been extensively investigated while those of inhibitory nodes have been studied much less. In this paper, we consider a model of oscillatory networks of excitable Boolean maps consisting of both excitatory and inhibitory nodes, focusing on the roles of inhibitory nodes. We find that inhibitory nodes in sparse networks （smM1 average connection degree） play decisive roles in weakening oscillations, and oscillation death occurs after continual weakening of oscillation for sufficiently high inhibitory node density. In the sharp contrast, increasing inhibitory nodes in dense networks may result in the increase of oscillation amplitude and sudden oscillation death at much lower inhibitory node density and the nearly highest excitation activities. Mechanism under these peculiar behaviors of dense networks is explained by the competition of the duplex effects of inhibitory nodes.
