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As a model of temporally evolving networks, we consider a globally coupled logistic map with variable connection weights. The model exhibits self-organization of network structure, reflected by the collective behavior of units. Structural…

无序系统与神经网络 · 物理学 2009-11-07 Junji Ito , Kunihiko Kaneko

Large networks of spiking neurons show abrupt changes in their collective dynamics resembling phase transitions studied in statistical physics. An example of this phenomenon is the transition from irregular, noise-driven dynamics to…

适应与自组织系统 · 物理学 2008-11-25 Vicenç Gómez , Andreas Kaltenbrunner , Vicente López , Hilbert J. Kappen

Network of nonlinear dynamical elements often show clustering of synchronization by chaotic instability. Relevance of the clustering to ecological, immune, neural, and cellular networks is discussed, with the emphasis of partially ordered…

chao-dyn · 物理学 2009-10-22 Kunihiko Kaneko

In this study, we performed comprehensive morphological investigations of the spontaneous formations of effective network structures among elements in coupled logistic maps, specifically with a delayed connection change. Our proposed model…

适应与自组织系统 · 物理学 2020-12-02 Amika Ohara , Masashi Fujii , Akinori Awazu

We study here a model of globally coupled units with adaptive interaction weights which has a delay in the updating rule. Simulations show that the model with such delayed synaptic change exhibits dynamical self-organization of network…

无序系统与神经网络 · 物理学 2009-10-31 Junji Ito , Toru Ohira

We describe a simple adaptive network of coupled chaotic maps. The network reaches a stationary state (frozen topology) for all values of the coupling parameter, although the dynamics of the maps at the nodes of the network can be…

适应与自组织系统 · 物理学 2015-06-19 V. Botella-Soler , P. Glendinning

Functional networks provide a topological description of activity patterns in the brain, as they stem from the propagation of neural activity on the underlying anatomical or structural network of synaptic connections. This latter is well…

无序系统与神经网络 · 物理学 2021-02-11 Ali Safari , Paolo Moretti , Ibai Diez , Jesus M. Cortes , Miguel Ángel Muñoz

Disordered systems subject to a fluctuating environment can self-organize into a complex history-dependent response, retaining a memory of the driving. In sheared amorphous solids, self-organization is established by the emergence of a…

软凝聚态物质 · 物理学 2026-01-08 Muhittin Mungan , Eric Clement , Damien Vandembroucq , Srikanth Sastry

Self-regulation of living tissue as an example of self-organization phenomena in hierarchical systems of biological, ecological, and social nature is under consideration. The characteristic feature of these systems is the absence of any…

医学物理 · 物理学 2009-11-30 Wassily Lubashevsky , Ihor Lubashevsky , Reinhard Mahnke

Networks of chaotic units with static couplings can synchronize to a common chaotic trajectory. The effect of dynamic adaptive couplings on the cooperative behavior of chaotic networks is investigated. The couplings adjust to the activities…

混沌动力学 · 物理学 2013-04-12 Marco Winkler , Sebastian Butsch , Wolfgang Kinzel

A novel type of self-organized lattice in which chaotic defects are arranged periodically is reported for a coupled map model of open flow. We find that temporally chaotic defects are followed by spatial relaxation to an almost periodic…

chao-dyn · 物理学 2009-10-22 Frederick H. Willeboordse , Kunihiko Kaneko

We investigate the role of connection density in an adaptive network model of chaotic units that dynamically rewire based on their internal states and local coherence. By systematically varying the network's connectivity density, we uncover…

适应与自组织系统 · 物理学 2025-08-19 Ramiro Plüss , Pablo Martín Gleiser

Effect of noise in inducing order on various chaotically evolving systems is reviewed, with special emphasis on systems consisting of coupled chaotic elements. In many situations it is observed that the uncoupled elements when driven by…

chao-dyn · 物理学 2015-06-24 Manojit Roy , R. E. Amritkar

Living neural networks in our brains autonomously self-organize into large, complex architectures during early development to result in an organized and functional organic computational device. A key mechanism that enables the formation of…

神经与进化计算 · 计算机科学 2020-06-15 Guruprasad Raghavan , Cong Lin , Matt Thomson

We comprehensively studied the morphology of the self-organized effective network structures that form in simple coupled maps with interelement synchronization-dependent connection changes. Based on the parameter values, the spontaneous…

适应与自组织系统 · 物理学 2022-02-09 Taito Nakanishi , Masashi Fujii , Akinori Awazu

Biological information processing is often carried out by complex networks of interconnected dynamical units. A basic question about such networks is that of reliability: if the same signal is presented many times with the network in…

混沌动力学 · 物理学 2015-06-11 Guillaume Lajoie , Kevin K. Lin , Eric Shea-Brown

From cytoskeletal networks to tissues, many biological systems behave as active materials. Their composition and stress-generation is affected by chemical reaction networks. In such systems, the coupling between mechanics and chemistry…

生物物理 · 物理学 2024-09-25 Luca Barberi , Karsten Kruse

Oscillatory activities are widely observed in specific frequency bands of recorded field potentials in different brain regions, and play critical roles in processing neural information. Understanding the structure of these oscillatory…

神经元与认知 · 定量生物学 2015-07-23 Pengsheng Zheng

Small networks of chaotic units which are coupled by their time-delayed variables, are investigated. In spite of the time delay, the units can synchronize isochronally, i.e. without time shift. Moreover, networks can not only synchronize…

混沌动力学 · 物理学 2009-11-13 Johannes Kestler , Evi Kopelowitz , Ido Kanter , Wolfgang Kinzel

Self-organized criticality has been proposed to be a universal mechanism for the emergence of scale-free dynamics in many complex systems, and possibly in the brain. While such scale-free patterns were identified experimentally in many…

神经元与认知 · 定量生物学 2021-05-11 Roxana Zeraati , Viola Priesemann , Anna Levina
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