Showing papers by "Stefano Boccaletti published in 2009"
TL;DR: This study uses simulations of biologically inspired neuronal networks during development to study the formation of functional groups (cliques) and inter-neuronal synchronization and shows that by the local synchronization properties at the very early developmental stages, it is possible to predict with high accuracy which clusters will become dominant in later stages of network development.
Abstract: Modular organization is a special feature shared by many biological and social networks alike. It is a hallmark for systems exhibiting multitasking, in which individual tasks are performed by separated and yet coordinated functional groups. Understanding how networks of segregated modules develop to support coordinated multitasking functionalities is the main topic of the current study. Using simulations of biologically inspired neuronal networks during development, we study the formation of functional groups (cliques) and inter-neuronal synchronization. The results indicate that synchronization cliques first develop locally according to the explicit network topological organization. Later on, at intermediate connectivity levels, when networks have both local segregation and long-range integration, new synchronization cliques with distinctive properties are formed. In particular, by defining a new measure of synchronization centrality, we identify at these developmental stages dominant neurons whose functional centrality largely exceeds the topological one. These are generated mainly in a few dominant clusters that become the centers of the newly formed synchronization cliques. We show that by the local synchronization properties at the very early developmental stages, it is possible to predict with high accuracy which clusters will become dominant in later stages of network development.
40 citations
01 Dec 2009
TL;DR: Cortical and Neural Networks Cultured Neural Networks Functional Connectivity in Complex Brain Networks Boolean Dynamics Gene Circuits Metabolic Networks Folding Landscapes and Networks Evolutionary Dynamics Motion Coordination Ecosystems.
Abstract: Cortical and Neural Networks Cultured Neural Networks Functional Connectivity in Complex Brain Networks Boolean Dynamics Gene Circuits Metabolic Networks Folding Landscapes and Networks Evolutionary Dynamics Motion Coordination Ecosystems.
24 citations
TL;DR: By means of this approach, a series of theorems are proved that allow to gather information on the ranking of the nodes of a network with respect to their strategic importance in order to preserve the functioning and performance of the network as a whole.
Abstract: An efficient and computationally advantageous definition of vulnerability of a complex network is introduced, through which one is able to overcome a series of practical difficulties encountered by the measurements used so far to quantify a network's security and stability under the effects of failures, attacks or disfunctions. By means of this approach, we prove a series of theorems that allow to gather information on the ranking of the nodes of a network with respect to their strategic importance in order to preserve the functioning and performance of the network as a whole.
14 citations
TL;DR: A real-time method for the identification of time-varying interaction delays in coupled systems with and without unknown structural parameters is introduced and the convergence of the delay identification process is analyzed.
Abstract: We introduce a real-time method for the identification of time-varying interaction delays in coupled systems with and without unknown structural parameters and analyze the convergence of the delay identification process. The identification method can be applied to monitor the change in interaction delays, as well as to decode the encoding of interaction delays. Several examples are presented to illustrate the reliability and robustness of the suggested strategy.
14 citations
TL;DR: A network synchronization bifurcation diagram is introduced that should prove to be an effective tool for analysis, design, and optimization of complex networks.
Abstract: We propose an experimental setup based on a single oscillator for studying large networks formed by identical unidirectionally coupled systems. A chaotic wave form generated by the oscillator is stored in a computer to adjust the signal according to the desired network configuration to feed it again into the same oscillator. No previous theoretical knowledge about the oscillator dynamics is needed. To visualize network synchronization we introduce a network synchronization bifurcation diagram that should prove to be an effective tool for analysis, design, and optimization of complex networks.
14 citations
TL;DR: It is shown that the arousal of a scale-free distribution in connection with the success of the entrainment process is a robust feature, characterizing different networks' initial configurations and parameters.
Abstract: We show that the topology and dynamics of a network of unsynchronized Kuramoto oscillators can be simultaneously controlled by means of a forcing mechanism which yields a phase locking of the oscillators to that of an external pacemaker in connection with the reshaping of the network's degree distribution. The entrainment mechanism is based on the addition, at regular time intervals, of unidirectional links from oscillators that follow the dynamics of a pacemaker to oscillators in the pristine graph whose phases hold a prescribed phase relationship. Such a dynamically based rule in the attachment process leads to the emergence of a power-law shape in the final degree distribution of the graph whenever the network is entrained to the dynamics of the pacemaker. We show that the arousal of a scale-free distribution in connection with the success of the entrainment process is a robust feature, characterizing different networks' initial configurations and parameters.
9 citations
TL;DR: It is demonstrated that there are two classes of networks susceptible of being regulated into a synchronous motion and a simple method is provided to properly design a pinning sequence to achieve regulation.
Abstract: To shed light on how biological and technological systems can establish or maintain a synchronous functioning, we address the problem of how to engineer an external pinning action on a network of dynamical units. In particular, we study the regulation of a network toward a synchronized behavior by means of a bidirectional interaction with an external node that leaves unchanged its inner parameters and architecture. We demonstrate that there are two classes of networks susceptible of being regulated into a synchronous motion and provide a simple method, for each one of them, to properly design a pinning sequence to achieve regulation. We also discuss how the obtained sequence can be compared with a topological ranking of the network nodes.
5 citations
TL;DR: It is shown that successful entrainment always corresponds to the generation of a scale-free topology in the original graph.
Abstract: A collection of connected phase oscillators, initially unsynchronised, are subjected to a growing process. In such a process, pacemaker oscillators attach to the original network following an exclusively dynamical criterion oriented to entrain the network. Under these conditions, we show that successful entrainment always corresponds to the generation of a scale-free topology in the original graph.