Literature DB >> 15697667

Network synchronization, diffusion, and the paradox of heterogeneity.

Adilson E Motter1, Changsong Zhou, Jürgen Kurths.   

Abstract

Many complex networks display strong heterogeneity in the degree (connectivity) distribution. Heterogeneity in the degree distribution often reduces the average distance between nodes but, paradoxically, may suppress synchronization in networks of oscillators coupled symmetrically with uniform coupling strength. Here we offer a solution to this apparent paradox. Our analysis is partially based on the identification of a diffusive process underlying the communication between oscillators and reveals a striking relation between this process and the condition for the linear stability of the synchronized states. We show that, for a given degree distribution, the maximum synchronizability is achieved when the network of couplings is weighted and directed and the overall cost involved in the couplings is minimum. This enhanced synchronizability is solely determined by the mean degree and does not depend on the degree distribution and system size. Numerical verification of the main results is provided for representative classes of small-world and scale-free networks.

Year:  2005        PMID: 15697667     DOI: 10.1103/PhysRevE.71.016116

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  25 in total

1.  Network synchronization landscape reveals compensatory structures, quantization, and the positive effect of negative interactions.

Authors:  Takashi Nishikawa; Adilson E Motter
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-20       Impact factor: 11.205

2.  Synchronization properties of heterogeneous neuronal networks with mixed excitability type.

Authors:  Michael J Leone; Brandon N Schurter; Benjamin Letson; Victoria Booth; Michal Zochowski; Christian G Fink
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2015-03-30

3.  Synchronous neural activity in scale-free network models versus random network models.

Authors:  Geoffrey Grinstein; Ralph Linsker
Journal:  Proc Natl Acad Sci U S A       Date:  2005-07-05       Impact factor: 11.205

4.  Dynamics and effective topology underlying synchronization in networks of cortical neurons.

Authors:  Danny Eytan; Shimon Marom
Journal:  J Neurosci       Date:  2006-08-16       Impact factor: 6.167

Review 5.  New Insights on Temporal Lobe Epilepsy Based on Plasticity-Related Network Changes and High-Order Statistics.

Authors:  Erika Reime Kinjo; Pedro Xavier Royero Rodríguez; Bianca Araújo Dos Santos; Guilherme Shigueto Vilar Higa; Mariana Sacrini Ayres Ferraz; Christian Schmeltzer; Sten Rüdiger; Alexandre Hiroaki Kihara
Journal:  Mol Neurobiol       Date:  2017-05-29       Impact factor: 5.590

6.  Control centrality and hierarchical structure in complex networks.

Authors:  Yang-Yu Liu; Jean-Jacques Slotine; Albert-László Barabási
Journal:  PLoS One       Date:  2012-09-27       Impact factor: 3.240

7.  Node vulnerability under finite perturbations in complex networks.

Authors:  Ricardo Gutiérrez; Francisco Del-Pozo; Stefano Boccaletti
Journal:  PLoS One       Date:  2011-06-16       Impact factor: 3.240

8.  On the Influence of Amplitude on the Connectivity between Phases.

Authors:  Andreas Daffertshofer; Bernadette C M van Wijk
Journal:  Front Neuroinform       Date:  2011-07-15       Impact factor: 4.081

9.  Synchronization from second order network connectivity statistics.

Authors:  Liqiong Zhao; Bryce Beverlin; Theoden Netoff; Duane Q Nykamp
Journal:  Front Comput Neurosci       Date:  2011-07-08       Impact factor: 2.380

10.  Evolutionary design of non-frustrated networks of phase-repulsive oscillators.

Authors:  Zoran Levnajić
Journal:  Sci Rep       Date:  2012-12-14       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.