ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2017
Synchronization patterns: from network motifs to hierarchical networks.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 41 citations in OpenAlex.
- Emergence of metastability in frustrated oscillatory networks: the key role of hierarchical modularity.Frontiers in network physiology · 2024Article
- Cross-frequency coupling between slow harmonics via the real brainstem oscillators: An in vivo animal study.PloS one · 2023Article
- Subgraphs of Interest Social Networks for Diffusion Dynamics Prediction.Entropy (Basel, Switzerland) · 2021Article
- Complex partial synchronization patterns in networks of delay-coupled neurons.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2019Article
- Horizons of cybernetical physics.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2017Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We investigate complex synchronization patterns such as cluster synchronization and partial amplitude death in networks of coupled Stuart-Landau oscillators with fractal connectivities. The study of fractal or self-similar topology is motivated by the network of neurons in the brain. This fractal property is well represented in hierarchical networks, for which we present three different models. In addition, we introduce an analytical eigensolution method and provide a comprehensive picture of the interplay of network topology and the corresponding network dynamics, thus allowing us to predict the dynamics of arbitrarily large hierarchical networks simply by analysing small network motifs. We also show that oscillation death can be induced in these networks, even if the coupling is symmetric, contrary to previous understanding of oscillation death. Our results show that there is a direct correlation between topology and dynamics: hierarchical networks exhibit the corresponding hierarchical dynamics. This helps bridge the gap between mesoscale motifs and macroscopic networks.This article is part of the themed issue 'Horizons of cybernetical physics'.
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