Remote Synchronization Reveals Network Symmetries and Functional Modules
We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmet...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/45546 |
| Acceso en línea: | https://hdl.handle.net/2445/45546 |
| Access Level: | acceso abierto |
| Palabra clave: | Xarxes neuronals (Neurobiologia) Sincronització Oscil·ladors elèctrics Caos (Teoria de sistemes) Complexitat computacional Neurociències Neural networks (Neurobiology) Synchronization Electric oscillators Chaotic behavior in systems Computational complexity Neurosciences |
| Sumario: | We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmetry are fully synchronized, despite their distance on the graph. We provide analytical arguments to explain this result, and we show how the frustration parameter affects the distribution of phases. An application to brain networks suggests that anatomical symmetry plays a role in neural synchronization by determining correlated functional modules across distant locations. |
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