%0 Journal Article %1 Nicosia2013Remote %A Nicosia, Vincenzo %A Valencia, Miguel %A Chavez, Mario %A D\'ıaz-Guilera, Albert %A Latora, Vito %D 2013 %I American Physical Society %J Physical Review Letters %K synchronization networks brain %N 17 %P 174102+ %R 10.1103/physrevlett.110.174102 %T Remote Synchronization Reveals Network Symmetries and Functional Modules %U http://dx.doi.org/10.1103/physrevlett.110.174102 %V 110 %X 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.

@article{Nicosia2013Remote, abstract = {{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.}}, added-at = {2019-06-10T14:53:09.000+0200}, author = {Nicosia, Vincenzo and Valencia, Miguel and Chavez, Mario and D\'{\i}az-Guilera, Albert and Latora, Vito}, biburl = {https://www.bibsonomy.org/bibtex/2e0a6ce6778b4cbb5d92c6f08e5687449/nonancourt}, citeulike-article-id = {12307837}, citeulike-linkout-0 = {http://dx.doi.org/10.1103/physrevlett.110.174102}, citeulike-linkout-1 = {http://link.aps.org/abstract/PRL/v110/i17/e174102}, citeulike-linkout-2 = {http://link.aps.org/pdf/PRL/v110/i17/e174102}, comment = {(private-note)way of categorising similar nodes in the network}, doi = {10.1103/physrevlett.110.174102}, interhash = {a178050c2f8c9ecdd747d11f6ecd5894}, intrahash = {e0a6ce6778b4cbb5d92c6f08e5687449}, issn = {0031-9007}, journal = {Physical Review Letters}, keywords = {synchronization networks brain}, month = apr, number = 17, pages = {174102+}, posted-at = {2014-06-02 19:27:36}, priority = {2}, publisher = {American Physical Society}, timestamp = {2019-08-01T16:20:35.000+0200}, title = {{Remote Synchronization Reveals Network Symmetries and Functional Modules}}, url = {http://dx.doi.org/10.1103/physrevlett.110.174102}, volume = 110, year = 2013 }