The Effect of noise on the synchronization dynamics of the Kuramoto model on a large human connectome graph
We have extended the study of the Kuramoto model with additive Gaussian noise running on the KKI-18 large human connectome graph. We determined the dynamical behavior of this model by solving it numerically in an assumed homeostatic state, below the synchronization crossover point we determined prev...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Pompeu Fabra |
| Repositorio: | Repositorio Digital de la UPF |
| OAI Identifier: | oai:repositori.upf.edu:10230/53533 |
| Acceso en línea: | http://hdl.handle.net/10230/53533 http://doi.org/10.1016/j.neucom.2020.04.161 |
| Access Level: | acceso abierto |
| Palabra clave: | Frustrated synchronization Human connectome Chimera states Noisy Kuramoto Criticality in resting state |
| Sumario: | We have extended the study of the Kuramoto model with additive Gaussian noise running on the KKI-18 large human connectome graph. We determined the dynamical behavior of this model by solving it numerically in an assumed homeostatic state, below the synchronization crossover point we determined previously. The de-synchronization duration distributions exhibit power-law tails, characterized by the exponent in the range 1:1 < st < 2, overlapping the in vivo human brain activity experiments by Palva et al. We show that these scaling results remain valid, by a transformation of the ultra-slow eigenfrequencies to Gaussian with unit variance. We also compare the connectome results with those, obtained on a regular cube with N ¼ 106 nodes, related to the embedding space, and show that the quenched internal frequencies themselves can cause frustrated synchronization scaling in an extended coupling space. |
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