Resumen
In complex systems such as the brain, interactions among their constituents units have been demonstrated to occur in groups of units and not limited only to pairwise interactions, like for example, neural coupling among different brain regions. This investigation delves into the inclusion of higher order interactions to simulate the dynamics of brain oscillations. Specifically, we employed a coupled oscillators approach to model large scale neural networks using an extended Kuramoto model to simulate high order synchronization dynamics in the brain using the human connectome. We found that the human connectome used in this study has a high order architecture, with simplicial complexes up to the 11th order. Furthermore, stability dynamics emerge through the addition of simplex of higher order to the simulations: hysteresis when considering from 3-simplex to 6-simplex and metastability when considering 7-simplex onward. This investigation is relevant in the modelling of neural oscillatory signals representing phenomenon of abrupt changes in synchrony, where non-linear regimes emerge.
Idioma original | Inglés |
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Título de la publicación alojada | 2022 41st International Conference of the Chilean Computer Science Society, SCCC 2022 |
Editorial | IEEE Computer Society |
ISBN (versión digital) | 9781665456746 |
DOI | |
Estado | Publicada - 2022 |
Evento | 41st International Conference of the Chilean Computer Science Society, SCCC 2022 - Santiago, Chile Duración: 2022 → 2022 |
Serie de la publicación
Nombre | Proceedings - International Conference of the Chilean Computer Science Society, SCCC |
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Volumen | 2022-November |
ISSN (versión impresa) | 1522-4902 |
Conferencia
Conferencia | 41st International Conference of the Chilean Computer Science Society, SCCC 2022 |
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País/Territorio | Chile |
Ciudad | Santiago |
Período | 21/11/22 → 25/11/22 |
Nota bibliográfica
Publisher Copyright:© 2022 IEEE.
Áreas temáticas de ASJC Scopus
- Ingeniería General
- Ciencia de la Computación General