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Comparison of the synchronization transition of the Kuramoto model on fruit-fly versus a large human connectome

ORAL

Abstract

The Kuramoto equation has been solved numerically on the 21.662 node fruit-fly [1] and the 804.113 node human connectomes. While the fly neural connectome resembles to a structureless random graph, the KKI-18 grey matter human connectome exhibits a hierarchical modular organization [2]. The synchronization transition of the fly is mean-field like, with a weak hysteresis, but a narrow Griffiths phase cannot be excluded [3]

In contrast, the transition on the KKI-18 is very broad and a frustrated synchronziation phase, with nonuniversal power-laws can be observed, sub-critically [4].

[1] L. K Scheffer et al, A connectome and analysis of the adult Drosophila central brain,

    eLife 2020;9:e57443 doi: 10.7554/eLife.57443

[2] M. T. Gastner and G. Odor, The topology of large Open Connectome

    networks for the human brain, Scientific Reports 6 (2016) 27249.

[3] G. Odor, J. Kelling, G. Deco, work in progress.

[4] G. Odor and J. Kelling, Critical synchronization dynamics of the

    Kuramoto model on connectome and small world graphs, Scientic Reports 9 (2019) 19621.

Publication: M. T. Gastner and G. Ódor, The topology of large Open Connectome networks for the human brain<br>Scientific Reports 6 (2016) 27249.<br><br>G. Odor and J. Kelling, Critical synchronization dynamics of the Kuramoto model on connectome and small world graphs. Scientic Reports 9 (2019). <br><br>Geza Odor, M. T. Gastner, J. Kelling, G. Deco,<br>Modelling on the very large-scale connectome, J. Phys. Complex. 2 (2021) 045002.

Presenters

  • Geza Odor

    Institute of Technical Physics and Mater

Authors

  • Geza Odor

    Institute of Technical Physics and Mater

  • Gustavo Deco

    Center for Brain and Cognition, Theoretical and Computational Group, Universitat Pompeu Fabra / ICREA, Barcelona, Spain

  • Jeffrey Kelling

    Department of Information Services and Computing, Helmholtz-Zentrum Dresden - Rossendorf, P.O.Box 51 01 19, 01314 Dresden, Germany