Previous simulation studies on human connectomes suggested that critical dynamics emerge subcritically in the so-called Griffiths phases. Now we investigate this on the largest available brain network, the 21662 node fruit-fly connectome, using the Kuramoto synchronization model. As this graph is less heterogeneous, lacking modular structure and exhibiting high topological dimension, we expect a difference from the previous results. Indeed, the synchronization transition is mean-field-like, and the width of the transition region is larger than in random graphs, but much smaller than as for the KKI-18 human connectome. This demonstrates the effect of modular structure and dimension on the dynamics, providing a basis for better understanding the complex critical dynamics of humans.
3 thoughts on “Poster 2022#8 – Geza ODOR – Comparison of the synchronization transition of the Kuramoto model on fruit-fly versus a large human connectome”
Hi, we van tune the disorder, by the self frequency distribution, but we did not change it. Best, Géza.
Hi Dr. Odor,
What is the parameter in your model which controls disorder?