English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

We have extended the study of the Kuramoto model with additive Gaussian noiserunning on the KKI-18 large human connectome graph. We determined the dynamicalbehavior of this model by solving it numerically in an assumed homeostaticstate, below the synchronization crossover point we determined previously. Thede-synchronization duration distributions exhibit power-law tails,characterized by the exponent in the range $1.1 < \tau_t < 2$, overlapping thein vivo human brain activity experiments by Palva et al. We show that thesescaling results remain valid, by a transformation of the ultra-sloweigen-frequencies to Gaussian with unit variance. We also compare theconnectome results with those, obtained on a regular cube with $N=10^6$ nodes,related to the embedding space, and show that the quenched internal frequenciesthemselves can cause frustrated synchronization scaling in an extended couplingspace.

The effect of noise on the synchronization dynamics of the Kuramoto model on a large human connectome graph