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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 < τ_t < 2, overlapping the in vivo human brain activity experiments byarXiv:1912.06018v3 fatcat:pncngryytzf6defa6xcrmzbsv4