Inferring the connectivity of coupled oscillators and anticipating their transition to synchrony through lag-time analysis

The synchronization phenomenon is ubiquitous in nature. In ensembles of coupled oscillators, explosive synchronization is a particular type of transition to phase synchrony that is first-order as the coupling strength increases. Explosive sychronization has been observed in several natural systems, and recent evidence suggests that it might also occur in the brain. A natural system to study this phenomenon is the Kuramoto model that describes an ensemble of coupled phase oscillators. Here we calculate bi-variate similarity measures (the cross-correlation, $ρ_{ij}$, and the phase locking value, PLV$_{ij}$) between the phases, $ϕ_i(t)$ and $ϕ_j(t)$, of pairs of oscillators and determine the lag time between them as the time-shift, $τ_{ij}$, which gives maximum similarity (i.e., the maximum of $ρ_{ij}(τ)$ or PLV$_{ij}(τ)$). We find that, as the transition to synchrony is approached, changes in the distribution of lag times provide an earlier warning of the synchronization transition (either gradual or explosive). The analysis of experimental data, recorded from Rossler-like electronic chaotic oscillators, suggests that these findings are not limited to phase oscillators, as the lag times display qualitatively similar behavior with increasing coupling strength, as in the Kuramoto oscillators. We also analyze the statistical relationship between the lag times between pairs of oscillators and the existence of a direct connection between them. We find that depending on the strength of the coupling, the lags can be informative of the network connectivity.

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