Performance of different synchronization measures in real data: A case study on electroencephalographic signals

TLDR

The study aims to assess interhemispheric synchronization in rat EEG. This assessment is performed using nonlinear interdependence, phase‑synchronization, mutual information, cross‑correlation, and coherence measures. The study demonstrates that, except for mutual information, all examined synchronization measures consistently quantify interhemispheric EEG coupling, with two phase‑synchronization metrics closely related and one extended, confirming their value for real‑data analysis and potential clinical relevance.

Abstract

We study the synchronization between left and right hemisphere rat EEG channels by using various synchronization measures, namely non-linear interdependences, phase-synchronizations, mutual information, cross-correlation and the coherence function. In passing we show a close relation between two recently proposed phase synchronization measures and we extend the definition of one of them. In three typical examples we observe that except mutual information, all these measures give a useful quantification that is hard to be guessed beforehand from the raw data. Despite their differences, results are qualitatively the same. Therefore, we claim that the applied measures are valuable for the study of synchronization in real data. Moreover, in the particular case of EEG signals their use as complementary variables could be of clinical relevance.