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

Rodrigo Quian QuirogaAlexander KraskovThomas KreuzPeter Grassberger

Abstract

We study the synchronization between left and right hemisphere rat electroencephalographic (EEG) channels by using various synchronization measures, namely nonlinear 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.

Nonlinear Dynamics and Pattern FormationNeural dynamics and brain functionChaos control and synchronizationSynchronization (alternating current)ElectroencephalographyPhase synchronizationCoherence (philosophical gambling strategy)Mutual informationComputer sciencePhase coherenceRaw dataRelevance (law)Correlation

MeSH terms

AnimalsBrain InjuriesCortical SynchronizationDisease Models, AnimalEpilepsy, AbsenceHumansIbotenic AcidMaleRats, Inbred StrainsThalamic NucleiTime FactorsNonlinear DynamicsRats
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