Detection of coupling with linear and nonlinear synchronization measures for EEG
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Date
2014-02
Authors
Bakhshayesh, Hanieh
Fitzgibbon, Sean Patrick
Pope, Kenneth
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Rights
Copyright © 2014 IEEE
Rights Holder
IEEE
Abstract
There has been extensive research aimed at measuring synchronization to study the relationships between complex time series, such as electroencephalography (EEG). We compare six synchronization measures: the linear measures of cross-correlation, coherence and partial coherence, and three nonlinear similarity measures, namely correntropy, phase index and mutual information. We apply these measures to simulated data (unidirectionally coupled Hénon maps) to test the detection of nonlinear and nonstationary interdependence, including in the presence of noise. We also apply these measures to simulated EEG. The results suggest different measures have both good and bad features. No measure is the clear winner and no method completely fails. “Best measure” depends on the particular data and aim of the research.
Description
Author version made available in accordance with Publisher copyright policy.
Keywords
Electroencephalography, Synchronization
Citation
Bakhshayesh, H. ; Fitzgibbon, S.P. ; Pope, K.J., 2011. Detection of coupling with linear and nonlinear synchronization measures for EEG. Biomedical Engineering (MECBME), 2014 Middle East Conference, 17-20 February 2014. pp. 240 - 243