Detection of coupling with linear and nonlinear synchronization measures for EEG

Hanieh Bakhshayesh, Sean Fitzgibbon, Kenneth Pope

    Research output: Contribution to conferencePaper

    1 Citation (Scopus)

    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, and to simulated EEG. No measure fails, none is the clear winner, all measures have advantages and disadvantages. 'Best measure' depends on the research aims and data. The tests selected here for EEG research recommend correntropy as the preferred measure.

    Original languageEnglish
    Pages240-243
    Number of pages4
    DOIs
    Publication statusPublished - 1 Jan 2014
    Event2014 Middle East Conference on Biomedical Engineering (MECBME) -
    Duration: 17 Feb 2014 → …

    Conference

    Conference2014 Middle East Conference on Biomedical Engineering (MECBME)
    Period17/02/14 → …

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  • Cite this

    Bakhshayesh, H., Fitzgibbon, S., & Pope, K. (2014). Detection of coupling with linear and nonlinear synchronization measures for EEG. 240-243. Paper presented at 2014 Middle East Conference on Biomedical Engineering (MECBME), . https://doi.org/10.1109/MECBME.2014.6783249