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Ensemble Empirical Mode Decomposition Analysis of EEG Data Collected during a Contour Integration Task

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  • Karema Al-Subari
  • Saad Al-Baddai
  • Ana Maria Tomé
  • Gregor Volberg
  • Rainer Hammwöhner
  • Elmar W Lang

Abstract

We discuss a data-driven analysis of EEG data recorded during a combined EEG/fMRI study of visual processing during a contour integration task. The analysis is based on an ensemble empirical mode decomposition (EEMD) and discusses characteristic features of event related modes (ERMs) resulting from the decomposition. We identify clear differences in certain ERMs in response to contour vs noncontour Gabor stimuli mainly for response amplitudes peaking around 100 [ms] (called P100) and 200 [ms] (called N200) after stimulus onset, respectively. We observe early P100 and N200 responses at electrodes located in the occipital area of the brain, while late P100 and N200 responses appear at electrodes located in frontal brain areas. Signals at electrodes in central brain areas show bimodal early/late response signatures in certain ERMs. Head topographies clearly localize statistically significant response differences to both stimulus conditions. Our findings provide an independent proof of recent models which suggest that contour integration depends on distributed network activity within the brain.

Suggested Citation

  • Karema Al-Subari & Saad Al-Baddai & Ana Maria Tomé & Gregor Volberg & Rainer Hammwöhner & Elmar W Lang, 2015. "Ensemble Empirical Mode Decomposition Analysis of EEG Data Collected during a Contour Integration Task," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-27, April.
    • Handle: RePEc:plo:pone00:0119489
    DOI: 10.1371/journal.pone.0119489
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    Cited by:

    1. Th I Götz & G Lahmer & V Strnad & Ch Bert & B Hensel & A M Tomé & E W Lang, 2017. "A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-31, September.

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