Ensemble Empirical Mode Decomposition Analysis of EEG Data Collected during a Contour Integration Task
Author(s) -
Karema Al-Subari,
Saad Al-Baddai,
Ana Maria Tomé,
Gregor Volberg,
Rainer Hammwöhner,
Elmar W. Lang
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0119489
Subject(s) - electroencephalography , stimulus (psychology) , neuroscience , pattern recognition (psychology) , brain activity and meditation , electrophysiology , brain mapping , functional magnetic resonance imaging , artificial intelligence , computer science , psychology , cognitive psychology
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 P 100) and 200 [ ms ] (called N 200) after stimulus onset, respectively. We observe early P 100 and N 200 responses at electrodes located in the occipital area of the brain, while late P 100 and N 200 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.
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