Al-Subari, Karema and Al-Baddai, Saad and Tome, Ana Maria and Volberg, Gregor and Ludwig, Bernd and Lang, Elmar W. (2016) Combined EMD-sLORETA Analysis of EEG Data Collected during a Contour Integration Task. PLOS ONE, 11 (12): e0167957. ISSN 1932-6203,
Full text not available from this repository. (Request a copy)Abstract
Lately, Ensemble Empirical Mode Decomposition (EEMD) techniques receive growing interest in biomedical data analysis. Event-Related Modes (ERMs) represent features extracted by an EEMD from electroencephalographic (EEG) recordings. We present a new approach for source localization of EEG data based on combining ERMs with inverse models. As the first step, 64 channel EEG recordings are pooled according to six brain areas and decomposed, by applying an EEMD, into their underlying ERMs. Then, based upon the problem at hand, the most closely related ERM, in terms of frequency and amplitude, is combined with inverse modeling techniques for source localization. More specifically, the standardized low resolution brain electromagnetic tomography (sLORETA) procedure is employed in this work. Accuracy and robustness of the results indicate that this approach deems highly promising in source localization techniques for EEG data.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | EMPIRICAL MODE DECOMPOSITION; HIGH-RESOLUTION EEG; SOURCE LOCALIZATION; ELECTROMAGNETIC TOMOGRAPHY; INVERSE PROBLEM; BRAIN; DENSITY; NUMBER; NOISE; |
| Subjects: | 000 Computer science, information & general works > 020 Library & information sciences 500 Science > 570 Life sciences |
| Divisions: | Psychology and Pedagogy > Institut für Psychologie Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Informationswissenschaft Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 11 Apr 2019 13:37 |
| Last Modified: | 11 Apr 2019 13:37 |
| URI: | https://pred.uni-regensburg.de/id/eprint/3793 |
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