Source analysis of median nerve stimulated somatosensory evoked potentials and fields using simultaneously measured EEG and MEG signals

  • The sources of somatosensory evoked potentials (SEPs) and fields (SEFs), which is a standard paradigm, is investigated using multichannel EEG and MEG simultaneous recordings. The hypothesis that SEP & SEF sources are generated in the posterior bank of the central sulcus is tested, and analyses are compared based on EEG only, MEG only, bandpass filtered MEG, and both combined. To locate the sources, the forward problem is first solved by using the boundary-element method for realistic head models and by using a locally-fitted-sphere approach for averaged head models consisting of a set of connected volumes, typically representing the skull, scalp, and brain. The location of each dipole is then estimated using fixed MUSIC and current-density-reconstruction (CDR) algorithms. For both analyses, the results demonstrate that the band-pass filtered MEG can localize the sources accurately at the desired region as compared to only EEG and unfiltered MEG. For CDR analysis, it looks like MEGThe sources of somatosensory evoked potentials (SEPs) and fields (SEFs), which is a standard paradigm, is investigated using multichannel EEG and MEG simultaneous recordings. The hypothesis that SEP & SEF sources are generated in the posterior bank of the central sulcus is tested, and analyses are compared based on EEG only, MEG only, bandpass filtered MEG, and both combined. To locate the sources, the forward problem is first solved by using the boundary-element method for realistic head models and by using a locally-fitted-sphere approach for averaged head models consisting of a set of connected volumes, typically representing the skull, scalp, and brain. The location of each dipole is then estimated using fixed MUSIC and current-density-reconstruction (CDR) algorithms. For both analyses, the results demonstrate that the band-pass filtered MEG can localize the sources accurately at the desired region as compared to only EEG and unfiltered MEG. For CDR analysis, it looks like MEG affects EEG during the combined analyses. The MUSIC algorithm gives better results than CDR, and when comparing the two head models, the averaged and the realistic head models showed the same result.show moreshow less

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Metadaten
Author:Kidist Gebremariam Mideksa, H. Hellriegel, Nienke Hoogenboom, Holger Krause, Alfons Schnitzler, Günther Deuschl, Jan Raethjen, U. Heute, Muthuraman MuthuramanORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1103523
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/110352
ISBN:978-1-4244-4119-8OPAC
Parent Title (English):2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 28 August - 1 September 2012, San Diego, CA, USA
Publisher:IEEE
Place of publication:Piscataway, NJ
Editor:Michael C. K. Khoo
Type:Conference Proceeding
Language:English
Year of first Publication:2012
Publishing Institution:Universität Augsburg
Release Date:2023/12/21
First Page:4903
Last Page:4906
DOI:https://doi.org/10.1109/embc.2012.6347093
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Informatik in der Medizintechnik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht