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Performance of Beamformers on EEG Source Reconstruction
Yaqub Jon Mohamadi Govinda Poudel Carrie R H Innes Richard Jones
Yaqub Jon Mohamadi
Govinda Poudel
Carrie R H Innes
Richard Jones
Abstract
Recently a number of new beamformers have been introduced for reconstruction and localization of neural sources from EEG and l\1IEG. Howenr, little is known about the relative performance of these beamformers. In this study, 8 scalar beamformers were examined with respect to several parameters to determine how effectin they are at reconstruction of a dipole time course from EEG. A simulated EEG signal was produced by means of forward head modelling for projection of an artificial dipole on scalp electrodes then superimposed on background signal. Both real EEG and white noise were applied as background acth,ity. Although the eigenspace beamformer can perform slightly better than other beamformers for small dipoles, and even more so for large dipoles, it is not a contender for real-time beamforming of EEG as it cannot be completely automated. Overall, in terlllS of per formance, robustness to vari ations in parameters, and ease of application, the minimum variance and Borgiotti-Kaplan beamformers were found to be the best performers.
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Date
2012
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Conference paper
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Mary MacKillop Institute for Health Research
Faculty of Health Sciences
Faculty of Health Sciences
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