Abstract
Adaptive minimum variance based beamformers (MVB) have been successfully applied to magnetoencephalogram (MEG) and electroencephalogram (EEG) data to localize brain activities. However, the performance of these beamformers falls down in situations where correlated or interference sources exist. To overcome this problem, we propose indirect dominant mode rejection (iDMR) beamformer application in brain source localization. This method by modifying measurement covariance matrix makes MVB applicable in source localization in the presence of correlated and interference sources. Numerical results on both EEG and MEG data demonstrate that presented approach accurately reconstructs time courses of active sources and localizes those sources with high spatial resolution. In addition, the results of real AEF data show the good performance of iDMR in empirical situations. Hence, iDMR can be reliably used for brain source localization especially when there are correlated and interference sources.
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Notes
BrainStorm, Matlab Toolbox. http://neuroimage.usc.edu/brainstorm/2017.
A point of the posterior root of the zygomatic arch lying immediately in front of the upper end of the tragus.
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Acknowledgements
The authors would like to acknowledge Elizabeth Bock, Esther Florin, Peter Donhauser, Francois Tadel and Sylvain Baillet from McGill University for providing the rest and AEF dataset.
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Handling Editor: Christoph M. Michel.
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Jafadideh, A.T., Asl, B.M. Spatio-temporal Reconstruction of Neural Sources Using Indirect Dominant Mode Rejection. Brain Topogr 31, 591–607 (2018). https://doi.org/10.1007/s10548-018-0645-8
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DOI: https://doi.org/10.1007/s10548-018-0645-8