Paper Info
Title
Multi-core beamformers: Derivation, limitations and improvements.
Abstract
Minimum variance beamformers are popular tools used in EEG and MEG for analysis of brain activity. In recent years new multi-source beamformer methods were developed, including the Dual-Core Beamformer (DCBF) and its enhanced version (eDCBF). Both techniques should allow modeling of correlated brain activity under a wide range of conditions. However, the mathematical justification given is based on single-source results and computer simulations, which do not provide an insight into the assumptions involved and the limits of their applicability. Current work addresses this problem. Analytical expressions relating actual source parameters to those obtained with the DCBF and eDCBF are derived, and rigorous conclusions regarding the accuracy of the DCBF/eDCBF reconstructions are made. In particular, it is shown that DCBF accurately identifies source coordinates, but amplitudes and orientations are only correct for high SNRs and fully correlated sources. In contrast, eDCBF source localization is inaccurate, but if the source positions are found precisely, eDCBF allows perfect reconstruction for arbitrary SNRs. If the source positions are approximate, the reconstruction errors are generally larger for higher SNR values. The eDCBF results can be improved by using global unbiased localizer functions and an alternative way of estimating source orientations.
Year
DOI
Venue
2013
10.1016/j.neuroimage.2012.12.072
NeuroImage
Keywords
Field
DocType
Magnetoencephalography (MEG),Inverse solutions,Minimum variance beamformers,Correlated sources,Dual-core beamformers
Minimum-variance unbiased estimator,Expression (mathematics),Cognitive psychology,Algorithm,Source localization,Statistics,Multi-core processor,Amplitude,Mathematics
Journal
Volume
ISSN
Citations 
71
1053-8119
3
PageRank 
References 
Authors
0.41
17
2
Name
Order
Citations
PageRank
Alexander Moiseev1222.71
Anthony T Herdman2556.88