A Family of Reduced-Rank Neural Activity Indices for EEG/MEG Source Localization
Localization of sources of brain electrical activity from electroencephalographic and magnetoencephalographic recordings is an ill-posed inverse problem. Therefore, the best one can hope for is to derive a source localization method which is guaranteed to find sources belonging to the set of possible solutions to this problem. Recently, a few methods with this property have been proposed as a non-trivial generalizations of the classical neural activity index based on the linearly constrained minimum-variance (LCMV) spatial filtering technique. In this paper we propose a family of reduced-rank activity indices achieving maximum value when evaluated at true source locations for uncorrelated dipole sources and any nonzero rank constraint. This fact shows in particular that this key property is not confined to a selected few activity indices. We present a series of numerical simulations evaluating localization performance of the proposed activity indices. We also give an overview of areas of future research which should be considered as an extension of the results of this paper. In particular, we discuss how new families of activity indices can be derived based on the proposed technique.
KeywordsElectroencephalography magnetoencephalography beamforming reduced-rank signal processing dipole source localization
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