We consider the problem of localization of sources of brain electrical activity from electroencephalographic (EEG) and magnetoencephalographic (MEG) measurements using spatial filtering techniques. We propose novel reduced-rank activity indices based on the minimum-variance pseudo-unbiased reduced-rank estimation (MV-PURE) framework. The main results of this paper establish the key unbiasedness property of the proposed indices and their higher spatial resolution compared with full-rank indices in challenging task of localizing closely positioned and possibly highly correlated sources, especially in low signal-to-noise regime. Numerical examples are provided to illustrate the practical applicability of the proposed activity indices using both simulated and real data.
Cite
@article{arxiv.1809.03930,
title = {Localization of Brain Activity from EEG/MEG Using MV-PURE Framework},
author = {Tomasz Piotrowski and Jan Nikadon and Alexander Moiseev},
journal= {arXiv preprint arXiv:1809.03930},
year = {2024}
}