title: EEG extended source localization: tensor-based vs. conventional methods.
abstract: The localization of brain sources based on EEG measurements is a topic that has attracted a lot of attention in the last decades and many different source localization algorithms have been proposed. However, their performance is limited in the case of several simultaneously active brain regions and low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a space-time-frequency (STF) or space-time-wave-vector (STWV) tensor and decomposing it using the Canonical Polyadic (CP) decomposition. In this paper, we present a new algorithm for the accurate localization of extended sources based on the results of the tensor decomposition. Furthermore, we conduct a detailed study of the tensor-based preprocessing methods, including an analysis of their theoretical foundation, their computational complexity, and their performance for realistic simulated data in comparison to conventional source localization algorithms such as sLORETA, cortical LORETA (cLORETA), and 4-ExSo-MUSIC. Our objective consists, on the one hand, in demonstrating the gain in performance that can be achieved by tensor-based preprocessing, and, on the other hand, in pointing out the limits and drawbacks of this method. Finally, we validate the STF and STWV techniques on real measurements to demonstrate their usefulness for practical applications.
authors.affiliation: Univ. Nice Sophia Antipolis, CNRS, I3S, UMR 7271, F-06900 Sophia Antipolis, France; INSERM, U1099, Rennes F-35000, France; Université de Rennes 1, LTSI, Rennes F-35000, France; GIPSA-Lab, CNRS UMR5216, Grenoble Campus BP.46, F-38402 St Martin d'Heres Cedex, France.
authors.forename: H
authors.initials: H
authors.lastname: Becker
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Université de Rennes 1, LTSI, Rennes F-35000, France; Centre INRIA Rennes-Bretagne Atlantique, Rennes F-35042, France. Electronic address: laurent.albera@univ-rennes1.fr.
authors.forename: L
authors.initials: L
authors.lastname: Albera
authors.affiliation: GIPSA-Lab, CNRS UMR5216, Grenoble Campus BP.46, F-38402 St Martin d'Heres Cedex, France.
authors.forename: P
authors.initials: P
authors.lastname: Comon
authors.affiliation: Ilmenau University of Technology, Communications Research Laboratory, P.O. Box 10 05 65, D-98684 Ilmenau, Germany.
authors.forename: M
authors.initials: M
authors.lastname: Haardt
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Université de Rennes 1, LTSI, Rennes F-35000, France.
authors.forename: G
authors.initials: G
authors.lastname: Birot
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Université de Rennes 1, LTSI, Rennes F-35000, France.
authors.forename: F
authors.initials: F
authors.lastname: Wendling
authors.affiliation: INSERM, UMR 1106, F-13005 Marseille, France; Aix-Marseille Université, F-13005 Marseille, France; AP-HM, Hopital Timone, F-13005 Marseille, France.
authors.forename: M
authors.initials: M
authors.lastname: Gavaret
authors.affiliation: INSERM, UMR 1106, F-13005 Marseille, France; Aix-Marseille Université, F-13005 Marseille, France.
authors.forename: C G
authors.initials: CG
authors.lastname: Bénar
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Université de Rennes 1, LTSI, Rennes F-35000, France.
authors.forename: I
authors.initials: I
authors.lastname: Merlet
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio
keywords: Distributed source localization; EEG; Space–time–frequency analysis; Space–time–wave–vector analysis; Tensor decomposition