A New Real-Time EEG Source Localization Method

Valentin Debenay (1, 2) , Grégory Turbelin (1) , Jean-Pierre Issartel (1) , Amine Chellali (2) , Béatrice Alescio-Lautier (3) , Marie-Hélène Ferrer (4)

1 LMEE - Laboratoire de Mécanique et d'Energétique d'Evry
2 IBISC - Informatique, BioInformatique, Systèmes Complexes
3 LNC - Laboratoire de Neurosciences Cognitives [Marseille]
4 IRBA - Institut de Recherche Biomédicale des Armées [Antenne Marseille]

Aims: Electroencephalography (EEG) provides insights for monitoring brain activity. Unfortunately, although scalp EEG can provide clinically useful information, its spatial resolution is low, making it difficult to determine the specific brain locations involved. However, noninvasive EEG-based source localization methods computationally estimate the locations, orientations, and strengths of the electric currents in the brain generating scalp potentials. Using anatomically faithful 3D head models, these approaches enable the accurate localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring, and provide guidance for patient-tailored treatment. Our goal is to determine whether our method of source localization, called "Renormalization", is helpful for obtaining real-time feedback. Methods: Our approach is based on the lead field theory. Unlike other methods, ours computes the so-called “visibility field” of the recording system through a “3D Renormalisation” process. Then, to determine the spatial location and the strength of sources producing the potential scalp maps, this field is used to calculate a unique solution to the neuroelectric inverse problem. Results: We used the “Renormalisation” method with an “ANT Neuro eego sports” system and an anatomically realistic 3D head model. The visibility field characterizes the regions in which the recording system concentrates its source identification ability. We used it to provide an accurate real-time spatial mapping of electrical brain activity and characterization (localization, strength, orientation) of localized and distributed sources. Conclusions: By its specificities, we expect that our method will contribute to a better understanding of brain functions and improve the care of brain-injured patients.

Domains: Signal and Image processing

Valentin Debenay, Grégory Turbelin, Jean-Pierre Issartel, Amine Chellali, Béatrice Alescio-Lautier, et al.. A New Real-Time EEG Source Localization Method. Federation of European Neuroscience Societies (FENS 2022) forum, Jul 2022, Paris, France. 2022. ⟨hal-03955214⟩