Novel algorithmic approaches for the forward and inverse M/EEG problems

Abstract : Magneto- and Electro-encephalography (M/EEG) are two non-invasive functional imaging modalities which measure the electromagnetic activity of the brain. These tools are used in cognitive studies as well as in clinical applications as, for example, epilepsy. Besides the presentation of some background material about the M/EEG modalities, this thesis describes two main contributions. The first one is a method for a fast approximation of a set of EEG forward problem solutions, parametrized by tissue conductivity values. This forward problem consists in computing how a specific cortical activity would be measured by EEG sensors. The main advantage of our method is that it significantly accelerates the computation time, while controlling the approximation error. Head tissue conductivity values vary across subjects and it might be interesting to estimate them from the EEG data. Our method is an important step towards an efficient solution of such a head tissues conductivity estimation problem. The second contribution is a novel source reconstruction method, which estimates extended cortical sources explaining the M/EEG measurements. The main originality of the method is that instead of providing a unique reconstruction, as the majority of the state-of-the-art methods do, it proposes several equally valid candidates. We validated both our contributions on simulated and real M/EEG data.
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Contributor : Kostiantyn Maksymenko <>
Submitted on : Wednesday, December 11, 2019 - 10:55:46 AM
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Kostiantyn Maksymenko. Novel algorithmic approaches for the forward and inverse M/EEG problems. Medical Imaging. Université Côte d'Azur, 2019. English. ⟨tel-02404166⟩



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