Régularisation du problème inverse MEG par IRM de diffusion

Anne-Charlotte Philippe 1
1 ATHENA - Computational Imaging of the Central Nervous System
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Magnetoencephalography (MEG) is a functional non-invasive modality which provides information on the temporal succession of cognitive processes with an excellent time resolution. Unfortunately, spatial resolution is limited due to the ill-posed nature of the MEG inverse problem for estimating source currents from the electromagnetic measurement. Cortex parcellation into regions sharing functional features constitutes a relevant spatial regularization. We propose a whole cortex parcellation method based on the anatomical connectivity mapped by diffusion MRI. Inside areas of a preparcellation, the correlation matrix between connectivity profiles is clustered. The cortex parcellation is then updated testing the similarity of diffusion data on both sides of pre-parcellation boundaries. MEG inverse problem is constrained from this result. Two methods have been developed. The first one is based on the subdivision of source space regarding the parcellation. The cortical activity is obtained on a set of parcels and its analysis is simplified. Not to force sources to have exactly the same value inside a cortical area, we develop an alternative method. We introduce a new regularization term in the MEG inverse problem which constrain sources in a same region to have close values. Our methods are applied on simulated and real subjects. Clinical application is also performed on epileptic data. Each contribution takes part of a pipeline whose each step is detailed to make our works reproducible.
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Anne-Charlotte Philippe. Régularisation du problème inverse MEG par IRM de diffusion. Autre. Université Nice Sophia Antipolis, 2013. Français. ⟨NNT : 2013NICE4135⟩. ⟨tel-00939159v2⟩

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