Data-driven cortical clustering to provide a family of plausible solutions to M/EEG inverse problem

Abstract : The M/EEG inverse problem is ill-posed. Thus additional hypotheses are needed to constrain the solution space. In this work, we consider that brain activity which generates an M/EEG signal is a connected cortical region. We study the case when only one region is active at once. We show that even in this simple case several configurations can explain the data. As opposed to methods based on convex optimization which are forced to select one possible solution, we propose an approach which is able to find several ”good” candidates - regions which are different in term of their sizes and/or positions but fit the data with similar accuracy.
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Communication dans un congrès
iTWIST, Nov 2018, Marseille, France. 2018, 〈https://sites.google.com/view/itwist18〉
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https://hal.inria.fr/hal-01946876
Contributeur : Kostiantyn Maksymenko <>
Soumis le : jeudi 6 décembre 2018 - 14:20:22
Dernière modification le : samedi 29 décembre 2018 - 12:09:52

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  • HAL Id : hal-01946876, version 1
  • ARXIV : 1812.04110

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Kostiantyn Maksymenko, Maureen Clerc, Théodore Papadopoulo. Data-driven cortical clustering to provide a family of plausible solutions to M/EEG inverse problem. iTWIST, Nov 2018, Marseille, France. 2018, 〈https://sites.google.com/view/itwist18〉. 〈hal-01946876〉

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