Incorporating transmission delays supported by diffusion MRI in MEG source reconstruction

Ivana Kojčić (1, 2) , Théodore Papadopoulo (1, 2) , Rachid Deriche (1, 2) , Samuel Deslauriers-Gauthier (1, 2)

1 UniCA - Université Côte d'Azur
2 ATHENA - Computational Imaging of the Central Nervous System

White matter fibers transfer the information between brain regions with delays that are measurable with magnetoencephalography and electroencephalography (M/EEG). In the context of regularizing the dynamics of M/EEG and recovering electrical activity of the brain from M/EEG measurements, this article proposes a graph representation-based framework to solve the M/EEG inverse problem, where prior information about transmission delays supported by diffusion MRI (dMRI) are included to enforce temporal smoothness. Results of the reconstruction of brain activity from simulated MEG measurements are compared to MNE, LORETA and CGS methods and we show that our approach improves MEG source localization when compared to these three state-of-theart approaches. In addition, we show preliminary qualitative results of the proposed reconstruction method on real MEG data for a sensory-motor task.

Mots clés: diffusion MRI; MEG; source localization; inverse problems

Domaines: Imagerie médicale; Traitement du signal et de l'image [eess.SP]; Modélisation et simulation; Neurosciences

Ivana Kojčić, Théodore Papadopoulo, Rachid Deriche, Samuel Deslauriers-Gauthier. Incorporating transmission delays supported by diffusion MRI in MEG source reconstruction. ISBI 2021 - 18th IEEE International Symposium on Biomedical Imaging, Apr 2021, Nice, France. ⟨10.1109/ISBI48211.2021.9433861⟩. ⟨hal-03143148⟩