Section: Partnerships and Cooperations
International Initiatives
Inria Associate Teams
BRAINCONNECTIVITIES
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Title: Fusing anatomical and functional connectivity information using diffusion MRI, MEG and EEG.
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International Partners (Institution - Laboratory - Researcher):
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Currently brain connectivity is studied through two different lenses: 1) Anatomical connectivity aims at recovering the “wires” that connect the various brain cortical “units”, 2) Functional connectivity studies when and how cortical regions are connected. Providing tools to fuse these two complementary views is the central goal of this project. Our effort will focus on three imaging modalities: diffusion MRI (dMRI) , Electroencephalography (EEG) and Magnetoencephalography (MEG). dMRI (jointly with traditional MRI) provides a detailed anatomical view of the brain. It allows the recovery of the fiber structure of the white matter: these are the electrical connexions between distant cortical areas. But dMRI does not provide any clue on: 1) on the actual use of connexions during brain activity, 2) on the way information propagates along time for a given task. On the opposite, EEG and MEG (jointly named MEEG) provide (after source reconstruction) time courses of the activity of the cortical areas. It is possible to recover some connectivity information from these time courses, but these are purely signal based and do not take account of the anatomy so there are multiple solutions that are sometimes difficult to discriminate. Furthermore source reconstructions are regularized with purely mathematical a priori taking only partially account of the actual brain structures.The main goals of this project are to provide tools: 1) To acquire diffusion data more efficiently, 2) To use the information of dMRI to define better models and regularization schemes for spatio-temporal MEEG source reconstruction, 3) To use MEEG data to better understand the task-dependent spatio-temporal structure of connectivity patterns.
Inria International Partners
Informal International Partners
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Department of CISE, the University of Florida, Gainesville, USA (Baba C. Vemuri)
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Centre for Medical Image Computing (CMIC), Dept. Computer Science, UCL, UK (D. Alexander)
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SBIA, University of Pennsylvania Medical School, USA (R. Verma).
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University Houari Boumedienne (USTHB, Algiers) (L. Boumghar) and University of Boumerdes, (D. Cherifi), Algeria.