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Abstract #0048

Mapping resting-state dynamics on spatio-temporal graphs: a combined functional and diffusion MRI approach

Alessandra Griffa 1,2 , Kirell Benzi 3 , Benjamin Ricaud 3 , Xavier Bresson 3 , Pierre Vandergheynst 3 , Patric Hagmann 1,2 , and Jean-Philippe Thiran 1,2

1 Signal Processing Laboratory 5 (LTS5), cole Polytechnique Fdrale de Lausanne (EPFL), Lausanne, Switzerland, 2 Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland, 3 Signal Processing Laboratory 2 (LTS2), cole Polytechnique Fdrale de Lausanne (EPFL), Lausanne, Switzerland

Magnetic resonance imaging allows inferring overall brain structural and functional networks. A growing body of recent literature suggests that a static description of functional connectivity (e.g. with simple correlation measures) might by over simplistic. In the present work we propose a mathematically sound and flexible method for the mapping of dynamic spatio-temporal resting state patterns. Our framework is based on the representation of data on a spatio-temporal graph and exploits structural (diffusion-based) and functional information in a complementary manner. Nodes within isolated functional sub-networks are simultaneously close in space (the space of the anatomical connectivity substrate) and time (temporally co-active).

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