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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