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Abstract #2019

Prediction of long-term evolution of cognitive impairment following stroke using resting-state functional connectivity.

Clément Bournonville1, Hilde Hénon1, Christine Delmaire1, Stéphanie Bombois1, Jean-Pierre Pruvo1, Xavier Leclerc1, Régis Bordet1, and Renaud lopes1

1Univ. Lille, INSERM, CHRU Lille, U1171 – Neurodegenerative and vascular disorders, Lille, France

The mechanisms of chronic post-stroke cognitive impairments are currently poor understood. However, the study of functional connectivity gives new opportunities to better elucidate the physiopathology. Here, using resting functional connectivity and a machine learning approach, we tried to predict the evolution of cognitive functions up to 36 months after stroke. The results showed that the prediction capacity depends on the studied cognitive domain, and that a particular focus should be done on frontal and temporal cortices.

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