We explore novel, innovative multivariate approaches, and lesion-network-mapping for lesion-deficit inference in patients with ischemic stroke. Our group investigates prediction of post-stroke deficits considering changes of structural brain network connectivity beyond traditional imaging markers. The extend of structural “dys-connection” is measured, either directly in DTI and fMRI data from affected patients or indirectly in reference connectomes from healthy subjects.

In collaboration with our research partners at the Institute of Computational Neuroscience at the UKE (head: Prof. C. Hilgetag), we apply an innovative inference approach based on game theory, the Multi-perturbation Shapley value Analysis (MSA), to better account for the dimensionalities inherent in brain anatomy and lesion patterns. MSA considers brain regions as ‘players’ in a game who interact to achieve a behavioral outcome and can also be used to quantify the interactions of the network elements (Zavaglia et al., 2015).

Collaboration: Institute of Computational Neuroscience, UKE