Chris Foulon

This study benchmarks predictive models for long-term stroke outcomes using a global consortium, revealing mechanistic diversity and key predictors across motor, cognitive, and emotional domains.

This paper uses deep learning to generate disconnectomes from stroke lesion masks, achieving faster computation and better prediction of post-stroke cognitive and behavioral outcomes.

The paper introduces Functionnectome, a method that maps functional white matter circuits using fMRI and anatomy, revealing their contribution to motor, working memory, and language functions.

This study maps the human Disconnectome using 1333 stroke lesions, revealing how white matter disconnections relate to brain function and behavior.

This study identifies three neural networks involved in Anosognosia for Hemiplegia using structural neuroimaging in stroke patients.

This study presents a new neuroanatomical model of the default-mode network (DMN) that includes subcortical structures, revealing their structural and functional importance through diffusion tractography and interindividual brain alignment.

The paper develops methods to map lesion effects on brain circuits and shows they impact category fluency, with results available in BCBtoolkit.