Jae‐Sung Lim

This study uses Bayesian modeling to analyze stroke patient data and identifies distinct brain regions associated with language and executive control impairments.

The paper models sex differences in white matter substrates of aphasia using Bayesian analysis in 1,401 stroke patients, identifying sex-specific lesion effects in language networks.

This study identifies brain infarct locations and white matter disconnections associated with post-stroke depressive symptoms using lesion-symptom mapping and disconnectome analyses.

The paper uses machine learning and Bayesian modeling to analyze lesion patterns in stroke patients, showing how left and right hemisphere damage relates to specific cognitive impairments.