Dirk‐Bart den Ouden

This paper uses GPT-2 to analyze aphasia subtypes and recovery by examining activation patterns in narrative speech over time, finding distinct differences across subtypes and changes during recovery.

This study investigates the neural separation of verbal working memory and syntactic comprehension, finding distinct brain networks associated with each function.

The paper uses connectome-based lesion-symptom mapping to investigate word and sentence comprehension deficits in stroke patients, finding that middle-posterior temporal lobe regions, not double disconnection, are primarily responsible.

This study uses lesion-symptom mapping to identify functional differentiation in language network regions by analyzing aphasia patients with left hemisphere stroke damage.

This study develops a deep neural network to subtype Primary Progressive Aphasia patients into three variants using speech and language data, achieving 80% accuracy.

This study uses lesion-symptom mapping to show a double dissociation between agrammatism and paragrammatism, linking them to distinct brain regions.