This is a project in collaboration between the research groups of Experimental Oto-Rhino-Laryngology, department of Neuroscience (PI’s Maaike Vandermosten & Tom Francart ) and Brain & Cognition, Faculty of Psychology & Educational Sciences (PI Céline Gillebert), both part of KU Leuven, Belgium. The research of Maaike Vandermosten focuses on the neurobiological basis of language, using longitudinal designs with neuroimaging and natural speech measures. Tom Francart has vast expertise in EEG neural tracking analyses in diverse patient populations (hearing impaired, CI, aphasia,…). Céline Gillebert focuses on understanding and detecting cognitive deficits in brain injured patients as well as on its neural correlates. The specific expertise of each PI will be combined in this project to guarantee a multidisciplinary supervision of the PhD student. The main affiliation of the PhD student will be the group of Experimental ORL (http://www.kuleuven.be/exporl), which is a strongly multidisciplinary lab, consisting of 35 researchers from a variety of backgrounds (engineering, audiology, medicine, psychology, speech pathology,…). Within the lab, there is expertise in state-of-the-art MRI techniques, multi-channel brain potential recordings (EEG) as well as psychophysical auditory experiments and language tests. We publish our work in world-class scientific journals and regularly present at important international conferences.

Around 52 people per day suffer a stroke in Belgium, of whom one third is affected by aphasia, an acquired and impactful language disorder. In the acute phase, formal language testing is challenging, due to potential co-morbid cognitive problems, leading to inaccurate diagnoses and predictions. Natural speech assessment is less depended on active cooperation and would be more representative for daily communication. Therefore, in a large-scale longitudinal project in stroke patients (n=600), we will optimize the standard screening protocol by including natural speech production tasks and a more extensive characterization of the lesion. Via data-driven clustering techniques we will define different profiles in the acute phase and test their predictive value in terms of long-term language outcomes. Second, we will examine natural speech reception in a subset of 100 acute stroke patients and neurotypical controls by testing the sensitivity, specificity and predictive value of EEG neural tracking (i.e., an EEG technique that links brain responses to specific acoustic and linguistic features encompassed within the natural story patients listened to). By using natural speech measures, the aim is to provide novel way to diagnose aphasia in a more comprehensive and functionally relevant manner.

Qualifications 

• An excellent Master degree in speech and language pathology, (neuro)psychology, biomedical engineering, experimental psychology, (cognitive) neuroscience, or related disciplines. Students who graduate in June or August 2024 are also welcome to apply.
• Good English and Dutch proficiency (data collection is in Dutch)
•  Good programming skills (or at least high willingness to learn)
•  Having experience with MRI and EEG techniques and/or with aphasia is an asset
• An inquisitive and creative mind, excellent problem solving skills
• Strong commitment and the ability to work in an interdisciplinary team
•  Ability to work flexibly and independently and flexible