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mission: to uncover how nutrient signaling pathways, particularly GATOR1-mTORC1, influence neurodevelopment and seizure formation in epilepsy and autism. Why Join Us? Work on cutting-edge projects exploring
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disorder (STXBP1-RD). Dr. Stamberger and Dr. Schoonjans are adult and pediatric neurologist respectively with a clinical focus on epilepsy and research focus on rare genetic epilepsy and neurodevelopmental
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-related disorder (STXBP1-RD). Dr. Stamberger and Dr. Schoonjans are adult and pediatric neurologist respectively with a clinical focus on epilepsy and research focus on rare genetic epilepsy and
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neurodevelopmental syndrome, STXBP1-related disorder (STXBP1-RD). Dr. Stamberger and Dr. Schoonjans are adult and pediatric neurologist respectively with a clinical focus on epilepsy and research focus on rare genetic
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of Neurophysiology). We are interested in the cellular and network mechanisms responsible for the generation of spike and wave discharges, the electrophysiological hallmark of absence epilepsy. The project is aimed
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on multiscale analysis of brain disorders with a focus on Parkinson’s and Alzheimer’s disease, and epilepsy by combining experimental and computational approaches. For a collaborative project within the Institute
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. Building on this work, we seek to harness the power of this new tool to optimize its therapeutic use for a wide variety of conditions including epilepsy, neuropsychiatric disease, movement disorders, chronic
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-signalling/ ), led by Prof. Alexander Skupin, which focuses on multiscale analysis of brain disorders with a focus on Parkinson's and Alzheimer's disease, and epilepsy by combining experimental and
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October 2025. Project description Acute brain injury in the newborn is a major cause of death and lifelong disability, including cerebral palsy, intellectual deficits, epilepsy and autism spectrum disorders
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at Ghent University from September 2025. The project aims to develop a minimally to non-invasive treatment for focal epilepsy with ultrasound neurorecording, modulation, and deep reinforcement learning