A Network-Based View of Epilepsy - Peter Hadar, MD, MS and Andrew (Jian) Li, PhD

In this episode we explore how a network-based understanding of epilepsy is advancing treatment for patients with drug-resistant seizures. We discuss how epilepsy can arise from distributed brain networks rather than a single lesion, and how neurostimulation therapies like Responsive Neurostimulation (RNS) and Deep Brain Stimulation (DBS) are being used to detect and disrupt seizures in real time. We explore how advances in neuroimaging, signal processing, and machine learning are helping map functional connectivity in the brain, enabling more precise and personalized interventions.

Dr. Peter Hadar is an Instructor in the Department of Neurology at Massachusetts General Hospital. His work focuses on personalizing neurostimulation therapies and studying human behavior through intracranial neurophysiology. He earned his MD and MS from the University of Pennsylvania and completed his Epilepsy fellowship at MGH in 2024. He is a recipient of the NIH NINDS R25/UE5 Grant and the Susan Spencer Scholarship in Epilepsy.

Dr. Andrew (Jian) Li is an Instructor at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and Harvard Medical School. He earned his Ph.D. in Electrical Engineering from the University of Southern California. His research applies statistical signal processing and machine learning to neuroimaging data, with a focus on functional connectivity and tools like NASCAR to identify overlapping brain networks.

Together, they are working to release a large-scale, multi-modal dataset from over 27,000 patients to the global research community, aiming to improve diagnosis, prediction, and treatment of epilepsy and other neurological disorders.