The CNTR

MGH Center for Neurotechnology and Neurorecovery

A podcast from the Center for Neurotechnology and Neurorecovery at Massachusetts General Hospital.

Episodes

  1. 5D AGO

    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.

    46 min
  2. MAR 13

    Restoring Speech with Brain-to-Computer Interfaces - Dan Rubin, MD, PhD & Kristina Simonyan, MD, PhD

    In this episode, we learn about how brain-to-computer interfaces (BCIs) are helping restore speech in individuals living with ALS and Laryngeal Dystonia. Dr. Dan Rubin discusses the research behind decoding speech intention from brain activity using motor cortex mapping and real-time phoneme prediction. Dr. Kristina Simonyan discuss her research on EEG-based neurofeedback therapy and VR to restore normal speech in patients with laryngeal dystonia. Dr. Dan Rubin is an Assistant Professor of Neurology at Harvard Medical School. His research looks into how placing micro-electrode arrays directly into the brain can help restore communication in patients with ALS and other disorders leading to speech paralysis. His team uses BCIs to record electrical activity from individual neurons in the speech motor cortex to decode the “intent’ to move speech muscles. The patient’s internal intent to speak is then translated and reproduced through computer systems to restore communication. Dr. Kristina Simonyan, Professor of Otolaryngology at Harvard Medical School, focuses primarily on restoring normal speech in patients with laryngeal dystonia. Laryngeal Dystonia is a neurological disorder that causes involuntary spasms of the vocal cord muscles making it difficult for patients to speak. The BCIs Dr. Simonyan uses involve high density EEG caps and neurofeedback to “retrain” a patient’s ability to speak. Dr. Rubin received his MD and PhD from Columbia University and completed his residency and a fellowship in Neurocritical Care at Massachusetts General Hospital.  Dr. Simonyan completed her medical degree and residency in Otolaryngology at Yerevan State Medical University in Armenia and Georg-August University in Germany. She holds a PhD in Neurobiology from the University of Hannover.

    1h 20m

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A podcast from the Center for Neurotechnology and Neurorecovery at Massachusetts General Hospital.