Intraoperative Mapping of the Tumor-Brain Interface - Angelique Paulk, PhD & Wenya Linda Bi, MD, PhD

Intraoperative Mapping of the Tumor-Brain Interface - Angelique Paulk, PhD & Wenya Linda Bi, MD, PhD

In this episode, we explore intraoperative mapping techniques, from ultrasound and fluorescence agents to intraoperative MRI — explaining how each layer of information helps neurosurgeons, like Dr. Wenya Linda Bi, safely remove as much tumor as possible while preserving critical brain function. We then turn to the field of cancer neuroscience, exploring how gliomas co-opt neural circuitry — inducing excitatory synaptogenesis onto tumor cells via neurogliomal synapses, driving a feedforward cycle of hyperexcitability and tumor proliferation. We discuss the study led by Dr. Angelique Paulk, exploring neural activity signatures of tumor infiltration in the human brain using high-resolution microelectrodes and Neuropixels probes to capture fine-scale electrical patterns across the tumor-brain boundary, and how a metric called the aperiodic exponent — reflecting the brain's excitatory-inhibitory balance — may offer a new, high-resolution tool for delineating healthy from pathological tissue in real time during surgery. Dr. Wenya Linda Bi is the Myers Family Endowed Chair in Skull Base Tumors and Cancer at Mass General Brigham, Harvard Medical School in Boston, USA.  She serves as the Chief of the Tumor Division for Mass General Brigham Neurosurgery, Neurosurgical Oncology Program Director, and Director of the Skull Base and Microneurosurgery Fellowship.  Her clinical expertise in skull base and deep-seated brain tumor surgery has been honored as a national Top Doctor for multiple consecutive years.  In addition, her research team focuses on the translational biology of skull base tumors and refining intraoperative neuromonitoring techniques. A central driver across her efforts is to translate knowledge from advanced technologies to be transparent, scalable, and broadly accessible.  Dr. Angelique Paulk, PhD is an Assistant Professor of Neurology at Harvard Medical School, where she uses high-resolution recording technologies to investigate how neural circuits generate cognition and behavior, how direct electrical stimulation alters neural dynamics, and, most recently, how electrical signatures in the brain can help distinguish healthy tissue from tumor tissue during surgery. She completed her PhD at the University of Arizona, followed by a fellowship at the Queensland Brain Institute in Australia.

High Resolution Imaging of the Brain - Anastasia Yendiki, PhD and Chiara Maffei, PhD

In this episode, we explore the science of diffusion MRI tractography with Dr. Anastasia Yendiki and Dr. Chiara Maffei. They discuss a landmark study that revealed how major brain pathways, long thought to be single unified structures, are actually composed of finer, interleaved connections — a finding that aligns with what neuroanatomists have long suspected but that in vivo imaging couldn't previously resolve. The conversation covers the range of techniques used to get there: ex vivo MRI, optical imaging, tracer studies in macaques, and X-ray microscopy at a European synchrotron. They also break down how this work connects to real clinical applications — from presurgical planning to deep brain stimulation for Parkinson's disease, OCD, and depression — and how their NIH BRAIN Initiative CONNECTS project is working toward the most detailed map of human brain connectivity ever created. Dr. Yendiki is an Associate Professor at Harvard Medical School whose research focuses on developing computational tools for mapping brain circuitry — including TRACULA, a widely used toolbox for diffusion MRI tractography — and on using high-resolution microscopy to build more accurate models of white matter pathways. She also leads the Large-scale Imaging of Neural Circuits (LINC) center, one of five NIH BRAIN Initiative CONNECTS comprehensive centers.  Dr. Maffei is an Instructor in Radiology at Harvard Medical School whose work centers on validating diffusion tractography using high-resolution imaging methods like optical imaging and ex vivo MRI, with a particular focus on improving the reliability of tractography for both clinical and research applications.

Theory of Mind & Semantic Encoding - Ziv Williams, MD and Mohsen Jamali, MD, PhD

In this episode, we explore Theory of Mind and Semantic Encoding. Dr. Williams and Dr. Jamali walk us through their research that involves recording the activity of individual neurons in awake patients undergoing surgery for deep brain stimulation. We discuss how the brain tracks other people's beliefs, how neurons encode the meaning of words and sentences, and what this tells us about the nature of language and social cognition. We explore how this research intersects with artificial intelligence — including whether large language models can pass a Theory of Mind test — and how these discoveries will help with the development of brain-computer interfaces for speech restoration in patients affected by paralysis or stroke.  Dr. Ziv Williams is an Associate Professor of Neurosurgery at Massachusetts General Hospital. Dr. Williams’ lab (Ziv Lab) explores the basic neural computations that underlie motor and cognitive behavior, and how they relate to disorders such as motor paralysis, Alzheimer’s disease and autism. Dr. Williams completed his MD at Stanford University School of Medicine, followed by residency at Massachusetts General Hospital and fellowship at the Mayo Clinic Foundation.  Dr. Mohsen Jamali is an Assistant Professor of Neurosurgery at Massachusetts General Hospital and Harvard Medical School, with training spanning medicine, neuroscience, and mathematics. His research uses single-neuron recordings in humans to study the neural underpinnings of social behavior and language. He is a recipient of the Banting Postdoctoral Fellowship, the NARSAD Young Investigator Grant, and the 2022 Daniel X. Freedman Award.

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.

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.