Our research program spans from the basic science of human intracranial electrophysiology to translational devices and clinical trials. Every project maintains a direct line from mechanism to therapy.
The Chan Lab occupies a rare position: a physician-scientist laboratory embedded in one of the most active surgical epilepsy programs in Appalachia. Patients undergoing stereo-EEG implantation, DBS, RNS, and VNS provide irreplaceable windows into the living human brain. We combine that access with rigorous signal processing, computational neuroscience, and device development to answer questions that cannot be addressed in animal models or non-invasive imaging.
The electrical signals recorded directly from the human brain with stereoEEG electrodes contain information that is fundamentally inaccessible to scalp EEG or fMRI. High-gamma activity, oscillatory phase coupling, cross-frequency interactions, and single-unit activity each reveal different aspects of circuit function. We work within the epilepsy monitoring unit to record broadband intracranial signals during cognitive tasks, resting state, and natural behavior, building a mechanistic understanding of how large-scale networks coordinate perception, mood, and memory.
A central focus is the frontal–limbic circuit and its role in comorbid depression in epilepsy. Approximately one-third of epilepsy patients meet criteria for major depression — not a reaction to diagnosis, but a shared circuit-level vulnerability. By recording simultaneously from prefrontal cortex, anterior cingulate, amygdala, and hippocampus during emotional paradigms, we characterize the oscillatory signatures that distinguish depressed from non-depressed epilepsy patients. This work underpins our NIMH K23 award.
Brain-computer interfaces bridge the gap between the brain and the external world without requiring intracranial surgery. Our BCI program operates on two distinct platforms: SeizEAR, an in-ear EEG system embedded in a commercial hearing aid form factor; and Axon-R (the Cognixion ONE AR headset), an augmented-reality BCI for patients with expressive aphasia after stroke or epilepsy surgery.
SeizEAR targets a fundamental unmet need: continuous, ambulatory, naturalistic monitoring of brain activity in epilepsy patients. The canal is an acoustically and electrically privileged recording site, and our work has demonstrated that in-ear EEG can capture interictal epileptiform discharges with sufficient signal quality for machine learning-based detection. This has implications not just for seizure monitoring but for passive digital biomarker capture in neurodegenerative conditions.
The AR-BCI program, pursued through the NSF BRAIN Pilot IUCRC, uses the eye-tracking and display capabilities of the Axon-R headset combined with P300-based or gaze-based decoding to provide a communication and language rehabilitation interface for patients with aphasia.
Neuromodulation therapies have transformed the treatment of epilepsy, Parkinson's disease, depression, and OCD — yet we still have only a limited mechanistic understanding of how they work. Our program uses the unique opportunity of intraoperative and post-implant recordings in patients undergoing DBS, RNS, and VNS to characterize the electrophysiological effects of stimulation on target circuits in real time.
We are particularly interested in low-intensity focused ultrasound (LIFU) as an emerging non-invasive or minimally invasive modulation tool. In partnership with the Focused Ultrasound Foundation and collaborators at NaviFUS, we are developing SEEG-guided LIFU protocols targeting the anterior nucleus of the thalamus — the same target as the SANTE trial — to understand how ultrasound-mediated neuromodulation interacts with ongoing thalamocortical rhythms in epilepsy. This work combines the precision of SEEG with the therapeutic promise of sonication.
The overlap between epilepsy and neurodegenerative disease — particularly Alzheimer's disease — is increasingly recognized. Epilepsy is both a risk factor for and a consequence of neurodegeneration. This provides a natural bridge for our lab's expertise in neural signal analysis and device development to address a much larger patient population.
Our neurodegeneration program centers on passive digital biomarker discovery using commercial hearing aid technology. Modern hearing aids continuously sample the acoustic environment, track activity metrics, and in some cases detect falls. We are developing the scientific framework to use this passively acquired data — collected over months and years — to identify neural signatures of cognitive decline earlier than conventional clinical assessments allow. In partnership with Starkey Hearing Technologies, we are building a retrospective observational study in a neurodegenerative disease cohort.
This research direction is expected to become the laboratory's primary growth area over the next decade, as the aging of Appalachia creates urgent demand for scalable, low-burden monitoring solutions.
Our research benefits from multi-institutional collaborations spanning neurosurgery, computational neuroscience, psychiatry, and biomedical engineering.