BIONIC: Biomarker Discovery in Epilepsy and Movement Disorders

In this talk, Dr. Nuri Ince, biomedical engineer and new member of the BIONIC team, shares his group’s journey to uncover neurobiomarkers that can transform neuromodulation therapies for epilepsy and movement disorders. His work combines brain–machine interface principles with advanced signal analysis to extract “clues” from neural activity—patterns that reveal disease mechanisms and guide more precise treatments. Dr. Ince describes how deep brain stimulation (DBS) electrodes can be used not only to treat Parkinson’s disease but also to record valuable neural oscillations. Early research showed that beta synchrony in the subthalamic nucleus aligns with the best therapeutic contacts—one of the first discoveries linking brain rhythms to DBS optimization. Long‑term recordings further revealed how medication induces unique shifts in beta and high‑frequency oscillations (HFOs), offering a roadmap for titrating therapy. He then explains how AI‑driven analysis of intraoperative signals can improve electrode placement. By turning low‑frequency signals into interpretable features, Dr. Ince’s team built real‑time systems that correctly predicted neurosurgeons’ targeting decisions in 80% of surgeries and even uncovered electrophysiological differences between Parkinson’s subtypes—patterns that correlate with symptom severity. The second half of the talk focuses on epilepsy, where identifying seizure‑onset zones remains slow and risky. Dr. Ince’s AI tools detect pathological HFO clusters even in noisy, artifact‑rich intracranial EEG, achieving near–EMU‑level precision and predicting surgical failures. These algorithms are now being integrated with next‑generation wireless cortical implants to enable real‑time seizure localization and future closed‑loop neuromodulation. Together, Dr. Ince’s work demonstrates how advanced signal processing + AI + neuromodulation can drive personalized, mechanism‑informed therapies for complex brain disorders. 00:00 Introduction to Dr. Nuri Ince 00:31 Brain–Machine Interfaces: Clinical vs Assistive Applications 01:40 “Mother Nature Leaves Crumbs”: Finding Clues in Neural Signals 02:27 DBS Overview & Using Electrodes for Neural Recording 03:04 Beta Synchrony Discovery & Optimal Therapy Contacts 04:18 Long‑Term LFP Recording & Medication‑Driven Oscillation Changes 05:22 High‑Frequency Oscillations (HFOs) as Therapeutic Clues 06:04 Challenges in DBS Lead Placement & Need for Better Biomarkers 07:08 AI‑Driven Intraoperative Pattern Recognition (80% Accuracy) 08:04 Electrophysiological Differences in Parkinson’s Phenotypes 09:37 Uncovering Mechanisms: Evoked Resonant Neural Activity (ERNA) 11:04 ERNA in Awake & Asleep Surgeries + Toward Personalized DBS 12:47 Transition to Epilepsy: Identifying Seizure Onset Zones 14:34 AI Tools for HFO Clustering & Artifact‑Robust Seizure Mapping 15:44 Real‑Time Systems + Integration with Next‑Gen Wireless Implants 17:14 Closing Remarks & Future of Personalized Neuromodulation From Mayo Clinic to your inbox (free): https://www.mayoclinic.org/patient-visitor-guide/newsletters Visit Mayo Clinic: https://www.mayoclinic.org Connect with Mayo Clinic: Facebook: https://www.facebook.com/mayoclinic Instagram: https://www.instagram.com/mayoclinic X: https://x.com/MayoClinic Threads: https://www.threads.net/@mayoclinic