CMU Neural Engineering Virtual Seminar
Sponsor, Bin HE, CMU
Seminar Title: A multifaceted view of epileptic seizures based on the brain’s electrical rhythmic activities
Speaker: Dr. Berj L. Bardakjian, Professor of Electrical and Computer Engineering and Biomedical Engineering, University of Toronto
Abstract: The potential of neural codes represented by cross-frequency coupling in the brain’s electrical rhythmic activities as biomarkers for characterizing epileptic brain states, is explored. a) The epileptogenic zone (EZ) is a brain region containing the sources of seizure genesis. Removal of the EZ is associated with cessation of seizures after resective surgical procedures. Specifically, delta-ripple phase-amplitude cross-frequency coupling (PAC) is explored as a spatiotemporal biomarker in the extratemporal lobe epileptic brain. Localization of the EZ using PAC analysis of intracranial EEG data from patients with epilepsy is described. A novel cross-frequency coupled potential signal (SCFC) derived from scalp EEG is used for source imaging and it demonstrated significant advantages over the “raw” scalp EEG, indicating its robust noise performance. This can enhance the placement of intracranial electrodes for surgical intervention. b) Neuroglial network models of the EZ using macro (nonparametric), meso (coupled oscillators), and micro (parametric) level perspectives will be described. c) PAC-based seizure prediction in adult extratemporal lobe epilepsy using random forests, and in infantile epileptic spasms using biomimetic deep learning networks will be presented as examples of the use of PAC-based machine learning in epilepsy.
About the Speaker: Berj L. Bardakjian PhD, PEng is currently a Professor in the Department of Electrical and Computer Engineering, and the Institute of Biomedical Engineering at the University of Toronto. He is an associate editor for the IEEE Transactions on Biomedical Engineering (TBME), the IEEE Reviews in Biomedical Engineering (RBME), and he was an associate editor for Annals of Biomedical Engineering. He has over 150 peer-reviewed publications and four patents. His main research interests are neural engineering, electrical rhythms of the brain, EEG based classification of brain states, detection/prediction and abolishment of epileptic seizures, modeling of nonlinear neural systems, signal processing of nonstationary bioelectric signals, biological clocks, and biomedical applications of machine-learning approaches. His previous awards and positions included being a Medical Research Council of Canada (MRC) postdoctoral fellow in the Department of Physiology, then MRC Scholar in the Institute of Biomedical Engineering, at the University of Toronto, and an investigator in the Playfair Neuroscience Unit at the Toronto Western Hospital. He received the “Bionetics Outstanding Canadian Bioengineer” Award from the Canadian Medical and Biological Society (CMBES). His research funding was provided by grants from the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), and the Ontario Brain Institute (OBI).