Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have developed a new approach to studying brain wave patterns that may offer vital clues into the mechanisms behind Sudden Unexpected Death in Epilepsy (SUDEP). By using a method called wavelet phase coherence, the team has uncovered significant differences in brain activity during epileptic seizures that could lead to better prevention strategies. This research was published in a recent issue of PLOS ONE.
Epilepsy, a neurological disorder affecting millions worldwide, poses a particular risk of sudden death, especially in patients with uncontrolled seizures. Despite years of research, the exact causes of SUDEP remain poorly understood.
The study — led by Adam Gravitis (BME PhD student), with Professor Berj Bardakjian (ECE, BME) as the corresponding author — identified a critical gap in understanding how specific patterns of brain activity during seizures might contribute to this risk. Their work seeks to fill this void by applying sophisticated mathematical tools to analyze brain signals more precisely.
“The motivation behind the study was to develop a risk assessment for sudden, unexpected death in epilepsy in order to alleviate the fear that dominates the lives of patients with epilepsy,” says Bardakjian.
The study employed wavelet phase coherence, a method that allows for the detailed examination of phase relationships between different brain regions during seizures.
By analyzing the synchronization of brain waves, the researchers were able to detect anomalies that might be linked to SUDEP. This approach represents a significant advancement over traditional methods, offering more nuanced insights into the complex dynamics of the brain during epileptic episodes.
“We were guided by the finding that contractions originating in the brainstem are distinct from those originating in the motor cortex,” says Gravitis. “Given that the brainstem is implicated in SUDEP cases, it was natural to want to examine electromuscular effects, which unfortunately are not routinely recorded in epilepsy monitoring units. We were successful in extracting scalp muscle activity from EEG, and fortunately that distinguished patients with high risk for SUDEP.”
“Our next steps will be to make this clinically relevant by increasing the sample size,” says Bardakjian.
“Ultimately, our goal is to provide a better quality of life for patients with epilepsy.”
