Physiological High-frequency Oscillations Change as the Brain Matures
Abstract number :
3.048
Submission category :
1. Basic Mechanisms / 1C. Electrophysiology/High frequency oscillations
Year :
2024
Submission ID :
192
Source :
www.aesnet.org
Presentation date :
12/9/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Riddhi Chabrotra, BS – Alberta Children's Hospital, University of Calgary
Daniel Lachner-Piza, PhD – University of Calgary
Margarita Maltseva, MD – University of Calgary
Julia Jacobs, MD, PhD – University of Calgary, Alberta Children's Hospital, Calgary, AB, Canada
Rationale: Epileptic high-frequency oscillations (HFOs) have been proposed as a potential biomarker for epilepsy, in recent literature.1 Recent research suggests that these pathological HFOs allow for precise localization of the seizure onset and epileptogenic zones2, can be predictive of epilepsy severity3 and may offer valuable insights into the mechanisms underlying seizure generation and propagation.4 Significantly less research exists on physiological HFOs. Differentiating between epileptic and physiological HFOs is crucial for improving diagnostic accuracy and patient outcomes. As a result, this research aims to systematically analyze physiological HFO activity in a large group of healthy children to develop a brain atlas indicative of the normal HFO distribution across brain regions and age.
Methods: We have selected 400 scalp EEGs recorded from developmentally normal patients with high sampling frequencies of 1024 Hz containing > 5 mins of NREM sleep. For this preliminary analysis, we included 109 participants as a proof of principle to establish our methods. The population was subdivided into two groups: group A included participants aged 1 month to 2 years and group B included participants aged 6-10 years. Man-Whitney U tests assessed statistically significant differences between the groups, and sex differences were considered.
Results: The analysis revealed two findings: HFO occurrence rates differ among age groups and sex. The younger cohort (group A) revealed significantly higher HFO rates (p =0.02) and in both groups, there were no significant sex differences.
Conclusions: This data is significant as it shows that we can detect physiological HFOs with an automated detection tool and that scalp HFO rates correlate with brain maturation indicating possible involvement in complex developmental processes. Further exploration of the relationship between physiological and epileptic HFOs may provide valuable insights into the mechanisms underlying epileptogenesis and could potentially lead to the development of novel diagnostic and therapeutic approaches for epilepsy.
Funding: This project is funded by NSERC.
Basic Mechanisms