Physiological High-Frequency Oscillations in Scalp EEGs Change During Brain Maturation

High-frequency oscillations (HFOs), occurring between 80-1000 Hz, were first identified only three decades ago. Since then, physiological HFOs have been implicated in learning, memory and motor function, while epileptic HFOs have been associated with epileptogenic tissue. Many studies have shown that HFO activity correlates with seizure frequency, severity, and surgical outcomes. However, distinguishing physiological from epileptic HFOs remains challenging due to their overlapping frequency ranges and similar morphologies. Little is known about how physiological HFOs change throughout typical brain development. Without a clear understanding of normal developmental patterns, it is difficult to determine which HFOs are truly physiological and which may be pathological. This thesis aims to characterize normative developmental changes in physiological HFOs across age, brain region and sex. Using a dataset of 244 scalp EEG recordings from developmentally typical children, we found that HFOs follow a structured developmental trajectory, differ by sex and vary regionally across different stages of maturation. These findings were used to generate a reference atlas describing typical HFO occurrence rates per minute. This atlas serves as a foundational tool for understanding physiological brain development and for distinguishing normal HFO activity from epileptic patterns. Moreover, this work also highlights the feasibility of automated HFO detection from scalp EEGs. The use of non-invasive methods opens the door to larger-scale studies and broader applications beyond epilepsy.

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Medicine – Neuroscience

Grantor dc:publisher.institution

Cumming School of Medicine

Year dc:date.issued

2025

Author dc:creator

• Chabrotra, Riddhi

Advisors dc:contributor.advisor

• Jacobs-LeVan, Julia
• Teskey, Gordon Campbell

Committee member dc:contributor.committeemember

• Serena Orr, Julia Kam

• High-frequency oscillations
• ripples
• development
• scalp EEG
• automated detection
• children

Statement dc:rights

• University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.

Language dc:language.iso

en

DOI

https://dx.doi.org/10.11575/PRISM/49966

OAI identifier oai:identifier

oai:ucalgary.scholaris.ca:1880/122373