Graduate Researcher University of California, Irvine
This abstract is recognized by Partners Against Mortality in Epilepsy for its contribution to improving the understanding of epilepsy-related mortality
Rationale: High frequency oscillations (HFOs) are short bursts of power at frequencies > 80 Hz, and they are thought to be significant markers of both cognition and disease in humans and animals. Physiological HFOs have been associated with basic vision, motor, and memory consolidation processes in humans. Pathological HFOs are a promising biomarker of epileptogenicity in infantile spasms (IS) and many other epilepsy syndromes. However, spontaneously occurring physiological scalp ripples in healthy human subjects using scalp electroencephalogram (EEG) have received little attention thus far, and previous studies focused on pathological HFOs have relied on visual analysis of short segments of data due to the prevalence of artifacts in EEG. Therefore, the goals of our study were to (1) develop a fully automated method of HFO detection that can be applied to large datasets, and (2) obtain robust estimates of HFO spatiotemporal characteristics in IS and healthy cohorts. Methods: We prospectively collected long-term scalp EEG data from 13 subjects with IS and 16 healthy infants. For patients with IS, recording began prior to diagnosis and continued through initiation of treatment with adrenocorticotropic hormone (ACTH); all awake and sleep data were analyzed. For healthy subjects, non-rapid eye movement (NREM) sleep data was extracted from overnight recordings for analysis. Ripples (80-250 Hz) were detected in all EEG data using an automated algorithm. For the healthy cohort, visual validation was also performed. We characterized HFO duration, peak frequency, root-mean-square (RMS) amplitude, spatial distribution, global HFO rate, and variability of global HFO rate across sleep stages and over time. Results: HFO rates were substantially higher in patients with IS compared to controls. In IS patients, HFO rates were higher during sleep compared to wakefulness (median 5.5/min and 2.9/min, respectively; p =0.002). In healthy subjects, we found that HFO rate was highest in frontal and temporal channels, and it was highest in the lightest stage of NREM sleep (N1) across all subjects. In IS subjects, ACTH therapy significantly decreased the rate of HFOs. Conclusions: Here, we show for the first time that a fully automated algorithm can be used to detect HFOs in long-term scalp EEG. We also provide a detailed characterization of the spatial distribution and rates of HFOs associated with infantile spasms, which may have relevance for diagnosis and assessment of treatment response. This work also represents the most comprehensive analysis of scalp physiological ripples thus far, contributing to our understanding of the visibility and characteristics of physiological ripples on the scalp and their relationship to the stages of sleep, as well as providing a valuable baseline for studies of pathological ripples associated with epilepsy. Funding: Please list any funding that was received in support of this abstract.: CHOC PSF Tithe Pilot Award.
