Very High-frequency Oscillations: Novel Biomarkers of the Epileptogenic Zone
Overview
Authors
Affiliations
Objective: In the present study, we aimed to investigate depth electroencephalographic (EEG) recordings in a large cohort of patients with drug-resistant epilepsy and to focus on interictal very high-frequency oscillations (VHFOs) between 500Hz and 2kHz. We hypothesized that interictal VHFOs are more specific biomarkers for epileptogenic zone compared to traditional HFOs.
Methods: Forty patients with focal epilepsy who underwent presurgical stereo-EEG (SEEG) were included in the study. SEEG data were recorded with a sampling rate of 25kHz, and a 30-minute resting period was analyzed for each patient. Ten patients met selected criteria for analyses of correlations with surgical outcome: detection of interictal ripples (Rs), fast ripples (FRs), and VHFOs; resective surgery; and at least 1 year of postoperative follow-up. Using power envelope computation and visual inspection of power distribution matrixes, electrode contacts with HFOs and VHFOs were detected and analyzed.
Results: Interictal very fast ripples (VFRs; 500-1,000Hz) were detected in 23 of 40 patients and ultrafast ripples (UFRs; 1,000-2,000Hz) in almost half of investigated subjects (n = 19). VFRs and UFRs were observed only in patients with temporal lobe epilepsy and were recorded exclusively from mesiotemporal structures. The UFRs were more spatially restricted in the brain than lower-frequency HFOs. When compared to R oscillations, significantly better outcomes were observed in patients with a higher percentage of removed contacts containing FRs, VFRs, and UFRs.
Interpretation: Interictal VHFOs are relatively frequent abnormal phenomena in patients with epilepsy, and appear to be more specific biomarkers for epileptogenic zone when compared to traditional HFOs. Ann Neurol 2017;82:299-310.
Shandilya M, Addo-Osafo K, Ranasinghe K, Shamas M, Staba R, Nagarajan S Brain Commun. 2025; 7(1):fcaf041.
PMID: 39949405 PMC: 11822293. DOI: 10.1093/braincomms/fcaf041.
Research progress of epileptic seizure prediction methods based on EEG.
Wang Z, Song X, Chen L, Nan J, Sun Y, Pang M Cogn Neurodyn. 2024; 18(5):2731-2750.
PMID: 39555266 PMC: 11564528. DOI: 10.1007/s11571-024-10109-w.
Weiss S, Sperling M, Engel J, Liu A, Fried I, Wu C Brain Commun. 2024; 6(5):fcae367.
PMID: 39464217 PMC: 11503960. DOI: 10.1093/braincomms/fcae367.
Information dynamics of in silico EEG Brain Waves: Insights into oscillations and functions.
Menesse G, Torres J PLoS Comput Biol. 2024; 20(9):e1012369.
PMID: 39236071 PMC: 11407780. DOI: 10.1371/journal.pcbi.1012369.
Kucewicz M, Cimbalnik J, Garcia-Salinas J, Brazdil M, Worrell G Brain. 2024; 147(9):2966-2982.
PMID: 38743818 PMC: 11370809. DOI: 10.1093/brain/awae159.