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Abstract
ObjectiveWe quantitatively analyzed high-frequency oscillations (HFOs) using scalp electroencephalography (EEG) in patients with infantile spasms (IS).MethodsWe enrolled 60 children with IS hospitalized from January 2019 to August 2020. Sixty healthy age-matched children comprised the control group. Time–frequency analysis was used to quantify γ, ripple, and fast ripple (FR) oscillation energy changes.Resultsγ, ripple, and FR oscillations dominated in the temporal and frontal lobes. The average HFO energy of the sleep stage is lower than that of the wake stage in the same frequency bands in both the normal control (NC) and IS groups (P < 0.05). The average HFO energy of the IS group was significantly higher than that of the NC group in γ band during sleep stage (P < 0.01). The average HFO energy of S and Post-S stage were higher than that of sleep stage in γ band (P < 0.05). In the ripple band, the average HFO energy of Pre-S, S, and Post-S stage was higher than that of sleep stage (P < 0.05). Before treatment, there was no significant difference in BASED score between the effective and ineffective groups. The interaction of curative efficacy × frequency and the interaction of curative efficacy × state are statistically significant. The average HFO energy of the effective group was lower than that of the ineffective group in the sleep stage (P < 0.05). For the 16 children deemed “effective” in the IS group, the average HFO energy of three frequency bands was not significantly different before compared with after treatment.SignificanceScalp EEG can record HFOs. The energy of HFOs can distinguish physiological HFOs from pathological ones more accurately than frequency. On scalp EEG, γ oscillations can better detect susceptibility to epilepsy than ripple and FR oscillations. HFOs can trigger spasms. The analysis of average HFO energy can be used as a predictor of the effectiveness of epilepsy treatment.
Highlights
Extensive high-frequency oscillations (HFOs) occur in the neural network
The results show that the Burden of Amplitudes and Epileptiform Discharges (BASED) score before treatment was higher compared with after treatment (P < 0.01)
HFOs are weaker than normal-frequency EEG signals, with lower amplitude and a shorter duration
Summary
Extensive high-frequency oscillations (HFOs) occur in the neural network. HFOs appear on electroencephalography (EEG) with a frequency of 40–500 Hz. HFOs include gamma (γ; 40∼80 Hz), ripple (80∼200 Hz), and fast ripple (FR; 200∼500 Hz) oscillations (Ferrari-Marinho et al, 2020). The clinical applications of HFOs include preoperative evaluation of epilepsy surgery, evaluation of seizure severity, evaluation of the efficacy of various methods of epilepsy treatment, evaluation of the severity of the pathological injury, and detection of susceptibility to epilepsy and seizures. Owing to the limitations of low amplitude and spatial distribution, HFOs are recorded using intracranial electrodes with a sampling frequency of > 2,000 Hz. An artificial analysis is still the gold standard for HFO analysis (Frauscher et al, 2017). Artificial analysis is time-consuming, and due to its inevitable subjectivity, HFOs are not routinely used in clinical practice
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