A skew-based method for identifying intracranial EEG channels with epileptic activity without detecting spikes, ripples, or fast ripples

Abstract

Objective: To develop a method for identifying intracranial EEG (iEEG) channels with epileptic activity without the need to detect spikes, ripples, or fast ripples.

Methods: We compared the skew of the distribution of power values from five minutes non-rapid eye movement stage N3 sleep for the 5-80 Hz, 80-250 Hz (ripple), and 250-500 Hz (fast ripple) bands of epileptic (located in seizure-onset or irritative zone) and non-epileptic iEEG channels recorded in patients with drug-resistant focal epilepsy. We optimized settings in 120 bipolar channels from 10 patients, compared the results to 120 channels from another 10 patients, and applied the method to channels of 12 individual patients.

Results: The distribution of power values was more skewed in epileptic than in non-epileptic channels in all three frequency bands. The differences in skew were correlated with the presence of spikes, ripples, and fast ripples. When classifying epileptic and non-epileptic channels, the mean accuracy over 12 patients was 0.82 (sensitivity: 0.76, specificity: 0.91).

Conclusions: The 'skew method' can distinguish epileptic from non-epileptic channels with good accuracy and, in particular, high specificity.

Significance: This is an easy-to-apply method that circumvents the need to visually mark or automatically detect interictal epileptic events.

Keywords: Biomarkers; Epileptogenic zone; High-frequency oscillations; NREM sleep; Skewness; Stockwell transform.