Abstract
High Frequency Oscillations are very brief events that are a well-established biomarker of the epileptogenic zone, but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency “background” data, which has received little attention but represents the majority of the EEG record, also may contain additional, novel information for identifying the epileptogenic zone.
We analyzed intracranial EEG (30–500 Hz frequency range) acquired from 24 patients who underwent resective surgery. We computed 38 quantitative features based on all usable, interictal data (63–307 hours per subject), excluding all detected high frequency oscillations. We assessed association between each feature and the seizure onset zone and resected volume using logistic regression. A pathology score per channel was also created via principle component analysis and logistic regression, using hold-out-one-patient cross validation to avoid in-sample training. Association of the pathology score with the seizure onset zone and resected volume was quantified using an asymmetry measure.
Many features were associated with the seizure onset zone: 23/38 features had odds ratios >1.3 or < 0.7 and 17/38 had odds ratios different than zero with high significance (p < 0.001/39, logistic regression with Bonferroni Correction). The pathology score, the rate of high frequency oscillations, and their channel-wise product were each strongly associated with the seizure onset zone (median asymmetry > =0.44, good surgery outcome patients; median asymmetry > =0.40, patients with other outcomes; 95% confidence interval > 0.27 in both cases). The pathology score and the channel-wise product also had higher asymmetry with respect to the seizure onset zone than the high frequency oscillation rate alone (median difference in asymmetry > =0.18, 95% confidence interval >0.05).
These results support that the high frequency background data contains useful information for determining the epileptogenic zone, distinct and complementary to information from detected high frequency oscillations. The concordance between the high frequency activity pathology score and the rate of high frequency oscillations appears to be a better biomarker of epileptic tissue than either measure alone.
Automatic Localization of Seizure Onset Zone from High-frequency SEEG Signals: A Preliminary Study
