Characterizing the electrophysiological abnormalities in visually reviewed normal EEGs of drug-resistant focal epilepsy patients

Abstract

Routine scalp EEG is essential in the clinical diagnosis and management of epilepsy. However, a normal scalp EEG (based on expert visual review) recorded from a patient with epilepsy can cause delays in diagnosis and clinical care delivery. Here we investigated whether normal EEGs might contain subtle electrophysiological clues of epilepsy. Specifically, we investigated a) whether there are indicators of abnormal brain electrophysiology in normal EEGs of epilepsy patients and b) whether such abnormalities are modulated by the side of the brain generating seizures in focal epilepsy. We analyzed awake scalp EEG recordings of age-matched groups of 144 healthy individuals and 48 individuals with drug-resistant focal epilepsy (DRFE) who had normal scalp EEGs. After preprocessing, using a bipolar montage of eight channels, we extracted the fraction of spectral power in the alpha band (8-13 Hz) relative to a wide band of 0.5-40 Hz within 10-second windows. We analyzed the extracted features for a) the extent to which people with DRFE differed from healthy subjects and b) whether differences within the DRFE patients were related to the hemisphere generating seizures. We then used those differences to classify whether an EEG is likely to have been recorded from a person with DRFE, and if so, the epileptogenic hemisphere. Furthermore, we tested the significance of these differences while controlling for confounders such as acquisition system, age, and medications. We found that the fraction of alpha power is generally reduced a) in DRFE compared to healthy controls, and b) in right-handed DRFE subjects with left hemispheric seizures compared to those with right hemispheric seizures, and that the differences are most prominent in the frontal and temporal regions. The fraction of alpha power yielded area under curve values of 0.83 in distinguishing DRFE from healthy and 0.77 in identifying the epileptic hemisphere in DRFE patients. Furthermore, our results suggest that the differences in alpha power are greater when compared with differences attributable to acquisition system differences, age, and medications. Our findings support that EEG-based measures of normal brain function, such as the normalized spectral power of alpha activity, may help identify patients with epilepsy even when an EEG does not contain any epileptiform activity, recorded seizures, or other abnormalities. Although alpha abnormalities are unlikely to be disease-specific, we propose that such abnormalities may provide a higher pre-test probability for epilepsy when an individual being screened for epilepsy has a normal EEG on visual assessment.

Quantitative analysis of visually reviewed normal scalp EEG predicts seizure freedom following anterior temporal lobectomy

“…Multiple studies have reported that quantitative analysis of EEG segments without interictal epileptiform abnormalities can reveal subtle nonspecific abnormalities in the normal brain function of patients with epilepsy. [26][27][28][29][30][31][32][33][34] These electrophysiological changes are hypothesized to arise from epilepsy-related pathologic changes such as neuronal loss, gliosis, and synaptic and network changes. They may also reflect interictal dysfunction in memory and cognition because the same neuronal-glial circuits underlying seizure generation in TLE may subserve normal brain functions.…”

“…They may also reflect interictal dysfunction in memory and cognition because the same neuronal-glial circuits underlying seizure generation in TLE may subserve normal brain functions. 35,36 The EEG biomarkers of normal brain function investigated in previous studies include alpha activity during eyes-closed wakefulness, [26][27][28][29] spectral connectivity measures based on phase-locking factor [30][31][32] and weighted partial directed coherence, 33 and EEG-based local and global synchrony measures. 34 Furthermore, several of those studies showed that the changes in EEG biomarkers of normal brain function can help determine, a) drug resistance, 26,27,29 b) focal vs generalized origin of seizures, 30,32 and c) seizuregenerating hemisphere in focal epilepsy.…”

“…35,36 The EEG biomarkers of normal brain function investigated in previous studies include alpha activity during eyes-closed wakefulness, [26][27][28][29] spectral connectivity measures based on phase-locking factor [30][31][32] and weighted partial directed coherence, 33 and EEG-based local and global synchrony measures. 34 Furthermore, several of those studies showed that the changes in EEG biomarkers of normal brain function can help determine, a) drug resistance, 26,27,29 b) focal vs generalized origin of seizures, 30,32 and c) seizuregenerating hemisphere in focal epilepsy. 26 Building on those findings, we hypothesize that biomarkers of normal EEG can help predict the likelihood of seizure recurrence following ATL.…”

“…34 Furthermore, several of those studies showed that the changes in EEG biomarkers of normal brain function can help determine, a) drug resistance, 26,27,29 b) focal vs generalized origin of seizures, 30,32 and c) seizuregenerating hemisphere in focal epilepsy. 26 Building on those findings, we hypothesize that biomarkers of normal EEG can help predict the likelihood of seizure recurrence following ATL.…”

“…Multiple studies have reported that quantitative analysis of EEG segments without interictal epileptiform abnormalities can reveal subtle nonspecific abnormalities in the normal brain function of patients with epilepsy 26–34 …”