Phase Lag Analysis Scalp Electroencephalography May Predict Seizure Frequencies in Patients with Childhood Epilepsy
Masayoshi Oguri1, Tetsuya Okazaki2, Tohru Okanishi3
1Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu 761-0123, Japan.
Insights
Childhood epilepsy with centrotemporal spikes (CECTS) brain network activity differs from controls. Resting-state phase lag index in the beta frequency band may predict seizure frequency in children with CECTS.
Area of Science:
- Neuroscience
- Epilepsy Research
- Brain Network Analysis
Background:
- Childhood epilepsy with centrotemporal spikes (CECTS) is a common epilepsy syndrome in school-aged children.
- Predictors for seizure frequency in CECTS remain unclear.
- Phase lag index (PLI) analysis offers a novel approach to investigate brain network dynamics.
Purpose of the Study:
- To investigate the utility of resting-state electroencephalography (EEG) phase lag index (PLI) in identifying predictive markers for seizure frequency in children with CECTS.
- To compare PLI between CECTS patients and healthy controls.
- To explore the association between PLI and seizure times in CECTS patients.
Main Methods:
- Compared resting-state EEG PLI between 13 CECTS patients and 13 age/sex-matched healthy controls.
- Analyzed mean PLIs across all electrodes and between specific interest electrodes (C3, C4, P3, P4, T3, T4) and others.
- Examined associations between PLIs and total seizure times in CECTS patients.
Main Results:
- No significant differences in clinical profiles or visual EEG between groups.
- CECTS patients showed higher theta and alpha band PLIs, and lower delta and gamma band PLIs compared to controls.
- A negative association was found between beta band PLI and seizure times in CECTS patients (P=0.02).
Conclusions:
- Resting-state PLI in delta, theta, alpha, and gamma bands may indicate aberrant brain networks in CECTS.
- Resting-state beta band PLI, particularly among selected electrodes, shows potential as a predictive marker for seizure frequency in CECTS.
Background:
Childhood epilepsy with centrotemporal spikes (CECTS) is the most common epilepsy syndrome in school-aged children. However, predictors for seizure frequency are yet to be clarified using the phase lag index (PLI) analyses. We investigated PLI of scalp electroencephalography data at onset to identify potential predictive markers for seizure times.
Methods:
We compared the PLIs of 13 patients with CECTS and 13 age- and sex-matched healthy controls. For the PLI analysis, we used resting-state electroencephalography data (excluding paroxysmal discharges), and analyzed the mean PLIs among all electrodes and between interest electrodes (C3, C4, P3, P4, T3, and T4) and other electrodes. Furthermore, we compared PLIs between CECTS and control data and analyzed the associations between PLIs and total seizure times in CECTS patients.
Results:
No differences were detected in clinical profiles or visual electroencephalography examinations between patients with CECTS and control participants. In patients with CECTS, the mean PLIs among all electrodes and toward interest electrodes were higher at the theta and alpha bands and lower at the delta and gamma bands than those in control participants. Additionally, the mean PLIs toward interest electrodes in the beta frequency band were negatively associated with seizure times (P = 0.02).
Conclusion:
The resting-state delta, theta, alpha, and gamma band PLIs might reflect an aberrant brain network in patients with CECTS. The resting-state PLI among the selected electrodes of interest in the beta frequency band may be a predictive marker of seizure times in patients with CECTS.
