Functional connectivity network based on scalp electroencephalogram in juvenile myoclonic epilepsy

Abstract

Background

Advances in neuroimaging technology have identified epilepsy as a disorder of brain network dysfunction. Previous research has confirmed alterations in the brain functional network of patients with juvenile myoclonic epilepsy (JME). However, studies investigating brain network changes in JME patients under different intervention conditions remain scarce.

Methods

The manuscript included 32 JME patients who met the ILAE diagnostic criteria, and 36 long-term video EEG records were collected and analyzed. Patients were classified into three groups according to their drug treatment status and reaction: the drug-naive group, the seizure-free group and the poor-controlled group. Based on the brain networks derived from electroencephalogram (EEG) data, network analysis, equivalent dipole source location analysis and Mendelian randomization analysis were conducted. Multiple hypothesis T-Tests were used to assess the difference in various indicators of brain networks enriched for strong functional connectivity (ρ > 0.7) between different patient groups.

Results

Significant differences were found in brain network diameter, shortest path length, transmissibility, and subgroup count between the drug-naïve and seizure-free groups. In contrast, no differences were detected between the drug-naïve and poor-controlled groups. K-means clustering achieved 89 % specificity and 83 % sensitivity in classifying JME patients.

Conclusion

(1) The topological characteristics of brain networks show significant associations with clinical symptom severity in JME patients, demonstrating their value as potential biomarkers for monitoring treatment response. (2) While group-specific variations exist, the overall brain network topology remains indistinguishable across all JME patients, indicating a stable disease-related reorganization. (3) Observed hemispheric lateralization in brain network topology highlights potential targets for neuromodulatory interventions.