ABSTRACT
OBJECTIVES: Despite the prevalence of cognitive symptoms in the idiopathic generalized epilepsies (IGEs), cognitive dysfunction in juvenile absence epilepsy (JAE), a common yet understudied IGE subtype, remains poorly understood. This descriptive study provides a novel, comprehensive characterization of cognitive functioning in a JAE sample and examines the relationship between cognition and 24-h epileptiform discharge load. METHOD: Forty-four individuals diagnosed with JAE underwent cognitive assessment using Woodcock Johnson III Test of Cognitive Abilities with concurrent 24-h ambulatory EEG monitoring. Generalized epileptiform discharges of any length, and prolonged generalized discharges ≥3 s were quantified across wakefulness and sleep. The relationship between standardized cognitive scores and epileptiform discharges was assessed through regression models. RESULTS: Cognitive performances in overall intellectual ability, acquired comprehension-knowledge, processing speed, long-term memory storage and retrieval, and executive processes were 0.63-1.07 standard deviation (SD) units lower in the JAE group compared to the population reference mean, adjusted for educational attainment. Prolonged discharges (≥3 s) were recorded in 20 patients (47.6%) from 42 available electroencephalography (EEG) studies and were largely unreported. Duration and number of prolonged discharges were associated with reduced processing speed and long-term memory storage and retrieval. SIGNIFICANCE: Cognitive dysfunction is seen in patients with JAE across various cognitive abilities, including those representing more stable processes like general intellect. During 24-h EEG, prolonged epileptiform discharges are common yet underreported in JAE despite treatment, and they show moderate effects on cognitive abilities. If epileptiform burden is a modifiable predictor of cognitive dysfunction, therapeutic interventions should consider quantitative 24-h EEG with routine neuropsychological screening. The growing recognition of the spectrum of neuropsychological comorbidities of IGE highlights the value of multidisciplinary approaches to explore the causes and consequences of cognitive deficits in epilepsy.
Subject(s)
Epilepsy, Absence , Humans , Cross-Sectional Studies , Electroencephalography , Cognition , Immunoglobulin EABSTRACT
For idiopathic generalized epilepsies (IGE), brain network analysis is emerging as a biomarker for potential use in clinical care. To determine whether people with IGE show alterations in resting-state brain connectivity compared to healthy controls, and to quantify these differences, we conducted a systematic review and meta-analysis of EEG and magnetoencephalography (MEG) functional connectivity and network studies. The review was conducted according to PRISMA guidelines. Twenty-two studies were eligible for inclusion. Outcomes from individual studies supported hypotheses for interictal, resting-state brain connectivity alterations in IGE patients compared to healthy controls. In contrast, meta-analysis from six studies of common network metrics clustering coefficient, path length, mean degree and nodal strength showed no significant differences between IGE and control groups (effect sizes ranged from -0.151 -1.78). The null findings of the meta-analysis and the heterogeneity of the included studies highlights the importance of developing standardized, validated methodologies for future research. Network neuroscience has significant potential as both a diagnostic and prognostic biomarker in epilepsy, though individual variability in network dynamics needs to be better understood and accounted for.
ABSTRACT
This article describes source data from a systematic review and meta-analysis of electroencephalography (EEG) and magnetoencephalography (MEG) studies investigating functional connectivity in idiopathic generalized epilepsy. Data selection, analysis and reporting was performed according to PRISMA guidelines. Eligible studies for review were identified from human case-control, and cohort studies. Twenty-two studies were included in the review. Extracted descriptive data included sample characteristics, acquisition of EEG or MEG recordings and network construction. Reported differences between IGE and control groups in functional connectivity or network metrics were extracted as the main outcome measure. Qualitative group differences in functional connectivity were synthesized through narrative review. Meta-analysis was performed for group-level, quantitative estimates of common network metrics clustering coefficient, path length, mean degree and nodal strength. Six studies were included in the meta-analysis. Risk of bias was assessed across all studies. Raw and synthesized data for included studies are reported, alongside effect size and heterogeneity statistics from meta-analyses. Network neurosciences is a rapidly expanding area of research, with significant potential for clinical applications in epilepsy. This data article provides novel, statistical estimates of brain network differences from patients with IGE relative to healthy controls, across the existing literature. Increasing data accessibility supports study replication and improves study comparability for future reviews, enabling a better understanding of network characteristics in IGE.