Functional brain network characteristics are associated with epilepsy severity in childhood absence epilepsy

Abstract

While cognitive impairments are not generally considered to be part of the childhood absence epilepsy (CAE) syndrome, some recent studies report cognitive, mainly attentional, deficits. Here we set out to investigate the whole brain functional network of children with CAE and controls. Furthermore, the possible relation of the functional network abnormalities with epilepsy and neurocognitive characteristics is studied. Seventeen children with childhood CAE (aged 9.2 ± 2.1 years) and 15 controls (aged 9.8 ± 1.8 years) were included. Resting state functional MRI was acquired to study the functional network. Using graph theoretical analysis, three global metrics of the functional network were investigated: the characteristic path length, the clustering coefficient, and the small-worldness. A multivariable linear regression model including age, sex, and subject motion as covariates was used to investigate group differences in the graph metrics. Subsequently, relations of the graph metrics with epilepsy and neurocognitive characteristics were assessed. Longer path lengths, weaker clustering and a lower small-world network topology were observed in children with CAE compared to controls. Moreover, longer path lengths were related to a longer duration of CAE and a higher number of absence seizure per hour. Clustering and small-worldness were not significantly related to epilepsy or neurocognitive characteristics. The organization of the functional network of children with CAE is less efficient compared to controls, and is related to disease duration. These preliminary findings suggest that CAE is associated with alterations in the functional network.

Keywords: Cognitive performance; Functional mri; Graph theory; Network analysis; Seizures.

Fig. 1

A) Normalized path length, B) normalized cluster coefficient and C) normalized small-worldness as a function of sparsity. Mean and standard errors for children with CAE (dashed) and controls (solid) are shown. Asterisks indicate a significant difference between the two groups (p < .05).

Fig. 2

The relationship of normalized path length for networks that are 82% sparse with A) the duration of CAE and B) the number of GSWD per hour. A least squares line and 95% confidence intervals are added for visualization. Note that the latter is boxcox transformed and therefore displayed on a log-scale. CAE, childhood absence epilepsy; GSWD, generalized spike-wave discharges.