Disrupted topological organization of structural brain networks in childhood absence epilepsy

Abstract

Childhood absence epilepsy (CAE) is the most common paediatric epilepsy syndrome and is characterized by frequent and transient impairment of consciousness. In this study, we explored structural brain network alterations in CAE and their association with clinical characteristics. A whole-brain structural network was constructed for each participant based on diffusion-weighted MRI and probabilistic tractography. The topological metrics were then evaluated. For the first time, we uncovered modular topology in CAE patients that was similar to healthy controls. However, the strength, efficiency and small-world properties of the structural network in CAE were seriously damaged. At the whole brain level, decreased strength, global efficiency, local efficiency, clustering coefficient, normalized clustering coefficient and small-worldness values of the network were detected in CAE, while the values of characteristic path length and normalized characteristic path length were abnormally increased. At the regional level, especially the prominent regions of the bilateral precuneus showed reduced nodal efficiency, and the reduction of efficiency was significantly correlated with disease duration. The current results demonstrate significant alterations of structural networks in CAE patients, and the impairments tend to grow worse over time. Our findings may provide a new way to understand the pathophysiological mechanism of CAE.

Figure 1

Differences of network metrics between CAE patients and healthy controls (CON). (A) Shows the group differences under different thresholds; significant between-group differences are indicated by an asterisk above the corresponding threshold at p < 0.05 with Bonferroni correction. (B) Displays the group differences at integrated level (**p < 0.05). The error bar indicates standard deviation.

Figure 2

Modular topology of the structural network of CAE patients and healthy controls (CON). (A) Number of modules and brain network modularity in CAE and CON under different thresholds. No significant difference is detected between the two groups. The error bar indicates standard deviation. (B) 3D representations of modular topology are visualized on the average structural network of each group. The nodes are colour-coded by modules.

Figure 3

(A) Distribution of hubs in CAE and healthy controls (CON). For abbreviations of the regions, please see Supplementary Table S1. (B) Significant group difference in integrated E_nodal of bilateral precuneus (left and right, respectively) (**p < 0.05). (C) Relationship between disease duration and integrated E_nodal of bilateral precuneus in the patient group. Significantly negative correlations are revealed for both sides.

Figure 4

Flowchart for brain network construction. Data from a typical healthy control is used to demonstrate the process of construction. (A) Raw high-resolution T1-weighted MRI and DTI images in native space and automated anatomical labelling (AAL) atlas in MNI space. (B) The connectivity matrix is built up according to the probabilistic tractography algorithm after the process of parcellation and normalization. (C) 3D visualization of the weighted network is rendered using BrainNet Viewer (BrainNet Viewer 1.53, Beijing Normal University, http://www.nitrc.org/projects/bnv/). The edges are encoded with their connection weights at the threshold of 0.01.