PLoS ONE (Jan 2019)

Reduced resilience of brain gray matter networks in idiopathic generalized epilepsy: A graph-theoretical analysis.

  • Daichi Sone,
  • Masako Watanabe,
  • Norihide Maikusa,
  • Noriko Sato,
  • Yukio Kimura,
  • Mikako Enokizono,
  • Mitsutoshi Okazaki,
  • Hiroshi Matsuda

DOI
https://doi.org/10.1371/journal.pone.0212494
Journal volume & issue
Vol. 14, no. 2
p. e0212494

Abstract

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PurposeThe pathophysiology of idiopathic generalized epilepsy (IGE) is still unclear, but graph theory may help to understand it. Here, we examined the graph-theoretical findings of the gray matter network in IGE using anatomical covariance methods.Materials and methodsWe recruited 33 patients with IGE and 35 age- and sex-matched healthy controls. Gray matter images were obtained by 3.0-T 3D T1-weighted MRI and were normalized using the voxel-based morphometry tools of Statistical Parametric Mapping 12. The normalized images were subjected to graph-theoretical group comparison using the Graph Analysis Toolbox with two different parcellation schemes. Initially, we used the Automated Anatomical Labeling template, whereas the Hammers Adult atlas was used for the second analysis.ResultsThe resilience analyses revealed significantly reduced resilience of the IGE gray matter networks to both random failure and targeted attack. No significant between-group differences were found in global network measures, including the clustering coefficient and characteristic path length. The IGE group showed several changes in regional clustering, including an increase mainly in wide areas of the bilateral frontal lobes. The second analysis with another region of interest (ROI) parcellation generated the same results in resilience and global network measures, but the regional clustering results differed between the two parcellation schemes.ConclusionThese results may reflect the potentially weak network organization in IGE. Our findings contribute to the accumulation of knowledge on IGE.