Impaired Topological Properties of Gray Matter Structural Covariance Network in Epilepsy Children With Generalized Tonic–Clonic Seizures: A Graph Theoretical Analysis

Frontiers in Neurology

Qian Chen¹  Huirong Wang²  Yongxin Li³  Yanfang Wang⁴  Wenhua Huang⁴  Ya Wang⁴  Ding Li⁴ 

[1] Department of Pediatric Neurosurgery, Shenzhen Children's Hospital, Shenzhen, China;Electromechanic Engineering College, Guangdong Engineering Polytechnic, Guangzhou, China;Formula-Pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China;Guangdong Provincial Key Laboratory of Medical Biomechanics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China;

关键词: generalized tonic–clonic seizures;    epilepsy children;    gray matter volume;    structural covariance network;    graph theory;    small-world;   

DOI  :  10.3389/fneur.2020.00253

来源: DOAJ

【 摘 要 】

Modern network science has provided exciting new opportunities for understanding the human brain as a complex network of interacting regions. The improved knowledge of human brain network architecture has made it possible for clinicians to detect the network changes in neurological diseases. Generalized tonic–clonic seizure (GTCS) is a subtype of epilepsy characterized by generalized spike-wave discharge involving the bilateral hemispheres during seizure. Network researches in adults with GTCS exhibited that GTCS can be conceptualized as a network disorder. However, the overall organization of the brain structural covariance network in children with GTCS remains largely unclear. Here, we used a graph theory method to assess the gray matter structural covariance network organization of 14 pediatric patients diagnosed with GTCS and 29 healthy control children. The group differences in regional and global topological properties were investigated. Results revealed significant changes in nodal betweenness locating in brain regions known to be abnormal in GTCS (the right thalamus, bilateral temporal pole, and some regions of default mode network). The network hub analysis results were in accordance with the regional betweenness, which presented a disrupted regional topology of structural covariance network in children with GTCS. To our knowledge, the present study is the first work reporting the changes of structural topological properties in children with GTCS. The findings contribute new insights into the understanding of the neural mechanisms underlying GTCS and highlight critical regions for future neuroimaging research in children with GTCS.

【 授权许可】

Unknown