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

Abstract

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.

Disrupted topological properties of functional networks in epileptic children with generalized tonic‐clonic seizures

“…Therefore, the findings of the present study suggest that children with GTCS showed a topological reorganization of the functional networks. Combining with the previous graph theory studies on children with epilepsy (Li et al., 2020; Qiu et al., 2017), the present study indicates that long‐term epilepsy history disrupts children's brain topology. The overall trend of brain topology in children with epilepsy would different from the adult with epilepsy.…”

“…Our recent studies in children with GTCS also found that the temporal regions of the DMN in the patient group showed abnormal brain activity and local coherence (Wang et al., 2018). Graph theory analysis on the GM structural covariance network found that children with GTCS showed significant alterations of the nodal betweenness in the right thalamus, bilateral temporal pole, and some regions of DMN (Li et al., 2020). In the present study, significant decreases of C p and nodal local efficiency in children with GTCS support the viewpoint that chronic epilepsy may disrupt the regional integration of their functional networks.…”

“…One recent study from our group also focused on children with GTCS and detected significant changes in brain gray matter volume and spontaneous brain activity in patients (Wang et al., 2018). Using graph theory method on the gray matter structural covariance network, children with GTCS showed significant changes in nodal betweenness locating in brain regions such as thalamus, temporal pole, and some regions of DMN (Li et al., 2020). Although specific changes of brain activity, functional connectivity and regional topology disruption of structural covariance network were detected in these previous studies of children with GTCS, the topological organization of their brain functional network is remain unclear.…”

Brain Structural Covariance Networks in Behavioral Variant of Frontotemporal Dementia

“…Moreover, the disruption of both normalized path length and global efficiency is indicative of an impaired functional integration of bvFTD networks, indicating a reduced ability to combine specialized information from distributed brain regions [10,49]. In the past years, several studies have investigated small-world property alterations in healthy individuals [58][59][60], as well as in neurological and psychiatric disorders [17,19,32,[61][62][63][64][65]. Neuroimaging studies have demonstrated that the cognitive and memory declines in Alzheimer's disease patients are often associated with the disruption of the small-world structure [17,27,66,67].…”

“…At the same time, their construction is less sensitive to noise in comparison to those of functional and DTI-based networks [27,28], and requires relatively lower computational loads [29]. Although several studies have used brain structural covariance and graph analysis in neurodegenerative diseases [14,[29][30][31][32][33], the investigation of changes in global and regional network characteristics within patients with bvFTD is still limited. To our knowledge, only one study has combined graph analysis and gray matter intensities to examine intra-individual structural covariation of the brain in bvFTD patients [34].…”