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Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures
Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures
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Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures
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Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures
Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures

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Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures
Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures
Journal Article

Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures

2023
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Overview
Generalized tonic-clonic seizures (GTCS) are a subtype of generalized seizures exhibiting bursts of bilaterally synchronous generalized spike-wave discharges. Numerous neuroimaging studies have reported aberrant functional activity and topological organization of brain network in epilepsy patients with GTCS, but most studies have focused on adults. However, the effect of GTCS on the spatial and temporal properties of brain function in children remains unclear. The present study aimed to explore whole-brain static (sFC) and dynamic functional connectivity (dFC) in children with GTCS. Twenty-three children with GTCS and 32 matched healthy controls (HCs) were recruited for the present study. Resting-state functional magnetic resonance imaging (MRI) data were collected for each subject. The group independent component analysis method was used to obtain independent components (ICs). Then, sFC and dFC methods were applied and the differences in functional connectivity (FC) were compared between the children with GTCS and the HCs. Additionally, we investigated the correlations between the dFC indicators and epilepsy duration. Compared to HCs, GTCS patients exhibited a significant decrease in sFC strengths among most networks. The K-means clustering method was implemented for dFC analysis, and the optimal number of clusters was estimated: two discrete connectivity configurations, State 1 (strong connection) and State 2 (weak connection). The decreased dFC mainly occurred in State 1, especially the dFC between the visual network (VIS) and somatomotor network (SMN); but the increased dFC mainly occurred in State 2 among most networks in GTCS children. In addition, GTCS children showed significantly shorter mean dwell time and lower fractional windows in stronger connected State 1, while GTCS children showed significantly longer mean dwell time in weaker connected State 2. In addition, the dFC properties, including mean dwell time and fractional windows, were significantly correlated with epilepsy duration. Conclusion: Our results indicated that GTCS epilepsy not only alters the connectivity strength but also changes the temporal properties of connectivity in networks in the whole brain. These findings also emphasized the differences in sFC and dFC in children with GTCS. Combining sFC and dFC methods may provide more comprehensive understanding of the abnormal changes in brain architecture in children with GTCS.