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Objective: The present study aims to investigate the disturbance of functional and structural profiles of patients with generalized tonic-clonic seizures (GTCS)., Methods: Resting-state fMRI and diffusion tensor imaging (DTI) data was collected from fifty-six patients and sixty-two healthy controls. Degree centrality (DC) of functional connectivity was first calculated and compared between groups using a two-sample t-test. Furthermore, the regions with significant alteration of DC in patients with GTCS were used as nodes to construct the brain network. Functional connectivity (FC) network was constructed using the Person's correlation analysis and structural connectivity (SC) network was obtained using deterministic tractography technology. Gray matter volume (GMV) and cortical thickness (CT) were computed and correlated with connective profiles., Results: The patients with GTCS showed increased DC in the primary network (PN), including bilateral precentral gyrus, supplementary motor areas (SMA), and visual cortex, and decreased DC in core regions of default mode network (DMN), bilateral anterior insular, and supramarginal gyrus. In the present study, 14 regions were identified to construct networks. In patients, the FC and SC were increased within the sensorimotor network (mainly linking with SMA) and decreased within DMN (mainly linking with the posterior cingulate cortex (PCC)). Except for the decreased FC and SC between cerebellum and SMA, patients demonstrated increased connectivity between DMN and PN. Besides, the insula demonstrated decreased FC with DMN and increased FC with PN, without significant SC alterations in patients with GTCS. Decreased GMV in bilateral thalamus and increased GMV in frontoparietal regions were found in patients. The decreased GMV of thalamus and increased GMV of SMA positively and negatively correlated with the FC between PCC and left superior frontal cortex, the FC between SMA and left precuneus respectively., Conclusion: Hyper-connectivity within PN helps to understand the disturbance of primary functions, especially the motor abnormality in GTCS. The hypo-connectivity within DMN suggested abnormal network organization possibly related to epileptogenesis. Moreover, over-interaction between DMN and PN and unbalanced connectivity between them and insula provided potential evidence reflecting abnormal interactions between primary and high-order function systems., (Copyright © 2021. Published by Elsevier B.V.)

Benign epilepsy with centrotemporal spikes (BECT) is the most common childhood idiopathic focal epilepsy syndrome, which characterized with white‐matter abnormalities in the rolandic cortex. Although diffusion tensor imaging research could characterize white‐matter structural architecture, it cannot detect neural activity or white‐matter functions. Recent studies demonstrated the functional organization of white‐matter by using functional magnetic resonance imaging (fMRI), suggesting that it is feasible to investigate white‐matter dysfunctions in BECT. Resting‐state fMRI data were collected from 24 new‐onset drug‐naive (unmedicated [NMED]), 21 medicated (MED) BECT patients, and 27 healthy controls (HC). Several white‐matter functional networks were obtained using a clustering analysis on voxel‐by‐voxel correlation profiles. Subsequently, conventional functional connectivity (FC) was calculated in four frequency sub‐bands (Slow‐5:0.01–0.027, Slow‐4:0.027–0.073, Slow‐3:0.073–0.198, and Slow‐2:0.198–0.25 Hz). We also employed a functional covariance connectivity (FCC) to estimate the covariant relationship between two white‐matter networks based on their correlations with multiple gray‐matter regions. Compared with HC, the NMED showed increased FC and/or FCC in rolandic network (RN) and precentral/postcentral network, and decreased FC and/or FCC in dorsal frontal network, while these alterations were not observed in the MED group. Moreover, the changes exhibited frequency‐specific properties. Specifically, only two alterations were shared in at least two frequency bands. Most of these alterations were observed in the frequency bands of Slow‐3 and Slow‐4. This study provided further support on the existence of white‐matter functional networks which exhibited frequency‐specific properties, and extended abnormalities of rolandic area from the perspective of white‐matter dysfunction in BECT. [ABSTRACT FROM AUTHOR]

Benign epilepsy with centrotemporal spikes (BECTS) is the most common idiopathic focal childhood epilepsy associated with either unilateral or bilateral epileptic discharge. Asymmetry as an important characteristic of the human brain is beneficial for brain functions. However, little is known about on asymmetry of BECTS patients with different epileptic spikes pattern. In the present study, we investigated functional and structural asymmetries in unilateral spikes BECTS (U_BECTS) patients and bilateral spikes BECTS (B_BECTS) patients using resting state functional magnetic resonance images and diffusion tensor imaging. Compared with the controls, we observed a decreased voxel-mirrored interhemispheric functional connectivity (FC) in primary sensorimotor cortex (SM1) in U_BECTS and B_BECTS groups, and reduced fractional anisotropy (FA) values of the corpus callosum (CC) connecting bilateral SM1 were also observed in B_BECTS group. Further region-based FC map analysis of SM1 demonstrated increased functional asymmetry with ipsilateral hemisphere, contralateral hemisphere and the whole brain in U_BECTS and increased functional asymmetry with the contralateral hemisphere and the whole brain in B_BECTS groups. The correlation between functional asymmetry of SM1 and intelligence quotient scores was found in the U_BECTS group. The altered asymmetries of the SM1 further indicated the important role of SM1 in the pathophysiology of the BECTS. Furthermore, the B_BECTS group also showed abnormal voxel-mirrored interhemispheric FC in the temporal pole, the lobule IX of the cerebellum, the caudate and the occipital cortex relative to the controls. Altogether, our findings provide additional insight into the neuronal mechanism of BECTS with different epileptic spikes pattern and cognitive impairments with BECTS patients. [ABSTRACT FROM AUTHOR]