Genetic generalized epilepsy is a network disorder typically involving distributed areas identified by classical neuroanatomy. However, the finer topological relationships in terms of continuous spatial arrangement between these systems are still ambiguous. Connectome gradients provide the topological representations of human macroscale hierarchy in an abstract low-dimensional space by embedding the functional connectome into a set of axes. Leveraging connectome gradients, we systematically scrutinized abnormalities of functional connectome gradient in patients with genetic generalized epilepsy with tonic-clonic seizure (GGE-GTCS, n = 78) compared to healthy controls (HC, n = 85), and further examined the reproducibility across multiple processing configurations and in an independent validation sample (patients with GGE-GTCS, n = 28; HC, n = 31). Our findings demonstrated an extended principal gradient at different spatial scales, network-level and vertex-level, in patients with GGE-GTCS. We found consistent results across processing parameters and in validation sample. The extended principal gradient revealed the excessive functional segregation between unimodal and transmodal systems associated with duration of epilepsy and age at seizure onset in patients. Furthermore, the connectivity profile of regions with abnormal principal gradients verified the disrupted functional hierarchy revealed by gradients. Together, our findings provided a novel view of functional system hierarchy alterations, which facilitated a continuous spatial arrangement of macroscale networks, to increase our understanding of the functional connectome hierarchy in generalized epilepsy.

Generalized tonic–clonic seizures (GTCS) are the severest and most remarkable clinical expressions of human epilepsy. Cortical, subcortical, and cerebellar structures, organized with different network patterns, underlying the pathophysiological substrates of genetic associated epilepsy with GTCS (GE‐GTCS) and focal epilepsy associated with focal to bilateral tonic–clonic seizure (FE‐FBTS). Structural covariance analysis can delineate the features of epilepsy network related with long‐term effects from seizure. Morphometric MRI data of 111 patients with GE‐GTCS, 111 patients with FE‐FBTS and 111 healthy controls were studied. Cortico‐striato‐thalao‐cerebellar networks of structural covariance within the gray matter were constructed using a Winner‐take‐all strategy with five cortical parcellations. Comparisons of structural covariance networks were conducted using permutation tests, and module effects of disease duration on networks were conducted using GLM model. Both patient groups showed increased connectivity of structural covariance relative to controls, mainly within the striatum and thalamus, and mostly correlated with the frontal, motor, and somatosensory cortices. Connectivity changes increased as a function of epilepsy durations. FE‐FBTS showed more intensive and extensive gray matter changes with volumetric loss and connectivity increment than GE‐GTCS. Our findings implicated cortico‐striato‐thalamo‐cerebellar network changes at a large temporal scale in GTCS, with FE‐FBTS showing more severe network disruption. The study contributed novel imaging evidence for understanding the different epilepsy syndromes associated with generalized seizures.

Functional connectivity hierarchy is an important principle in the process of brain functional organization and an important feature reflecting brain development. However, atypical brain network hierarchy organization in Rolandic epilepsy have not been systematically investigated. We examined connectivity alteration with age and its relation to epileptic incidence, cognition, or underlying genetic factors in 162 cases of Rolandic epilepsy and 117 typically developing children, by measuring fMRI multi-axis functional connectivity gradients. Rolandic epilepsy is characterized by contracting and slowing expansion of the functional connectivity gradients, highlighting the atypical age-related change of the connectivity hierarchy in segregation properties. The gradient alterations are relevant to seizure incidence, cognition, and connectivity deficit, and development-associated genetic basis. Collectively, our approach provides converging evidence for atypical connectivity hierarchy as a system-level substrate of Rolandic epilepsy, suggesting this is a disorder of information processing across multiple functional domains, and established a framework for large-scale brain hierarchical research.

Brain structural covariance network (SCN) can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network (CaSCN), winner-take-all and cortex–subcortex covariance network (WTA-CSSCN), and modulation analysis of structural covariance network (MOD-SCN) have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface (GUI) toolkit of brain structural covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily.

The objective was to study the modulation effects of levetiracetam on the fMRI activation/deactivation patterns associated with centrotemporal spikes (CTS) in Rolandic epilepsy. Forty patients with Rolandic epilepsy, including levetiracetam-medicated patients (n = 20) and drug-naive patients (n = 20), were studied. Single and sequential hemodynamic response functions-based EEG-fMRI analysis was performed to detect dynamic activation/deactivation associated with CTS. Comparisons of spatiotemporal features of activation/deactivation were performed between the two groups. Both the groups (CTS were detected in 12 cases of levetiracetam-medicated group, and 11 cases of drug-naive group) showed CTS-associated activation in the Rolandic cortex, whereas activation strength, time-to-peak delay, and overall activation were diminished in the levetiracetam-medicated group. Moreover, the drug-naive group showed deactivation in the regions engaged in higher cognition networks compared with the levetiracetam-medicated group. Levetiracetam inhibits CTS-associated activation intensity and alters the temporal pattern of this activation in the epileptogenic regions, and it also affects the brain deactivation related to higher cognition networks. The findings sheds a light on the pharmocological mechanism of levetiracetam therapy on Rolandic epilepsy.