The human brain is a large-scale integrated network in the functional and structural domain. Graph theoretical analysis provides a novel framework for analysing such complex networks. While previous neuroimaging studies have uncovered abnormalities in several specific brain networks in patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures, little is known about changes in whole-brain functional and structural connectivity networks. Regarding functional and structural connectivity, networks are intimately related and share common small-world topological features. We predict that patients with idiopathic generalized epilepsy would exhibit a decoupling between functional and structural networks. In this study, 26 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 26 age- and sex-matched healthy controls were recruited. Resting-state functional magnetic resonance imaging signal correlations and diffusion tensor image tractography were used to generate functional and structural connectivity networks. Graph theoretical analysis revealed that the patients lost optimal topological organization in both functional and structural connectivity networks. Moreover, the patients showed significant increases in nodal topological characteristics in several cortical and subcortical regions, including mesial frontal cortex, putamen, thalamus and amygdala relative to controls, supporting the hypothesis that regions playing important roles in the pathogenesis of epilepsy may display abnormal hub properties in network analysis. Relative to controls, patients showed further decreases in nodal topological characteristics in areas of the default mode network, such as the posterior cingulate gyrus and inferior temporal gyrus. Most importantly, the degree of coupling between functional and structural connectivity networks was decreased, and exhibited a negative correlation with epilepsy duration in patients. Our findings suggest that the decoupling of functional and structural connectivity may reflect the progress of long-term impairment in idiopathic generalized epilepsy, and may be used as a potential biomarker to detect subtle brain abnormalities in epilepsy. Overall, our results demonstrate for the first time that idiopathic generalized epilepsy is reflected in a disrupted topological organization in large-scale brain functional and structural networks, thus providing valuable information for better understanding the pathophysiological mechanisms of generalized tonic-clonic seizures.

Studies of in mesial temporal lobe epilepsy (mTLE) patients with hippocampal sclerosis (HS) have reported reductions in both functional and structural connectivity between hippocampal structures and adjacent brain regions. However, little is known about the connectivity among the default mode network (DMN) in mTLE. Here, we hypothesized that both functional and structural connectivity within the DMN were disturbed in mTLE. To test this hypothesis, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were applied to examine the DMN connectivity of 20 mTLE patients, and 20 gender- and age-matched healthy controls. Combining these two techniques, we explored the changes in functional (temporal correlation coefficient derived from fMRI) and structural (path length and connection density derived from DTI tractography) connectivity of the DMN. Compared to the controls, we found that both functional and structural connectivity were significantly decreased between the posterior cingulate cortex (PCC)/precuneus (PCUN) and bilateral mesial temporal lobes (mTLs) in patients. No significant between-group difference was found between the PCC/PCUN and medial prefrontal cortex (mPFC). In addition, functional connectivity was found to be correlated with structural connectivity in two pairwise regions, namely between the PCC/PCUN and bilateral mTLs, respectively. Our results suggest that the decreased functional connectivity within the DMN in mTLE may be a consequence of the decreased connection density underpinning the degeneration of structural connectivity.

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Although the brain areas in the default-mode network (DMN) act in a coordinated way during rest, the activity levels in the individual areas of the DMN are highly heterogeneous. The relation between the activity levels and the pattern of causal interaction among the DMN areas remains unknown. In the present fMRI study, seven nodes of the DMN were identified and their activity levels were rank-ordered based on a power spectral analysis of the resting blood oxygenation level-dependent (BOLD) signals. Furthermore, the direction of information flow among these DMN nodes was determined using Granger causality analysis and graph-theoretic methods. We found that the activity levels in these seven DMN nodes had a highly consistent hierarchical distribution, with the highest activity level in the posterior cingulate/precuneus cortices, followed by ventral medial prefrontal cortex and dorsal medial prefrontal cortex, and with the lowest level in the left inferior temporal gyrus. Importantly, a significant correlation was found between the activity levels and the In-Out degrees of information flow across the DMN nodes, suggesting that Granger causal influences can be used to predict BOLD activity levels. These findings shed light on the dynamical organization of cortical neuronal networks and may provide the basis for characterizing network disruption by brain disorders.

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Objective: Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. Although it is commonly related to hippocampal pathology, increasing evidence suggests structural changes beyond the mesiotemporal lobe. Functional anomalies and their link to underlying structural alterations, however, remain incompletely understood. Methods: We studied 30 drug-resistant TLE patients and 57 healthy controls using multimodal magnetic resonance imaging (MRI) analyses. All patients had histologically verified hippocampal sclerosis and underwent postoperative imaging to outline the extent of their surgical resection. Our analysis leveraged a novel resting-state functional MRI framework that parameterizes functional connectivity distance, consolidating topological and physical properties of macroscale brain networks. Functional findings were integrated with morphological and microstructural metrics, and utility for surgical outcome prediction was assessed using machine learning techniques. Results: Compared to controls, TLE patients showed connectivity distance reductions in temporoinsular and prefrontal networks, indicating topological segregation of functional networks. Testing for morphological and microstructural associations, we observed that functional connectivity contractions occurred independently from TLE-related cortical atrophy but were mediated by microstructural changes in the underlying white matter. Following our imaging study, all patients underwent an anterior temporal lobectomy as a treatment of their seizures, and postsurgical seizure outcome was determined at a follow-up at least 1 year after surgery. Using a regularized supervised machine learning paradigm with fivefold cross-validation, we demonstrated that patient-specific functional anomalies predicted postsurgical seizure outcome with 76 ± 4% accuracy, outperforming classifiers operating on clinical and structural imaging features.

ObjectiveNeuroimaging evidence suggested that the thalamic nuclei may play different roles in the progress of idiopathic generalized epilepsy (IGE). This study aimed to demonstrate the alterations in morphometry and functional connectivity in the thalamic nuclei in IGE.MethodsFifty-two patients with IGE characterized by generalized tonic-clonic seizures and 67 healthy controls were involved in the study. The three-dimensional high-resolution T1-weighted MRI data were acquired for voxel-based morphometry (VBM) analysis, and resting-state blood-oxygenation level functional MRI data were acquired for functional connectivity analysis. The thalamic nuclei of bilateral medial dorsal nucleus (MDN) and pulvinar, as detected with decreased gray matter volumes in patients with IGE through VBM analysis, were selected as seed regions for functional connectivity analysis.ResultsDifferent alteration patterns were found in functional connectivity of the thalamic nuclei with decreased gray matter volumes in IGE. Seeding at the MDN, decreased connectivity in the bilateral orbital frontal cortex, caudate nucleus, putamen and amygdala were found in the patients (P<0.05 with correction). However, seeding at the pulvinar, no significant alteration of functional connectivity was found in the patients (P<0.05 with correction).ConclusionsSome specific impairment of thalamic nuclei in IGE was identified using morphological and functional connectivity MRI approaches. These findings may strongly support the different involvement of the thalamocortical networks in IGE.