Altered functional–structural coupling of large-scale brain networks in idiopathic generalized epilepsy

Abstract

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.

Long‐term acclimatization to high‐altitude hypoxia modifies interhemispheric functional and structural connectivity in the adult brain

“…2014), and it is widely assumed that structural connectivity is relatively stable over time, whereas functional connectivity is more variable (Zhang et al. 2011). Therefore, we hypothesized that homotopic functional brain reorganization was initially triggered to compensate for the compromised microstructural integrity of transcallosal WM fibers, and the functional deficits in the unilateral visual cortex, such as long‐term interhemispheric functional enhancement, may induce a dynamic modification of structural connectivity.…”

Resting-state fMRI studies in epilepsy

“…Having both fairly high spatial and temporal resolu- analysis [68][69][70] , graph theory [61,62] , and dynamic causal modeling [64] . Applications of these methods to epilepsy need close collaboration among multi-disciplinary investigators, especially when multiple techniques (e.g., structural MRI, diffusion MRI, EEG, as well as fMRI) are required.…”

“…First, the defini- by-moment dynamic changes in resting-state functional connectivity [59] provide a new approach to the network dynamics during different phases of seizures [60] . Fifth, linear correlation-based graph theory has been used to depict the complex network and has shown an altered small-world property in epilepsy [61,62] . More studies are needed to determine its clinical importance.…”

Identifying Corticothalamic Network Epicenters in Patients with Idiopathic Generalized Epilepsy

“…Only values above a predefined threshold (corresponding to P ϭ .05/M) were transformed to z values and summed as the FCS value of cortical or thalamic subregion voxels. The FCS value is referred to as the "degree centrality" of weighted networks 20 ; voxels with higher FCS values indicate a greater role in the heterogeneity of the capacity and intensity of connections.…”