Graph theoretical analysis reveals disrupted topological properties of whole brain functional networks in temporal lobe epilepsy

Wang, Junjing; Qiu, Shijun; Xu, Yong; Liu, Zhenyin; Yang, Sihua; Hu, Xiangshu; Zhang, Ruibin; Li, Meng; Wang, Wensheng; Huang, Ruiwang

doi:10.1016/j.clinph.2013.12.120

Cited by 87 publications

(68 citation statements)

References 89 publications

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“…Previous studies have examined brain efficiency in both functional networks (Vlooswijk et al, 2011;Wang et al, 2014;Zhang et al, 2011) and structural networks in epilepsy (Bernhardt et al, 2011;Liu et al, 2014). However, these findings have remained conflicting potentially due to various factors such as different data processing approach and heterogeneous study population.…”

Section: Discussionmentioning

confidence: 97%

“…This regional, abnormal neuronal activity could potentially disrupt the base connectivity of individual brain regions as well as brain networks. Previous studies on epilepsy have shown topological changes of wholebrain functional networks in temporal lobe epilepsy (TLE) (Doucet et al, 2015;Wang et al, 2014) and in idiopathic generalized epilepsy (IGE) (Zhang et al, 2011). These studies showed epilepsy-related impairments in the whole-brain functional networks, including reduced clustering coefficient and increased global efficiency in TLE and IGE patients relative to healthy controls.…”

Section: Introductionmentioning

confidence: 88%

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Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis

et al. 2015

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The human brain is a complex and dynamic system that can be modeled as a large-scale brain network to better understand the reorganizational changes secondary to epilepsy. In this study, we developed a brain functional network model using graph theory methods applied to resting-state fMRI data acquired from a group of epilepsy patients and age-and gender-matched healthy controls. A brain functional network model was constructed based on resting-state functional connectivity. A minimum spanning tree combined with proportional thresholding approach was used to obtain sparse connectivity matrices for each subject, which formed the basis of brain networks. We examined the brain reorganizational changes in epilepsy thoroughly at the level of the whole brain, the functional network, and individual brain regions. At the whole-brain level, local efficiency was significantly decreased in epilepsy patients compared with the healthy controls. However, global efficiency was significantly increased in epilepsy due to increased number of functional connections between networks (although weakly connected). At the functional network level, there were significant proportions of newly formed connections between the default mode network and other networks and between the subcortical network and other networks. There was a significant proportion of decreasing connections between the cingulo-opercular task control network and other networks. Individual brain regions from different functional networks, however, showed a distinct pattern of reorganizational changes in epilepsy. These findings suggest that epilepsy alters brain efficiency in a consistent pattern at the whole-brain level, yet alters brain functional networks and individual brain regions differently.

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Section: Discussionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 88%

Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis

et al. 2015

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“…A more regularized topology of large-scale networks in TLE has also been shown in graph theoretical analyses of networks derived from diffusion MRI [135,138], task-free functional MRI [139], and interictal intracranial EEG [140]. A recent meta-analysis systematically assessed 12 studies that reported alterations in whole-brain clustering coefficient and characteristic path length based on MEG, MRI covariance, fMRI, and diffusion MRI [141].…”

Section: Is There a Consistent Pattern Of Topological Alterations In mentioning

confidence: 95%

Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy

Bernhardt

Bonilha

Gross

2015

Epilepsy & Behavior

228

181

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“…Moreover, the graph theoretical approaches can also identify highly connected regions in a network, so-called hub nodes, which play central roles in integrating diverse information sources and supporting fast communication with minimal energy cost [11]. These network properties can be used to demonstrate fundamental aspects of normal brain organization and highlight important aspects of underlying brain pathology in various neurologic diseases such as Alzheimer disease [12], Parkinson disease [13], and epilepsy [14]. These studies have suggested that many neurologic diseases could be produced by the dysfunction of a brain network.…”

Section: Introductionmentioning

confidence: 99%

Is Transient Global Amnesia a Network Disease?

2018

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Background: We evaluated a brain network using graph theoretical analysis and microstructural abnormalities of the white matter in patients with transient global amnesia (TGA). Methods: Twenty patients with TGA and healthy control subjects were recruited, and they underwent diffusion tensor imaging (DTI) scans. Graph theory was applied to obtain network measures based on DTI data. We investigated the network measures and microstructural abnormalities of white matter using tract-based spatial statistics (TBSS) analysis in the patients with TGA. Results: Measures of global topology were not different between the patients with TGA and healthy subjects. However, there were significant differences of hubs organization; the strength of the right superior and inferior orbitofrontal, the right inferior frontal operculum, the left superior parietal, and left postcentral gyrus, the cluster coefficient of the right middle orbitofrontal and left inferior parietal gyrus, the betweenness centrality of the left angular gyrus, and the pagerank centrality of the right superior and inferior orbitofrontal, right inferior frontal operculum, left superior parietal, and left postcentral gyrus in the patients with TGA were significantly lower than those in healthy subjects. Regarding the analysis of the white matter microstructure with TBSS, there were no differences in the fractional anisotropy and mean diffusivity values between the 2 groups. Conclusions: We newly identify a reorganization of network hubs of the brain network in patients with TGA, especially in the regions of the default-mode network. These alterations of the brain network may play a role in the pathophysiologic mechanism underlying TGA and suggest that TGA is a network disease.

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Graph theoretical analysis reveals disrupted topological properties of whole brain functional networks in temporal lobe epilepsy

Cited by 87 publications

References 89 publications

Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis

Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis

Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy

Is Transient Global Amnesia a Network Disease?

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