ArticleEpilepsy research2016
Low functional robustness in mesial temporal lobe epilepsy.
Article in Epilepsy research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Convergent functional networks of intrinsic activity alterations in temporal lobe epilepsy and their molecular correlates.Frontiers in molecular neuroscience · 2026Article
- Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data.Scientific reports · 2025Article
- DeepEZ: A Graph Convolutional Network for Automated Epileptogenic Zone Localization From Resting-State fMRI Connectivity.IEEE transactions on bio-medical engineering · 2023Article
- Cerebellar functional disruption and compensation in mesial temporal lobe epilepsy.Frontiers in neurology · 2023Article
- Reproducibility of graph measures derived from resting-state MEG functional connectivity metrics in sensor and source spaces.Human brain mapping · 2022Article
- Regional and global resting-state functional MR connectivity in temporal lobe epilepsy: Results from the Epilepsy Connectome Project.Epilepsy & behavior : E&B · 2021Article
- Lateralization of epilepsy using intra-hemispheric brain networks based on resting-state MEG data.Human brain mapping · 2020Article
- Using Low-Frequency Oscillations to Detect Temporal Lobe Epilepsy with Machine Learning.Brain connectivity · 2019Article
- Predicting seizure outcome of vagus nerve stimulation using MEG-based network topology.NeuroImage. Clinical · 2018Article
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Authors and funding
4 authors.
Funding
Abstract
objectivesBrain functional topology was investigated in patients with mesial temporal lobe epilepsy (mTLE) by means of graph theory measures in two differentially defined graphs. Measures of segregation, integration, and centrality were compared between subjects with mTLE and healthy controls (HC).
methodsEleven subjects with mTLE (age 36.5±10.9years) and 15 age-matched HC (age 36.8±14.0years) participated in this study. Both anatomically and functionally defined adjacency matrices were used to investigate the measures. Binary undirected graphs were constructed to study network segregation by calculating global clustering and modularity, and network integration by calculating local and global efficiency. Node degree and participation coefficient were also computed in order to investigate network hubs and their classification into provincial or connector hubs. Measures were investigated in a range of low to medium graph density.
resultsThe group of patients presented lower global segregation than HC while showing higher global but lower local integration. They also failed to engage regions that comprise the default-mode network (DMN) as hubs such as bilateral medial frontal regions, PCC/precuneus complex, and right inferior parietal lobule, which were present in controls. Furthermore, the cerebellum in subjects with mTLE seemed to be playing a major role in the integration of their functional networks, which was evident through the engagement of cerebellar regions as connector hubs.
conclusionsFunctional networks in subjects with mTLE presented both global and local abnormalities compared to healthy subjects. Specifically, there was significant separation between groups, with lower global segregation and slightly higher global integration observed in patients. This could be indicative of a network that is working as a whole instead of in segregated or specialized communities, which could translate into a less robust network and more prone to disruption in the group with epilepsy. Furthermore, functional irregularities were also observed in the group of patients in terms of the engagement of cerebellar regions as hubs while failing to engage DMN-related areas as major hubs in the network. The use of two differentially defined graphs synergistically contributed to findings.
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