ArticleCNS neuroscience & therapeutics2023
Abnormal brain functional network dynamics in sleep-related hypermotor epilepsy.
Article in CNS neuroscience & therapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Disparities in Connectivity Profiles Between Structural and Functional Networks in Patients With Temporal Lobe Epilepsy.Brain and behavior · 2025Article
- Abnormal dynamic functional connectivity and topological properties of cerebellar network in male obstructive sleep apnea.CNS neuroscience & therapeutics · 2024Article
- Abnormal brain functional network dynamics in sleep-related hypermotor epilepsy.CNS neuroscience & therapeutics · 2023Article
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Authors and funding
12 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsThis study aimed to use resting-state functional magnetic resonance imaging (rs-fMRI) to determine the temporal features of functional connectivity states and changes in connectivity strength in sleep-related hypermotor epilepsy (SHE).
methodsHigh-resolution T1 and rs-fMRI scanning were performed on all the subjects. We used a sliding-window approach to construct a dynamic functional connectivity (dFC) network. The k-means clustering method was performed to analyze specific FC states and related temporal properties. Finally, the connectivity strength between the components was analyzed using network-based statistics (NBS) analysis. The correlations between the abovementioned measures and disease duration were analyzed.
resultsAfter k-means clustering, the SHE patients mainly exhibited two dFC states. The frequency of state 1 was higher, which was characterized by stronger connections within the networks; state 2 occurred at a relatively low frequency, characterized by stronger connections between networks. SHE patients had greater fractional time and a mean dwell time in state 2 and had a larger number of state transitions. The NBS results showed that SHE patients had increased connectivity strength between networks. None of the properties was correlated with illness duration among patients with SHE.
conclusionThe patterns of dFC patterns may represent an adaptive and protective mode of the brain to deal with epileptic seizures.
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