ArticleFrontiers in physiology2022
Graph Theory Analysis of the Cortical Functional Network During Sleep in Patients With Depression.
Article in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Response to letter regarding "hemispheric imbalance in mild cognitive impairment: a graph-theoretical analysis of multimodal brain networks".Annals of medicine · 2026Article
- Hemispheric asymmetry in depressive symptoms is associated with sex-divergent functional brain connectivity patterns.iScience · 2026Article
- From Brain Networks to Sleep Perception: EEG-Derived Global Efficiency is Associated with Subjective Sleep Quality in University Students.Nature and science of sleep · 2026Article
- Revolutionizing Sleep Science: A Narrative Review of the Historical Origins and Current Applications of Sleep Neuroimaging.Nature and science of sleep · 2025Review
- Abnormal topological organization of functional brain networks in the patients with anterior segment ischemic optic neuropathy.Frontiers in neuroscience · 2024Article
- Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends.Bioengineering (Basel, Switzerland) · 2023Review
- Investigating the influence of an adjustable zoned air mattress on sleep: a multinight polysomnography study.Frontiers in neuroscience · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
Depression, a common mental illness that seriously affects the psychological health of patients, is also thought to be associated with abnormal brain functional connectivity. This study aimed to explore the differences in the sleep-state functional network topology in depressed patients. A total of 25 healthy participants and 26 depressed patients underwent overnight 16-channel electroencephalography (EEG) examination. The cortical networks were constructed by using functional connectivity metrics of participants based on the weighted phase lag index (WPLI) between the EEG signals. The results indicated that depressed patients exhibited higher global efficiency and node strength than healthy participants. Furthermore, the depressed group indicated right-lateralization in the δ band. The top 30% of connectivity in both groups were shown in undirected connectivity graphs, revealing the distinct link patterns between the depressed and control groups. Links between the hemispheres were noted in the patient group, while the links in the control group were only observed within each hemisphere, and there were many long-range links inside the hemisphere. The altered sleep-state functional network topology in depressed patients may provide clues for a better understanding of the depression pathology. Overall, functional network topology may become a powerful tool for the diagnosis of depression.
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