AUTHOR=Song Yingjie , Wang Kejie , Wei Yu , Zhu Yongpeng , Wen Jinfeng , Luo Yuxi 

TITLE=Graph Theory Analysis of the Cortical Functional Network During Sleep in Patients With Depression

JOURNAL=Frontiers in Physiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.858739

DOI=10.3389/fphys.2022.858739

ISSN=1664-042X

ABSTRACT=Depression is a prevalent mental illness that seriously affects the psychological health of patients, which is also thought to be related to the aberrant functional connectivity of the brain. Consequently, the goals of the current study were to explore the difference in sleep-state functional network topology in depressed patients. Twenty-five healthy participants and twenty-six depressed patients underwent overnight 16-channel electroencephalography (EEG) examination. The cortical networks were constructed by using functional connectivity metrics of participants based on weighted phase lag index (WPLI) between EEG signals. The results indicated that both global efficiency and node strength were greater in the depressed patients than in healthy participants. Furthermore, depressed group indicated right-lateralization in δ band. Top 30% connectivity in both groups were shown in undirected connectivity graphs, which revealed different link patterns between depressed group and healthy control. In the patient group, links between hemispheres were observed. On the contrary, the link of the control group is only indicated within each hemisphere and there are many long-range links inside the hemisphere. Altered sleep-state functional network topology in depressed patients may provide clues to understanding the pathology of depression. And functional network topology may become a powerful tool for the diagnosis of depression.