| Literature DB >> 34668168 |
Yun Wu1,2,3, Yuan Zhong4,5, Gang Zheng6,7, Ya Liu6,7, Manlong Pang1,2,3, Huazhen Xu1,8, Huachen Ding1,8, Chun Wang9,10,11, Ning Zhang1,2,3.
Abstract
Recent neuroimaging studies have identified alterations in activity and connectivity among many brain regions as potential biomarkers for panic disorder. However, the functional connectome of panic disorder is not well understood. Therefore, a graph-theoretical approach was applied in this study to construct functional networks of patients and healthy controls in order to discover topological changes in panic disorder. 31 patients and 33 age and sex matched healthy controls underwent resting-state functional magnetic resonance imaging. Brain networks for each participant were structured using nodes from the Anatomical Automatic Labeling template and edges from connectivity matrices. Then, topological organizations of networks were calculated. Network-based statistical analysis was conducted, and global and nodal properties were compared between patients and controls. Unlike controls, patients with panic disorder displayed a small-world network. Patients also revealed decreased nodal efficiency in right superior frontal gyrus (SFG), middle frontal gyrus (MFG), right superior temporal gyrus (STG), and left middle temporal gyrus (MTG). Decreased functional connectivity was found in panic disorder between right MTG and extensive temporal regions. Among these disrupted regions, the decreased nodal efficiency of SFG showed a positive correlation with clinical symptoms while nodal betweenness centrality in angular gyrus showed a negative correlation. Our results indicated decreased function of global and regional information transmission in panic disorder and emphasized the role of temporal regions in its pathology.Entities:
Keywords: Graph theory; Magnetic resonance imaging; Network-based statistic; Temporal lobe
Mesh:
Year: 2021 PMID: 34668168 DOI: 10.1007/s11682-021-00563-z
Source DB: PubMed Journal: Brain Imaging Behav ISSN: 1931-7557 Impact factor: 3.224