Aberrant functional network topology and effective connectivity in burnout syndrome

Abstract

Objective: Recent neuroimaging studies have demonstrated that burnout is linked to specific anatomical and functional abnormalities in the brain. However, topological alterations of brain networks are not yet characterized in burnout.

Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was performed on 32 female participants with burnout and 30 matched healthy controls. Subsequently, we employed graph theoretical and network-based statistic (NBS) methods to analyze the functional connectivity. We further explored the causal influences between brain regions using the Granger Causal Analysis. Finally, partial correlation analyses were conducted between clinical scores and the altered network properties as well as connectivity metrics.

Results: Both the participants with burnout and healthy controls displayed a small-world organization. However, participants with burnout showed increased characteristic path length and decreased global efficiency. Corresponding local changes were mainly distributed in the visual network (2/3,66.67%). With the network-based statistic (NBS) approach, significantly decreased effective connectivities were observed mainly between the visual network and the right hippocampus. In addition, characteristic path length and nodal local efficiency of the left fusiform gyrus showed a significant negative correlation with depression severity.

Conclusions: The present psychopathological findings reflect the disrupted global integration of the functional network related to the traits of participants with burnout.

Significance: These findings deliver novel insights from a full network perspective into the brain mechanisms of burnout.

Keywords: Burnout; Effective connectivity; Functional network topology; Network-based statistic analysis; Nurse.