Effects of Tai Chi on Multiple Brain Networks Structure–Function Couplings in Individuals with Subthreshold Depression: A Randomized Controlled Trial

INTRODUCTION: Subthreshold depression represents a prodromal stage of major depressive disorder and may be associated with abnormalities in brain structural and functional networks. While studies have shown that mind-body exercises such as Tai Chi can alleviate subthreshold depression, the underlying mechanisms remain unclear. Purpose: This study aimed to explore the potential mechanisms of Tai Chi for improving subthreshold depression from the perspective of structure-function coupling of brain networks. METHODS: This randomized controlled trial enrolled 112 individuals with subthreshold depression, randomly assigning them to either the Tai Chi group or a waitlist control group. Participants in the Tai Chi group received three 60-min training sessions per week for 12 wk. Outcome measures included assessments of negative mood symptoms, such as depression and stress, as well as structural and functional brain imaging. RESULTS: After accounting for the dropout of nine participants, a total of 103 individuals were included in the final statistical analysis. Compared with the control group, participants in the Tai Chi group exhibited significant reductions in depression, stress, and anxiety scores. Network analyses revealed a decrease in structure-function coupling and characteristic path length within the frontoparietal network following Tai Chi practice. Further nodal analyses indicated a significant reduction in nodal degree and efficiency in the left prefrontal cortex and posterior cingulate gyrus, while increases were observed in the right lateral prefrontal cortex. Partial correlation analysis demonstrated a significant negative correlation between right prefrontal efficiency and anxiety scores. CONCLUSIONS: The benefits of Tai Chi on subthreshold depression may be related to modulating the structure-function coupling of the frontoparietal network and increasing nodal efficiency.