Altered brain dynamic functional network connectivity in heavy smokers

Cigarette smoking is associated with altered static functional connectivity, however, studies on functional connectivity dynamics may provide new insightful perspectives for understanding the neural mechanisms of smoking addiction. The aim of this study was to investigate the characteristics of dynamic functional network connectivity (dFNC) in heavy smokers. DFNC analysis based on sliding window approach and k -means clustering was performed to the resting-state functional magnetic resonance imaging data of 34 heavy smokers and 36 healthy non-smokers. The between-group differences in temporal properties of dFNC states were assessed, followed by a correlation analysis of these differences with smoking-related factors in heavy smokers. Compared to non-smokers, heavy smokers showed a lower occurrence rate and mean dwell time in state 2, characterized by negative connectivity between the default-mode network and the other networks. Heavy smokers also had a trend toward higher occurrence rate and mean dwell time in state 1, characterized by global weak connectivity. Network-based statistics identified cognitive control and cerebellar domains played an important role in the impaired subnetworks. Correlation analyses demonstrated that in heavy smokers, both the occurrence rate and the mean dwell time were negatively associated with the duration of smoking in state 2, characterized by high connectivity within the sensory domains. Our findings suggest that dFNC abnormalities in heavy smokers may become new neuroimaging biomarkers and provide a deeper understanding of the pathophysiological mechanisms of smoking addiction.