The changes of brain functional networks in young adult smokers based on independent component analysis
XianFu Wang1,2, Ting Xue1,3, Fang Dong1
1Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, Inner Mongolia, China.
Abstract:
Intrinsic functional connectivity (FC) networks, including the default mode network (DMN), central executive network (CEN), and salience network (SN), have been implicated in nicotine addiction. However, litter evidence exists about the abnormalities in the three networks in young adult smokers. Forty-eight young adult smokers and 49 age- and gender-matched non-smokers were recruited in the present study. Resting-state functional magnetic resonance imaging (fMRI) data were analyzed by a combination of independent component analysis (ICA) and dual regression to identify potential differences of FC patterns in the DMN, CEN, and SN. Compared to non-smokers, young adult smokers showed enhanced FC of the left posterior cingulate cortex (LPCC), right medial prefrontal cortex (RMPFC) and right precuneus within the DMN network, of the right dorsolateral prefrontal cortex (DLPFC) within the right CEN, and of the left anterior insula (LAI) within the SN. We also found increased FC between the DMN, CEN and key node of the SN (anterior insula, AI). Correlation analysis showed that the increased FC within the networks was significantly correlated with smoking behaviors (pack-years, smoking duration, FTND, first smoking age, and number of cigarettes per day). Our findings may provide additional evidence for conceptualizing the framework of nicotine addiction as a disease of intercommunicating brain networks.
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