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.

中文翻译：

---

基于独立成分分析的年轻成年吸烟者脑功能网络的变化。

内在功能连接（FC）网络，包括默认模式网络（DMN），中央执行网络（CEN）和显着网络（SN），已与尼古丁成瘾有关。然而，存在关于年轻成年吸烟者三个网络异常的垃圾证据。在本研究中，招募了48名年轻的成年吸烟者以及49名年龄和性别相匹配的不吸烟者。通过结合独立分量分析（ICA）和双重回归分析对静止状态功能磁共振成像（fMRI）数据进行分析，以识别DMN，CEN和SN中FC模式的潜在差异。与不吸烟者相比，年轻的成年吸烟者显示DMN网络内左后扣带回皮层（LPCC），右前额叶皮层（RMPFC）和右前突的FC增强，右CEN内的右背外侧前额叶皮层（DLPFC）和SN内的左前岛（LAI）。我们还发现，DMN，CEN和SN的关键节点（前岛，AI）之间的FC增加。相关分析表明，网络中FC的增加与吸烟行为（包装年数，吸烟时间，FTND，首次吸烟年龄和每天吸烟的数量）显着相关。我们的发现可能为将尼古丁成瘾框架概念化为相互交流的大脑网络疾病提供更多证据。相关分析表明，网络中FC的增加与吸烟行为（包装年数，吸烟时间，FTND，首次吸烟年龄和每天吸烟的数量）显着相关。我们的发现可能为将尼古丁成瘾框架概念化为相互交流的大脑网络疾病提供更多证据。相关分析表明，网络中FC的增加与吸烟行为（包装年数，吸烟时间，FTND，首次吸烟年龄和每天吸烟的数量）显着相关。我们的发现可能为将尼古丁成瘾框架概念化为相互交流的大脑网络疾病提供更多证据。