Abstract：
Tobacco cigarette smoking is associated with disrupted brain network dynamics in resting brain networks including the Salience (SN) and Fronto parietal (FPN). Unified multimodal methods [Resting state connectivity analysis, Diffusion Tensor Imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and cortical thickness analysis] were employed to test the hypothesis that the impact of cigarette smoking on the balance among these networks is due to alterations in white matter connectivity, microstructural architecture, functional connectivity and cortical thickness (CT) and that these metrics define fundamental differences between people who smoke and nonsmokers. Multimodal analyses of previously collected 7 Tesla MRI data via the Human Connectome Project were performed on 22 people who smoke (average number of daily cigarettes was 10 ± 5) and 22 age- and sex-matched nonsmoking controls. First, functional connectivity analysis was used to examine SN-FPN-DMN interactions between people who smoke and nonsmokers. The anatomy of these networks was then assessed using DTI and CT analyses while microstructural architecture of WM was analyzed using the NODDI toolbox. Seed-based connectivity analysis revealed significantly enhanced within network [p = 0.001 FDR corrected] and between network functional coupling of the salience and R-frontoparietal networks in people who smoke [p = 0.004 FDR corrected]. The network connectivity was lateralized to the right hemisphere. Whole brain diffusion analysis revealed no significant differences between people who smoke and nonsmokers in Fractional Anisotropy, Mean diffusivity and in neurite orienting and density. There were also no significant differences in CT in the hubs of these networks. Our results demonstrate that tobacco cigarette smoking is associated with enhanced functional connectivity, but anatomy is largely intact in young adults. Whether this enhanced connectivity is pre-existing, transient or permanent is not known. The observed enhanced connectivity in resting state networks may contribute to the maintenance of smoking frequency.
摘要：
烟草吸烟与静息大脑网络中的大脑网络动力学中断有关，包括Salence（SN）和Fronto顶叶（FPN）。统一的多模态方法[静息状态连通性分析，扩散张量成像(DTI),神经突取向色散和密度成像（NODDI），和皮质厚度分析]用于测试以下假设：吸烟对这些网络之间平衡的影响是由于白质连通性的改变，微结构架构，功能连通性和皮质厚度（CT），以及这些指标定义了吸烟者和不吸烟者之间的基本差异。通过HumanConnectome项目对22名吸烟的人（平均每日吸烟数为10±5）和22名年龄和性别匹配的非吸烟对照进行了先前收集的7份TeslaMRI数据的多模态分析。首先,功能连接分析用于检查吸烟者和不吸烟者之间的SN-FPN-DMN相互作用.然后使用DTI和CT分析评估这些网络的解剖结构，同时使用NODDI工具箱分析WM的微结构架构。基于种子的连通性分析显示，吸烟人群[p=0.004FDR校正]的网络内部[p=0.001FDR校正]以及网络功能与R-额叶网络之间的网络功能耦合显着增强。网络连接被横向到右半球。全脑扩散分析显示，吸烟者和不吸烟者在分数各向异性上没有显著差异，平均扩散率和神经突的取向和密度。在这些网络的集线器中，CT也没有显着差异。我们的结果表明，吸烟与增强的功能连通性有关，但是年轻人的解剖学基本完好无损。这种增强的连接是否已经存在，暂时或永久未知。在静息状态网络中观察到的增强的连接性可以有助于维持吸烟频率。
