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.
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