Lin Fuchun, Wu Guangyao, Zhu Ling, Lei Hao
Wuhan Center for Magnetic Resonance, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, China.
Department of Magnetic Resonance Imaging, Zhongnan Hospital, Wuhan University, China.
Addict Biol. 2015 Jul;20(4):809-19. doi: 10.1111/adb.12155. Epub 2014 Jun 24.
Recent neuroimaging studies have demonstrated that cigarette smoking is associated with changed brain structure and function. However, little is known about alterations of the topological organization of brain functional networks in heavy smokers. Thirty-one heavy smokers and 33 non-smokers underwent a resting-state functional magnetic resonance imaging scan. The whole-brain functional networks were constructed by thresholding the correlation matrices of 90 brain regions and their topological properties were analyzed using graph network analysis. Non-parametric permutation tests were performed to investigate group differences in network topological measures and multiple regression analysis was conducted to determine the relationships between the network metrics and smoking-related variables. Both heavy smokers and non-smokers exhibited small-world architecture in their brain functional networks. Compared with non-smokers, however, heavy smokers showed altered topological measurements characterized by lower global efficiency, higher local efficiency and clustering coefficients and greater path length. Furthermore, heavy smokers demonstrated decreased nodal global efficiency mainly in brain regions within the default mode network, whereas increased nodal local efficiency predominated in the visual-related regions. In addition, heavy smokers exhibited an association between the altered network metrics and the duration of cigarette use or the severity of nicotine dependence. Our results suggest that heavy smokers may have less efficient network architecture in the brain, and chronic cigarette smoking is associated with disruptions in the topological organization of brain networks. Our findings may further the understanding of the effects of chronic cigarette smoking on the brain and the pathophysiological mechanisms underlying nicotine dependence.
近期的神经影像学研究表明,吸烟与大脑结构和功能的改变有关。然而,对于重度吸烟者大脑功能网络拓扑组织的改变却知之甚少。31名重度吸烟者和33名非吸烟者接受了静息态功能磁共振成像扫描。通过对90个脑区的相关矩阵进行阈值处理构建全脑功能网络,并使用图网络分析方法分析其拓扑特性。进行非参数置换检验以研究网络拓扑指标的组间差异,并进行多元回归分析以确定网络指标与吸烟相关变量之间的关系。重度吸烟者和非吸烟者的大脑功能网络均呈现小世界架构。然而,与非吸烟者相比,重度吸烟者的拓扑测量结果发生了改变,表现为全局效率较低、局部效率和聚类系数较高以及路径长度更长。此外,重度吸烟者主要在默认模式网络内的脑区表现出节点全局效率降低,而在视觉相关区域则以节点局部效率增加为主。此外,重度吸烟者的网络指标改变与吸烟时长或尼古丁依赖程度之间存在关联。我们的结果表明,重度吸烟者的大脑网络架构效率可能较低,慢性吸烟与大脑网络拓扑组织的破坏有关。我们的发现可能会进一步加深对慢性吸烟对大脑的影响以及尼古丁依赖潜在病理生理机制的理解。