Literature DB >> 24962385

Altered brain functional networks in heavy smokers.

Fuchun Lin1, Guangyao Wu2, Ling Zhu2, Hao Lei1.   

Abstract

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.
© 2014 Society for the Study of Addiction.

Entities:  

Keywords:  Functional networks; heavy smokers; network efficiency; resting-state fMRI; small-world

Mesh:

Year:  2014        PMID: 24962385     DOI: 10.1111/adb.12155

Source DB:  PubMed          Journal:  Addict Biol        ISSN: 1355-6215            Impact factor:   4.280


  29 in total

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