Abstract
Previous electroencephalogram (EEG) studies revealed reduced spectral power during the resting state in smokers. However, few studies investigated the changes of global brain networks during the resting state in young smokers by EEG. In the present study, we used minimum spanning tree (MST) to assess the differences of global network efficiency between young smoker (n = 20) and nonsmokers (n = 20). Compared with healthy nonsmokers, young smokers showed decreased leaf fraction, kappa value, increased diameter and eccentricity value in alpha band (r = 0.574, p = 0.008), which suggested the global network efficiency was decreased in young smokers. We also found positive correlation between leaf fraction and onset time of smoking in smokers. These results provided more scientific evidence of the abnormal neural oscillations of young smokers and improved our understanding of smoking addiction.
Highlights
Annual smoking-attributable deaths was about 6 million in the world including one million in China (World Health Organization, 2013)
The horizontal electro-oculogram (HEOG) and vertical electro-oculogram (VEOG) recording were using two active Ag/AgCl electrodes placed at outer canthus of right eye and above the left eye
The kappa value responded to a tree high-degree and was decreased (t = −2.373, p = 0.023) in young smoker compare to nonsmoker
Summary
Annual smoking-attributable deaths was about 6 million in the world including one million in China (World Health Organization, 2013). “China Report on the Health Hazards of Smoking” in 2012 indicated China had more than 350 million smokers, of which 14 millions were young smokers. By using spectral analysis of neural oscillations in EEG, previous resting state studies had found decreased theta and delta power, increased beta power and inconsistent results in alpha band.in smokers (Rass et al, 2015). Graph theoretical network analyses (GTA) of EEG signal during the resting state was used to investigate the integrity and efficiency of global brain networks in brain diseases, by assessing the topology characteristics of global brain networks (Delbeuck et al, 2003; Lee et al, 2006; Leistedt et al, 2009; Fraga González et al, 2016). Few Decreased Efficiency in Young Smoker study used EEG to investigate the changes of global brain networks during the resting state in young smokers
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