Altered resting state functional connectivity of anterior insula in young smokers
文献类型:期刊论文
作者 | Bi, Yanzhi1,2; Yuan, Kai1,2,3; Guan, Yanyan1,2; Cheng, Jiadong1,2; Zhang, Yajuan1,2; Li, Yangding1,2; Yu, Dahua3; Qin, Wei1,2; Tian, Jie1,2,4![]() |
刊名 | BRAIN IMAGING AND BEHAVIOR
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出版日期 | 2017-02-01 |
卷号 | 11期号:1页码:155-165 |
关键词 | Insula Resting State Functional Connectivity Young Smokers Cognitive Control Craving |
DOI | 10.1007/s11682-016-9511-z |
文献子类 | Article |
英文摘要 | The insula has been implicated in cognitive control and craving, all of which are critical to the clinical manifestations of nicotine dependence. However, little evidence exists about the abnormalities in resting state functional connectivity (RSFC) of the insula in young smokers, which might improve our understanding of the neural mechanisms of nicotine dependence. Due to the structural and functional heterogeneity of the insula, the RSFC patterns of both left and right anterior (AI) and posterior insula (PI) were investigated in young smokers and non-smokers. Meanwhile, the relationship was assessed between the neuroimaging findings and clinical information (pack-years, FTND, and craving) as well as cognitive control deficits measured by Stroop task performance. Compared with non-smokers, young smokers showed reduced RSFC between right AI and anterior cingulate cortex (ACC), ventromedial prefrontal cortex (VMPFC), amygdala, left dorsolateral prefrontal cortex, and dorsal striatum. Additionally, left AI showed reduced RSFC with ACC. Both left and right PI network differences were not observed between two groups. Moreover, in young smokers, FTND and incongruent errors in the Stroop task were negatively correlated with the RSFC between AI and ACC. Craving scores showed a significantly negative relationship with the RSFC strength between right AI and left VMPFC. These results provide a more thorough network-level understanding the role of insula in cigarette smoking. The findings provide new insights into the roles of AI-ACC circuit in cognitive control deficits and right AI-VMPFC circuit relevant to the craving of nicotine dependence for young smokers. |
WOS关键词 | TRANSCRANIAL MAGNETIC STIMULATION ; OLD-WORLD MONKEY ; SMOKING CUES ; NICOTINE DEPENDENCE ; CIGARETTE-SMOKING ; COGNITIVE CONTROL ; CINGULATE CORTEX ; BRAIN ; FMRI ; ADDICTION |
WOS研究方向 | Neurosciences & Neurology |
语种 | 英语 |
WOS记录号 | WOS:000400575300013 |
资助机构 | Project for the National Key Basic Research and Development Program(2014CB543203 ; National Natural Science Foundation of China(81571751 ; Natural Science Basic Research Plan in Shaanxi Province of China(2014JQ4118) ; Fundamental Research Funds for the Central Universities(JB151204 ; Natural Science Foundation of Inner Mongolia(2014BS0610) ; Innovation Fund Project of Inner Mongolia University of Science and Technology(2015QNGG03 ; General Financial Grant China Post-doctoral Science Foundation(2014 M552416) ; 2011CB707700 ; 81571753 ; JB121405) ; 2014QDL002) ; 2012CB518501) ; 61502376 ; 81401478 ; 81401488 ; 81271644 ; 81271546 ; 81271549 ; 81470816 ; 81471737 ; 81301281) |
源URL | [http://ir.ia.ac.cn/handle/173211/15259] ![]() |
专题 | 自动化研究所_中国科学院分子影像重点实验室 |
作者单位 | 1.Xidian Univ, Sch Life Sci & Technol, Xian 710071, Shaanxi, Peoples R China 2.Minist Educ, Engn Res Ctr Mol & Neuro Imaging, Xian, Peoples R China 3.Inner Mongolia Univ Sci & Technol, Sch Informat Engn, Informat Proc Lab, Baotou, Inner Mongolia, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Bi, Yanzhi,Yuan, Kai,Guan, Yanyan,et al. Altered resting state functional connectivity of anterior insula in young smokers[J]. BRAIN IMAGING AND BEHAVIOR,2017,11(1):155-165. |
APA | Bi, Yanzhi.,Yuan, Kai.,Guan, Yanyan.,Cheng, Jiadong.,Zhang, Yajuan.,...&Tian, Jie.(2017).Altered resting state functional connectivity of anterior insula in young smokers.BRAIN IMAGING AND BEHAVIOR,11(1),155-165. |
MLA | Bi, Yanzhi,et al."Altered resting state functional connectivity of anterior insula in young smokers".BRAIN IMAGING AND BEHAVIOR 11.1(2017):155-165. |
入库方式: OAI收割
来源:自动化研究所
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