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Brain Imaging and Behavior

, Volume 11, Issue 1, pp 155–165 | Cite as

Altered resting state functional connectivity of anterior insula in young smokers

  • Yanzhi Bi
  • Kai Yuan
  • Yanyan Guan
  • Jiadong Cheng
  • Yajuan Zhang
  • Yangding Li
  • Dahua Yu
  • Wei Qin
  • Jie Tian
Original Research

Abstract

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.

Keywords

Insula Resting state functional connectivity Young smokers Cognitive control Craving 

Notes

Acknowledgments

This paper is supported by the Project for the National Key Basic Research and Development Program (973) under Grant nos. 2014CB543203, 2011CB707700, 2012CB518501, the National Natural Science Foundation of China under Grant nos. 81571751, 81571753, 61502376, 81401478, 81401488, 81271644, 81271546, 81271549, 81470816, 81471737, 81301281, the Natural Science Basic Research Plan in Shaanxi Province of China under Grant no. 2014JQ4118, and the Fundamental Research Funds for the Central Universities under the Grant nos. JB151204, JB121405, the Natural Science Foundation of Inner Mongolia under Grant no. 2014BS0610, the Innovation Fund Project of Inner Mongolia University of Science and Technology Nos. 2015QNGG03, 2014QDL002, General Financial Grant the China Post- doctoral Science Foundation under Grant no. 2014 M552416.

Compliance with ethical standards

Conflict of interest

Yanzhi Bi, Kai Yuan, Yanyan Guan, Jiadong Cheng, Yajuan Zhang, Yangding Li, Dahua Yu, Wei Qin, Jie Tian declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Ethical statements

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Yanzhi Bi
    • 1
    • 2
  • Kai Yuan
    • 1
    • 2
    • 3
  • Yanyan Guan
    • 1
    • 2
  • Jiadong Cheng
    • 1
    • 2
  • Yajuan Zhang
    • 1
    • 2
  • Yangding Li
    • 1
    • 2
  • Dahua Yu
    • 3
  • Wei Qin
    • 1
    • 2
  • Jie Tian
    • 1
    • 2
    • 4
  1. 1.School of Life Science and TechnologyXidian UniversityXi’anChina
  2. 2.Engineering Research Center of Molecular and Neuro ImagingMinistry of EducationXi’anChina
  3. 3.Information Processing Laboratory, School of Information EngineeringInner Mongolia University of Science and TechnologyBaotouChina
  4. 4.Institute of AutomationChinese Academy of SciencesBeijingChina

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