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Brain Imaging and Behavior

, Volume 11, Issue 3, pp 677–684 | Cite as

Neural correlates of 12-h abstinence-induced craving in young adult smokers: a resting-state study

  • Yangding Li
  • Kai YuanEmail author
  • Yanzhi Bi
  • Yanyan Guan
  • Jiadong Cheng
  • Yajuan Zhang
  • Sha Shi
  • Xiaoqi Lu
  • Dahua YuEmail author
  • Jie Tian
Original Research

Abstract

Studying the neural correlates of craving to smoke in young adulthood is of great importance to improve treatment outcomes in nicotine dependence. Previous nicotine dependence studies mainly focused on the neural substrates of craving elicited by smoking-related cues. More explicit attention to abstinence-induced craving during resting state in nicotine dependence has the potential to yield valuable information about craving, and characterizing this kind of craving is critical for developing effective interventions. Twenty-five young male smokers were enrolled in the present study. A within-subject experiment design was carried out to compare regional homogeneity (ReHo) between 12-h smoking abstinence and smoking satiety conditions during resting state in young adult smokers. Then, the ReHo changes associated with smoking abstinence (compared with satiety) were further examined for correlations with abstinence-induced changes in subjective craving. We found young adult smokers in abstinence state (compared with satiety) had higher ReHo in brain regions in fronto-striatal circuits including bilateral caudate, anterior cingulate cortex (ACC) and bilateral dorsal lateral prefrontal cortex (DLPFC), as well as brain regions in default mode network (DMN) including posterior cingulate cortex (PCC)/precuneus and angular gyrus. Additionally, we found the ReHo changes of the ACC and the bilateral caudate were positively correlated with the changes in craving induced by abstinence (i.e., abstinence minus satiety) in young adult smokers. The present findings improve the understanding of the effects of acute smoking abstinence on spontaneous brain activity and may contribute new insights into the neural mechanism of abstinence-induced craving in nicotine dependence.

Keywords

Resting state Within-subject design Regional homogeneity (ReHo) Abstinence-induced craving Young adult smokers 

Notes

Acknowledgments

This paper is supported by the National Natural Science Foundation of China under Grant nos. 81571751, 81571753, 61502376, 81401478, 81401488, 81470816, 81471737, 81301281, 81271546, 81271549, 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. 2014M552416.

Compliance with ethical standards

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.

Conflict of Interest

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

Informed consent

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

  • Yangding Li
    • 1
    • 2
  • Kai Yuan
    • 1
    • 2
    Email author
  • Yanzhi Bi
    • 1
    • 2
  • Yanyan Guan
    • 1
    • 2
  • Jiadong Cheng
    • 1
    • 2
  • Yajuan Zhang
    • 1
    • 2
  • Sha Shi
    • 1
    • 2
  • Xiaoqi Lu
    • 3
  • Dahua Yu
    • 3
    Email author
  • Jie Tian
    • 1
    • 2
    • 4
  1. 1.School of Life Science and TechnologyXidian UniversityXi’anPeople’s Republic of China
  2. 2.Engineering Research Center of Molecular and Neuro Imaging, Ministry of EducationXi’anPeople’s Republic of China
  3. 3.Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information EngineeringInner Mongolia University of Science and TechnologyBaotouPeople’s Republic of China
  4. 4.Institute of Automation, Chinese Academy of SciencesBeijingPeople’s Republic of China

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