J Psychiatry Neurosci 2018;43(1):48-57
Qiang Li, PhD, MD*; Jierong Liu, PhD*; Wei Wang, MD*; Yarong Wang, PhD, MD; Wei Li, PhD, MD; Jiajie Chen, MD; Jia Zhu, MD; Xuejiao Yan, MD; Yongbin Li, MD; Zhe Li, PhD, MD; Jianjun Ye, MD; Wei Wang, PhD, MD
Background: It is unknown whether impaired coupling among 3 core large-scale brain networks (salience [SN], default mode [DMN] and executive control networks [ECN]) is associated with relapse behaviour in treated heroin-dependent patients.
Methods: We conducted a prospective resting-state functional MRI study comparing the functional connectivity strength among healthy controls and heroin-dependent men who had either relapsed or were in early remission. Men were considered to be either relapsed or in early remission based on urine drug screens during a 3-month follow-up period. We also examined how the coupling of large-scale networks correlated with relapse behaviour among heroin-dependent men.
Results: We included 20 controls and 50 heroin-dependent men (26 relapsed and 24 early remission) in our analyses. The relapsed men showed greater connectivity than the early remission and control groups between the dorsal anterior cingulate cortex (key node of the SN) and the dorsomedial prefrontal cortex (included in the DMN). The relapsed men and controls showed lower connectivity than the early remission group between the left dorsolateral prefrontal cortex (key node of the left ECN) and the dorsomedial prefrontal cortex. The percentage of positive urine drug screens positively correlated with the coupling between the dorsal anterior cingulate cortex and dorsomedial prefrontal cortex, but negatively correlated with the coupling between the left dorsolateral prefrontal cortex and dorsomedial prefrontal cortex.
Limitations: We examined deficits in only 3 core networks leading to relapse behaviour. Other networks may also contribute to relapse.
Conclusion: Greater coupling between the SN and DMN and lower coupling between the left ECN and DMN is associated with relapse behaviour. These findings may shed light on the development of new treatments for heroin addiction.
Submitted Jan. 12, 2017; Revised May. 9, 2017; Revised June 20, 2017; Accepted June 22, 2017; Online first Sept. 26, 2017
*These authors contributed equally to this work.
Affiliations: From the Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China (Li, Liu, Wang, Li, Chen, Zhu, Yan, Li, Li, Ye, Wang); the Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD (Li); and the the First Affiliated Hospital of Chinese PLA General Hospital, Beijing, China (Wang).
Acknowledgements: This work was supported by grants from the National Natural Science Foundation of China (No. 81671661, 81201081, 81371532 and 81401393) and the Technology Innovation Development Foundation of Tangdu Hospital (No. 2013LCYJ003). The funders had no role in the design and conduct of the study; data collection, analysis, or interpretation of the data; preparation and approval of the manuscript; or the decision to submit the manuscript for publication. The authors thank Mrs. Yan Meng (Department of culture and media, Shaanxi Youth Vocational College) for editing the figures and Mr. Liyan Zhao (National Institute on Drug Dependence, Peking University) and Mr. Yonggui Yuan (Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Southeast University) for improvement of this study.
Competing interests: None declared.
Contributors: Q. Li and W. Wang designed the study. J. Liu, Y. Wang, W. Li, J. Chen, J. Zhu, X. Yan, Y. Li, Z. Li and J. Ye acquired the data, which Q. Li and J. Liu analyzed. Q. Li, J. Liu and W. Wang wrote the article, which all authors reviewed and approved. All authors approved the final version to be published and can certify that no other individuals not listed as authors have made substantial contributions to the paper.
Correspondence to: Q. Li and W. Wang, Department of Radiology, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, BaQiao District, Xi’an, Shaanxi 710038, China; email@example.com; firstname.lastname@example.org