Reconfigurations of Dynamic Functional Network Connectivity in Large-scale Brain Network after Prolonged Abstinence in Heroin Users


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Abstract

Background:Brain recovery phenomenon after long-term abstinence had been reported in substance use disorders. Yet, few longitudinal studies have been conducted to observe the abnormal dynamic functional connectivity (dFNC) of large-scale brain networks and recovery after prolonged abstinence in heroin users.

Objective:The current study will explore the brain network dynamic connection reconfigurations after prolonged abstinence in heroin users (HUs).

Methods:The 10-month longitudinal design was carried out for 40 HUs. The 40 healthy controls (HCs) were also enrolled. Group independent component analysis (GICA) and dFNC analysis were employed to detect the different dFNC patterns of addiction-related ICNs between HUs and HCs. The temporal properties and the graph-theoretical properties were calculated. Whether the abnormalities would be reconfigured in HUs after prolonged abstinence was then investigated.

Results:Based on eight functional networks extracted from GICA, four states were identified by the dFNC analysis. Lower mean dwell time and fraction rate in state4 were found for HUs, which were increased toward HCs after prolonged abstinence. In this state, HUs at baseline showed higher dFNC of RECN-aSN, aSN- aSN and dDMN-pSN, which decreased after protracted abstinence. A similar recovery phenomenon was found for the global efficiency and path length in abstinence HUs. Mean while, the abnormal dFNC strength was correlated with craving both at baseline and after abstinence.

Conclusion:Our longitudinal study observed the large-scale brain network reconfiguration from the dynamic perspective in HUs after prolonged abstinence and improved the understanding of the neurobiology of prolonged abstinence in HUs.

About the authors

Shan Zhang

Center for Brain Imaging, School of Life Science and Technology, Xidian University

Email: info@benthamscience.net

Wenhan Yang

Department of Radiology, Second Xiangya Hospital, Central South University

Email: info@benthamscience.net

Minpeng Li

Center for Brain Imaging, School of Life Science and Technology, Xidian University

Email: info@benthamscience.net

Xinwen Wen

Center for Brain Imaging, School of Life Science and Technology, Xidian University

Email: info@benthamscience.net

Ziqiang Shao

Center for Brain Imaging, School of Life Science and Technology, Xidian University

Email: info@benthamscience.net

Jun Li

Center for Brain Imaging, School of Life Science and Technology, Xidian Universit

Email: info@benthamscience.net

Jixin Liu

Center for Brain Imaging, School of Life Science and Technology, Xidian University

Email: info@benthamscience.net

Jun Zhang

, Hunan Judicial Police Academy

Email: info@benthamscience.net

Dahua Yu

Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology

Email: info@benthamscience.net

Jun Liu

Department of Radiology, Second Xiangya Hospital, Central South University

Author for correspondence.
Email: info@benthamscience.net

Kai Yuan

Center for Brain Imaging, School of Life Science and Technology, Xidian University

Author for correspondence.
Email: info@benthamscience.net

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