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      Decreased effective connection from the parahippocampal gyrus to the prefrontal cortex in Internet gaming disorder: A MVPA and spDCM study

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          Understanding the neural mechanisms underlying Internet gaming disorder (IGD) is essential for the condition's diagnosis and treatment. Nevertheless, the pathological mechanisms of IGD remain elusive at present. Hence, we employed multi-voxel pattern analysis (MVPA) and spectral dynamic causal modeling (spDCM) to explore this issue.


          Resting-state fMRI data were collected from 103 IGD subjects (male = 57) and 99 well-matched recreational game users (RGUs, male = 51). Regional homogeneity was calculated as the feature for MVPA based on the support vector machine (SVM) with leave-one- out cross-validation. Mean time series data extracted from the brain regions in accordance with the MVPA results were used for further spDCM analysis.


          Results display a high accuracy of 82.67% (sensitivity of 83.50% and specificity of 81.82%) in the classification of the two groups. The most discriminative brain regions that contributed to the classification were the bilateral parahippocampal gyrus (PG), right anterior cingulate cortex (ACC), and middle frontal gyrus (MFG). Significant correlations were found between addiction severity (IAT and DSM scores) and the ReHo values of the brain regions that contributed to the classification. Moreover, the results of spDCM showed that compared with RGU, IGD showed decreased effective connectivity from the left PG to the right MFG and from the right PG to the ACC and decreased self-connection in the right PG.


          These results show that the weakening of the PG and its connection with the prefrontal cortex, including the ACC and MFG, may be an underlying mechanism of IGD.

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          Author and article information

          Journal of Behavioral Addictions
          J Behav Addict
          Akadémiai Kiadó (Budapest )
          07 April 2020
          : 1-11
          [1 ] State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research , univBeijing Normal University , Beijing, PR China
          [2 ] Center for Cognition and Brain Disorders , univThe Affiliated Hospital of Hangzhou Normal University , Hangzhou, Zhejiang Province, PR China
          [3 ] deptDepartment of Psychology , univZhejiang Normal University , Jinhua, PR China
          [4 ] deptDepartment of Physics , Shanghai Key Laboratory of Magnetic Resonance , univEast China Normal University , Shanghai, PR China
          [5 ] Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments , Hangzhou, Zhejiang Province, PR China
          Author notes
          []Corresponding author. Tel./fax: +86 10 58800728. E-mail: zhangjintao@
          [∗∗ ]Corresponding author. Center for Cognition and Brain Disorders , univHangzhou Normal University , Hangzhou, Zhejiang Province, P.R. China. Tel.: +86 15 867949909. E-mail: dongguangheng@
          © 2020 The Author(s)

          This is an open-access article distributed under the terms of the Creative Commons Attribution‐NonCommercial 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.

          Page count
          Figures: 03, Tables: 05, Equations: 00, References: 70, Pages: 11
          Self URI (journal page):
          Funded by: National Natural Science Foundation
          Award ID: 31371023 and 31871122
          Funded by: Zhejiang Natural Science Foundation
          Award ID: LY20C090005
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