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Sci Rep. 2018 Feb 1;8(1):2155. doi: 10.1038/s41598-018-19904-y.

Internet Communication Disorder and the structure of the human brain: initial insights on WeChat addiction.

Author information

1
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China. christian.montag@uni-ulm.de.
2
Institute of Psychology and Education, Ulm University, Ulm, Germany. christian.montag@uni-ulm.de.
3
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
4
Institute of Psychology and Education, Ulm University, Ulm, Germany.
5
Chengdu Mental Health Center, Chengdu, 610031, China.
6
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China. ben_becker@gmx.de.

Abstract

WeChat represents one of the most popular smartphone-based applications for communication. Although the application provides several useful features that simplify daily life, a growing number of users spend excessive amounts of time on the application. This may lead to interferences with everyday life and even to addictive patterns of use. In the context of the ongoing discussion on Internet Communication Disorder (ICD), the present study aimed to better characterize the addictive potential of communication applications, using WeChat as an example, by examining associations between individual variations in tendencies towards WeChat addiction and brain structural variations in fronto-striatal-limbic brain regions. To this end levels of addictive tendencies, frequency of use and structural MRI data were assessed in n = 61 healthy participants. Higher tendencies towards WeChat addiction were associated with smaller gray matter volumes of the subgenual anterior cingulate cortex, a key region for monitoring and regulatory control in neural networks underlying addictive behaviors. Moreover, a higher frequency of the paying function was associated with smaller nucleus accumbens volumes. Findings were robust after controlling for levels of anxiety and depression. The present results are in line with previous findings in substance and behavioral addictions, and suggest a similar neurobiological basis in ICD.

PMID:
29391461
PMCID:
PMC5794793
DOI:
10.1038/s41598-018-19904-y
[Indexed for MEDLINE]
Free PMC Article

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