Deficient dynamics of prefrontal-striatal and striatal-default mode network (DMN) neural circuits in internet gaming disorder
Copyright © 2022 Elsevier B.V. All rights reserved..
BACKGROUND: Studies have proven that individuals with internet gaming disorder (IGD) show impaired cognitive control over game craving; however, the neural mechanism underlying this process remains unclear. Accordingly, the present study aimed to investigate the dynamic features of brain functional networks of individuals with IGD during rest, which have barely been understood until now.
METHODS: Resting-state fMRI data were collected from 333 subjects (123 subjects with IGD (males/females: 73/50) and 210 healthy controls (males/females: 135/75)). First, the data-driven methodology, named co-activation pattern analysis, was applied to investigate the dynamic features of nucleus accumbens (the core region involved in craving/reward processing and addiction)-centered brain networks in IGD. Further, machine learning analysis was conducted to investigate the prediction effect of the dynamic features on participants' addiction severity.
RESULTS: Compared to controls, subjects in the IGD group showed decreased resilience, betweenness centrality and occurrence in the prefrontal-striatal neural circuit, and decreased in-degree in the striatal-default mode network (DMN) circuit. Moreover, these decreased dynamic features could significantly predict participants' addiction severity.
LIMITATIONS: The causal relationship between IGD and the abnormal dynamic features cannot be identified in this study. All the subjects were university students.
CONCLUSIONS: The present results revealed the underlying brain networks of uncontrollable craving and game-seeking behaviors in individuals with IGD during rest. The decreased dynamics of the prefrontal-striatal and striatal-DMN neural circuits might be potential biomarkers for predicting the addiction severity of IGD and potential targets for effective interventions to reduce game craving of this disorder.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:323 |
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| Enthalten in: |
Journal of affective disorders - 323(2023) vom: 15. Feb., Seite 336-344 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wang, Lingxiao [VerfasserIn] |
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| Links: |
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| Themen: |
Co-activation pattern |
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| Anmerkungen: |
Date Completed 12.01.2023 Date Revised 17.03.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jad.2022.11.074 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM349483043 |
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| 100 | 1 | |a Wang, Lingxiao |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Deficient dynamics of prefrontal-striatal and striatal-default mode network (DMN) neural circuits in internet gaming disorder |
| 264 | 1 | |c 2023 | |
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| 500 | |a Date Completed 12.01.2023 | ||
| 500 | |a Date Revised 17.03.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2022 Elsevier B.V. All rights reserved. | ||
| 520 | |a BACKGROUND: Studies have proven that individuals with internet gaming disorder (IGD) show impaired cognitive control over game craving; however, the neural mechanism underlying this process remains unclear. Accordingly, the present study aimed to investigate the dynamic features of brain functional networks of individuals with IGD during rest, which have barely been understood until now | ||
| 520 | |a METHODS: Resting-state fMRI data were collected from 333 subjects (123 subjects with IGD (males/females: 73/50) and 210 healthy controls (males/females: 135/75)). First, the data-driven methodology, named co-activation pattern analysis, was applied to investigate the dynamic features of nucleus accumbens (the core region involved in craving/reward processing and addiction)-centered brain networks in IGD. Further, machine learning analysis was conducted to investigate the prediction effect of the dynamic features on participants' addiction severity | ||
| 520 | |a RESULTS: Compared to controls, subjects in the IGD group showed decreased resilience, betweenness centrality and occurrence in the prefrontal-striatal neural circuit, and decreased in-degree in the striatal-default mode network (DMN) circuit. Moreover, these decreased dynamic features could significantly predict participants' addiction severity | ||
| 520 | |a LIMITATIONS: The causal relationship between IGD and the abnormal dynamic features cannot be identified in this study. All the subjects were university students | ||
| 520 | |a CONCLUSIONS: The present results revealed the underlying brain networks of uncontrollable craving and game-seeking behaviors in individuals with IGD during rest. The decreased dynamics of the prefrontal-striatal and striatal-DMN neural circuits might be potential biomarkers for predicting the addiction severity of IGD and potential targets for effective interventions to reduce game craving of this disorder | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Co-activation pattern | |
| 650 | 4 | |a Internet gaming disorder | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Prefrontal-striatal network | |
| 650 | 4 | |a Striatal-default mode network | |
| 700 | 1 | |a Zhang, Zhengjie |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Shizhen |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Min |e verfasserin |4 aut | |
| 700 | 1 | |a Dong, Haohao |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Shuaiyu |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Xiaoxia |e verfasserin |4 aut | |
| 700 | 1 | |a Dong, Guang-Heng |e verfasserin |4 aut | |
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