Is the Internet gaming-addicted brain close to be in a pathological state?

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• 作者：Chang-hyun Park ; Ji-Won Chun ; Huyn Cho ; Young-Chul Jung ; Jihye Choi and Dai Jin Kim
• 刊名：Addiction Biology
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：22
• 期：1
• 页码：196-205
• 全文大小：456K
• ISSN：1369-1600

文摘

Internet gaming addiction (IGA) is becoming a common and widespread mental health concern. Although IGA induces a variety of negative psychosocial consequences, it is yet ambiguous whether the brain addicted to Internet gaming is considered to be in a pathological state. We investigated IGA-induced abnormalities of the brain specifically from the network perspective and qualitatively assessed whether the Internet gaming-addicted brain is in a state similar to the pathological brain. Topological properties of brain functional networks were examined by applying a graph-theoretical approach to analyzing functional magnetic resonance imaging data acquired during a resting state in 19 IGA adolescents and 20 age-matched healthy controls. We compared functional distance-based measures, global and local efficiency of resting state brain functional networks between the two groups to assess how the IGA subjects' brain was topologically altered from the controls' brain. The IGA subjects had severer impulsiveness and their brain functional networks showed higher global efficiency and lower local efficiency relative to the controls. These topological differences suggest that IGA induced brain functional networks to shift toward the random topological architecture, as exhibited in other pathological states. Furthermore, for the IGA subjects, the topological alterations were specifically attributable to interregional connections incident on the frontal region, and the degree of impulsiveness was associated with the topological alterations over the frontolimbic connections. The current findings lend support to the proposition that the Internet gaming-addicted brain could be in the state similar to pathological states in terms of topological characteristics of brain functional networks.