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Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency

机译:基于网络的分析揭示了与互联网成瘾趋势有关的功能连接

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摘要

Preoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills). Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction.
机译:过度专注和强迫使用互联网会产生负面的心理影响,因此人们越来越多地将其视为精神障碍。本研究采用基于网络的统计数据,以探讨通过自评问卷对处于静止状态的全脑功能连接与个人网络成瘾程度之间的关系。我们确定了两个具有拓扑意义的网络,一个网络与网络成瘾趋势呈正相关,另一个网络与网络成瘾趋势呈负相关。这两个网络主要在额叶区域互连,这可能反映了额叶区域对于认知控制的不同方面(即,对互联网使用和游戏技能的控制)的变化。接下来,我们将大脑分为几个大的区域子组,并发现两个网络中大多数的连接比例对应于包含四回路模型的小脑成瘾模型。最后,我们观察到与网络成瘾倾向相关的区域间联系最多的大脑区域可以复制成瘾文献中经常看到的区域,并且通过我们对网络成瘾研究的荟萃分析得到证实。这项研究可以更好地理解与网络成瘾趋势有关的大型网络,并表明临床前网络成瘾水平与成瘾的临床案例与相似的地区和联系有关。

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