School of Psychology, Liaoning Normal University, Da Lian, China.
Brain Behav. 2019 Mar;9(3):e01218. doi: 10.1002/brb3.1218. Epub 2019 Jan 31.
Internet addiction (IA) has been associated with widespread brain alterations. Functional connectivity (FC) and network analysis results related to IA are inconsistent between studies, and how network hubs change is not known. The aim of this study was to evaluate functional and topological networks using an unbiased minimum spanning tree (MST) analysis on electroencephalography (EEG) data in IA and healthy control (HC) college students.
In this study, Young's internet addiction test was used as an IA severity measure. EEG recordings were obtained in IA (n = 30) and HC participants (n = 30), matched for age and sex, during rest. The phase lag index (PLI) and MST were applied to analyze FC and network topology. We expected to obtain evidence of underlying alterations in functional and topological networks related to IA.
IA participants showed higher delta FC between left-side frontal and parieto-occipital areas compared to the HC group (p < 0.001), global MST measures revealed a more star-like network in IA participants in the upper alpha and beta bands, and the occipital brain region was relatively less important in the IA relative to the HC group in the lower band. The correlation results were consistent with the MST results: higher IA severity correlated with higher Max degree and kappa, and lower eccentricity and diameter.
Functional networks of the IA group were characterized by increased FC, a more random organization, and a decrease of relative functional importance of the visual processing area. Taken together, these alterations can help us understand the influence of IA to brain mechanism.
互联网成瘾（IA）与广泛的大脑改变有关。关于 IA 的功能连接（FC）和网络分析结果在研究之间不一致，并且不知道网络枢纽如何变化。本研究的目的是使用脑电图（EEG）数据的无偏最小生成树（MST）分析评估 IA 和健康对照组（HC）大学生的功能和拓扑网络。
在这项研究中，使用 Young 的互联网成瘾测试作为 IA 严重程度的衡量标准。在休息期间，从 IA（n=30）和 HC 参与者（n=30）中获取 EEG 记录，这些参与者按年龄和性别匹配。应用相位滞后指数（PLI）和 MST 来分析 FC 和网络拓扑。我们期望获得与 IA 相关的功能和拓扑网络潜在改变的证据。
IA 参与者与 HC 组相比，左侧额叶和顶枕区域之间的 delta FC 更高（p<0.001），全局 MST 测量结果显示，IA 参与者在上 alpha 和 beta 波段的网络更像星型，并且在较低波段中，IA 参与者的枕叶大脑区域相对比 HC 组的重要性较低。相关性结果与 MST 结果一致：IA 严重程度越高，Max 度和 kappa 越高，而偏心度和直径越低。
IA 组的功能网络的特征是 FC 增加、组织更随机，以及视觉处理区域的相对功能重要性降低。综上所述，这些改变可以帮助我们了解 IA 对大脑机制的影响。
