Industry-Academy Cooperation Team, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, South Korea.
Center for Bionics, Korea Institute of Science and Technology, 5, Hwarang-ro 14-gil Seongbuk-gu, Seoul, 02792, South Korea.
BMC Public Health. 2023 May 4;23(1):816. doi: 10.1186/s12889-023-15750-4.
Internet gaming disorder (IGD) is receiving increasing attention owing to its effects on daily living and psychological function.
In this study, electroencephalography was used to compare neural activity triggered by repeated presentation of a stimulus in healthy controls (HCs) and those with IGD. A total of 42 adult men were categorized into two groups (IGD, n = 21) based on Y-IAT-K scores. Participants were required to watch repeated presentations of video games while wearing a head-mounted display, and the delta (D), theta (T), alpha (A), beta (B), and gamma (G) activities in the prefrontal (PF), central (C), and parieto-occipital (PO) regions were analyzed.
The IGD group exhibited higher absolute powers of D, D, T, T, B, and B than HCs. Among the IGD classification models, a neural network achieves the highest average accuracy of 93% (5-fold cross validation) and 84% (test).
These findings may significantly contribute to a more comprehensive understanding of the neurological features associated with IGD and provide potential neurological markers that can be used to distinguish between individuals with IGD and HCs.
由于互联网游戏障碍 (IGD) 对日常生活和心理功能的影响,它越来越受到关注。
在这项研究中,我们使用脑电图比较了健康对照组 (HCs) 和 IGD 患者对刺激重复呈现的神经活动。根据 Y-IAT-K 评分,将 42 名成年男性分为两组(IGD,n=21)。参与者被要求佩戴头戴式显示器观看重复呈现的视频游戏,分析前额 (PF)、中央 (C) 和顶枕 (PO) 区域的 delta (D)、theta (T)、alpha (A)、beta (B) 和 gamma (G) 活动。
IGD 组的 D、D、T、T、B 和 B 的绝对功率均高于 HCs。在 IGD 分类模型中,神经网络的平均准确率最高,为 93%(5 倍交叉验证)和 84%(测试)。
这些发现可能对更全面地了解与 IGD 相关的神经特征有重要贡献,并提供潜在的神经标志物,可用于区分 IGD 患者和 HCs。