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动作视频游戏体验与静息态脑电图的时间和空间复杂性改变有关。

Action Video Gaming Experience Related to Altered Resting-State EEG Temporal and Spatial Complexity.

作者信息

Cui Ruifang, Jiang Jinliang, Zeng Lu, Jiang Lijun, Xia Zeling, Dong Li, Gong Diankun, Yan Guojian, Ma Weiyi, Yao Dezhong

机构信息

MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.

School of Life Sciences and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China.

出版信息

Front Hum Neurosci. 2021 Jun 29;15:640329. doi: 10.3389/fnhum.2021.640329. eCollection 2021.

Abstract

Action video gaming (AVG) places sustained cognitive load on various behavioral systems, thus offering new insights into learning-related neural plasticity. This study aims to determine whether AVG experience is associated with resting-state electroencephalogram (rs-EEG) temporal and spatial complexity, and if so, whether this effect is observable across AVG subgenres. Two AVG games - League of Legends (LOL) and Player Unknown's Battle Grounds (PUBG) that represent two major AVG subgenres - were examined. We compared rs-EEG microstate and omega complexity between LOL experts and non-experts (Experiment 1) and between PUBG experts and non-experts (Experiment 2). We found that the experts and non-experts had different rs-EEG activities in both experiments, thus revealing the adaptive effect of AVG experience on brain development. Furthermore, we also found certain subgenre-specific complexity changes, supporting the recent proposal that AVG should be categorized based on the gaming mechanics of a specific game rather than a generic genre designation.

摘要

动作视频游戏(AVG)会对各种行为系统施加持续的认知负荷,从而为与学习相关的神经可塑性提供新的见解。本研究旨在确定AVG体验是否与静息态脑电图(rs-EEG)的时间和空间复杂性相关,如果是,这种效应在不同的AVG子类型中是否都可观察到。我们研究了两款代表两种主要AVG子类型的游戏——《英雄联盟》(LOL)和《绝地求生》(PUBG)。我们比较了LOL专家和非专家之间(实验1)以及PUBG专家和非专家之间(实验2)的rs-EEG微状态和欧米伽复杂性。我们发现,在两个实验中,专家和非专家的rs-EEG活动都有所不同,从而揭示了AVG体验对大脑发育的适应性影响。此外,我们还发现了某些特定子类型的复杂性变化,支持了最近提出的观点,即AVG应根据特定游戏的游戏机制而非一般类型来分类。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a21e/8275975/e40824b8776d/fnhum-15-640329-g001.jpg

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