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Ongoing EEG oscillatory dynamics suggesting evolution of mental fatigue in a color-word matching stroop task

机译:持续的EEG振荡动力学表明在颜色-单词匹配的Stroop任务中精神疲劳的演变

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Mental fatigue would develop when performing a tedious cognitive task for a long time. The present study evaluated the evolution of mental fatigue in a Stroop task using electroencephalography (EEG) with independent component analysis (ICA) method. Specifically, two aspects of mental fatigue, i.e., mental effort and mental engagement, were tracked by the ongoing oscillatory dynamics from frontal independent component (IC) related to cognitive control and posterior ICs related to attention. While behavioral data, i.e., number of errors and response times, indicated complicated patterns along the time, increasing patterns were consistently observed in the theta band activity of the frontal IC and in the alpha band activity of the posterior ICs as the time on task. These patterns are indicative of a gradual impairment of mental effort and mental engagement (or sustained attention), which can be explained by the evolution of mental fatigue. The present results demonstrate that ongoing EEG obtained from ICA is a sensitive and reliable mean to measure mental fatigue.
机译:长时间执行乏味的认知任务会导致精神疲劳。本研究使用独立成分分析(ICA)方法通过脑电图(EEG)对Stroop任务中精神疲劳的发展进行了评估。具体而言,通过与认知控制有关的额叶独立成分(IC)和与注意力有关的后方IC的持续振荡动力学,跟踪了精神疲劳的两个方面,即精神努力和精神投入。行为数据(即错误数量和响应时间)表明了随时间变化的复杂模式,随着工作时间的推移,在额叶IC的θ带活动性和后部IC的α带活动性中始终观察到增加的模式。这些模式表明精神努力和精神参与(或持续关注)逐渐受损,这可以通过精神疲劳的发展来解释。目前的结果表明,从ICA获得的正在进行的EEG是测量精神疲劳的一种敏感而可靠的方法。

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