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Ongoing EEG Oscillatory Dynamics Suggesting Evolution of Mental Fatigue in a Color-word Matching Stroop Task

机译:持续的脑电图振荡动力学表明颜色词匹配的心理疲劳演变

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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:在很长一段时间内执行繁琐的认知任务时,精神疲劳会发生。本研究评估了使用脑电图(EEG)与独立分量分析(ICA)方法的螺旋术(EEG)中精神疲劳的演变。具体而言,通过与关注相关的认知控制和后部IC相关的正面独立组分(IC)的正在进行的振荡动态跟踪了精神疲劳,即心理努力和心理参与的两个方面。虽然行为数据,即误差和响应时间,沿着时间表示复杂的模式,但在正面IC的THETA频段活动中始终如一地观察到越来越多的模式,以及作为任务的时间的后部IC的α带活动。这些模式表明精神努力和心理参与(或持续注意)的逐步减值,这可以通过精神疲劳的演变来解释。本结果表明,从ICA获得的持续脑电图是衡量精神疲劳的敏感和可靠的平均值。

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