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脑电图变异性:任务驱动还是受试者驱动的感兴趣信号?

EEG variability: Task-driven or subject-driven signal of interest?

作者信息

Gibson Erin, Lobaugh Nancy J, Joordens Steve, McIntosh Anthony R

机构信息

Rotman Research Institute, Baycrest Centre, 3560 Bathurst St, Toronto, ON M6A 2E1, Canada.

Brain Health Imaging Centre, Centre for Addiction and Mental Health, Canada; Department of Medicine, Division of Neurology, Temerty Faculty of Medicine, University of Toronto, Canada.

出版信息

Neuroimage. 2022 May 15;252:119034. doi: 10.1016/j.neuroimage.2022.119034. Epub 2022 Mar 1.

Abstract

Neurons in the brain are seldom perfectly quiet. They continually receive input and generate output, resulting in highly variable patterns of ongoing activity. Yet the functional significance of this variability is not well understood. If brain signal variability is functionally relevant and serves as an important indicator of cognitive function, then it should be highly sensitive to the precise manner in which a cognitive system is engaged and/or relate strongly to differences in behavioral performance. To test this, we examined EEG activity in younger adults as they performed a cognitive skill learning task and during rest. Several measures of EEG variability and signal strength were calculated in overlapping time windows that spanned the trial interval. We performed a systematic examination of the factors that most strongly influenced the variability and strength of EEG activity. First, we examined the relative sensitivity of each measure to across-subject variation (within blocks) and across-block variation (within subjects). We found that the across-subject variation in EEG variability and signal strength was much stronger than the across-block variation. Second, we examined the sensitivity of each measure to different sources of across-block variation during skill acquisition. We found that key task-driven changes in EEG activity were best reflected in changes in the strength, rather than the variability, of EEG activity. Lastly, we examined across-subject variation in each measure and its relationship with behavior. We found that individual differences in response time measures were best reflected in individual differences in the variability, rather than the strength, of EEG activity. Importantly, we found that individual differences in EEG variability related strongly to stable indicators of subject identity rather than dynamic indicators of subject performance. We therefore suggest that EEG variability may provide a more sensitive subject-driven measure of individual differences than task-driven signal of interest.

摘要

大脑中的神经元很少完全处于静息状态。它们不断接收输入并产生输出,从而导致持续活动的模式高度可变。然而,这种变异性的功能意义尚未得到很好的理解。如果脑信号变异性在功能上具有相关性并作为认知功能的重要指标,那么它应该对认知系统参与的精确方式高度敏感,并且/或者与行为表现的差异密切相关。为了验证这一点,我们在年轻成年人执行认知技能学习任务和休息期间检查了他们的脑电图(EEG)活动。在跨越试验间隔的重叠时间窗口中计算了几种脑电图变异性和信号强度的测量值。我们对最强烈影响脑电图活动变异性和强度的因素进行了系统研究。首先,我们检查了每种测量对受试者间变异(在组内)和组间变异(在受试者内)的相对敏感性。我们发现,脑电图变异性和信号强度的受试者间变异比组间变异要强得多。其次,我们检查了每种测量对技能习得期间组间变异不同来源的敏感性。我们发现,脑电图活动中关键的任务驱动变化最好反映在脑电图活动强度的变化上,而不是变异性上。最后,我们检查了每种测量的受试者间变异及其与行为的关系。我们发现,反应时间测量中的个体差异最好反映在脑电图活动变异性而非强度的个体差异上。重要的是,我们发现脑电图变异性的个体差异与受试者身份的稳定指标密切相关,而不是与受试者表现的动态指标相关。因此,我们认为脑电图变异性可能提供一种比感兴趣的任务驱动信号更敏感的受试者驱动的个体差异测量方法。

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