PDF(Pubmed)
Abstract：
Natural fluctuations in sustained attention can lead to attentional failures in everyday tasks and even dangerous incidences. These fluctuations depend on personal factors, as well as task characteristics. So far, our understanding of sustained attention is partly due to the common usage of laboratory setups and tasks, and the complex interplay between behavior and brain activity. The focus of the current study was thus to test the feasibility of applying a single-channel wireless EEG to monitor patterns of sustained attention during a set of ecological tasks. An EEG marker of attention (BEI-Brain Engagement Index) was continuously recorded from 42 healthy volunteers during auditory and visual tasks from the Test of Everyday Attention (TEA) and Trail Making Test (TMT). We found a descending pattern of both performance and BEI in the auditory tasks as task complexity increases, while the increase in performance and decrease in BEI on the visual task. In addition, patterns of BEI in the complex tasks were used to detect outliers and the optimal range of attention through exploratory models. The current study supports the feasibility of combined electrophysiological and neurocognitive investigation of sustained attention in ecological tasks yielding unique insights on patterns of sustained attention as a function of task modality and task complexity.
摘要：
持续注意力的自然波动会导致日常任务中的注意力失败，甚至是危险的事件。这些波动取决于个人因素，以及任务特征。到目前为止,我们对持续关注的理解部分是由于实验室设置和任务的常见用法，以及行为和大脑活动之间复杂的相互作用。因此，当前研究的重点是测试在一系列生态任务中应用单通道无线EEG监测持续注意力模式的可行性。在日常注意力测试（TEA）和跟踪测试（TMT）的听觉和视觉任务中，连续记录了42名健康志愿者的EEG注意力标记（BEI-大脑参与指数）。随着任务复杂性的增加，我们发现听觉任务中的性能和BEI的下降模式，而在视觉任务上性能的增加和BEI的减少。此外,BEI在复杂任务中的模式被用来通过探索性模型检测异常值和最佳注意范围。当前的研究支持在生态任务中对持续注意进行电生理和神经认知联合研究的可行性，从而对持续注意模式作为任务模态和任务复杂性的函数产生了独特的见解。
