Avirame Keren, Gshur Noga, Komemi Reut, Lipskaya-Velikovsky Lena
Psychiatric Division, Sourasky Medical Center, Tel Aviv-Yafo, Israel.
Independent Researcher, Tel Aviv-Yafo, Israel.
Front Hum Neurosci. 2022 Sep 29;16:971314. doi: 10.3389/fnhum.2022.971314. eCollection 2022.
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.
持续注意力的自然波动可能导致日常任务中的注意力失误，甚至引发危险事件。这些波动取决于个人因素以及任务特征。到目前为止，我们对持续注意力的理解部分源于实验室设置和任务的普遍使用，以及行为与大脑活动之间的复杂相互作用。因此，本研究的重点是测试应用单通道无线脑电图来监测一组生态任务中持续注意力模式的可行性。在来自日常注意力测试（TEA）和连线测验（TMT）的听觉和视觉任务期间，连续记录了42名健康志愿者的注意力脑电图标记（BEI-大脑参与指数）。我们发现，随着任务复杂性增加，听觉任务中的表现和BEI均呈下降模式，而视觉任务中的表现增加且BEI下降。此外，通过探索性模型，复杂任务中的BEI模式被用于检测异常值和注意力的最佳范围。本研究支持在生态任务中对持续注意力进行电生理和神经认知联合研究的可行性，从而对作为任务模式和任务复杂性函数的持续注意力模式产生独特见解。
