Abstract:
Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural mechanisms of sustained attention with computational models to facilitate research and application. Although many studies have assessed attention, the evaluation of humans\' sustained attention is not sufficiently comprehensive. Hence, this study provides a current review on both neural mechanisms and computational models of visual sustained attention. We first review models, measurements, and neural mechanisms of sustained attention and propose plausible neural pathways for visual sustained attention. Next, we analyze and compare the different computational models of sustained attention that the previous reviews have not systematically summarized. We then provide computational models for automatically detecting vigilance states and evaluation of sustained attention. Finally, we outline possible future trends in the research field of sustained attention.
摘要:
持续关注是人类保持专注于相关信息而忽略不相关信息的基本能力之一。该综述的目的是提供有关如何将持续注意力的神经机制与计算模型相结合以促进研究和应用的见解。尽管许多研究评估了注意力,对人类持续注意力的评估不够全面。因此,本研究对视觉持续注意的神经机制和计算模型进行了综述.我们首先回顾模型,测量,和持续注意的神经机制,并提出了视觉持续注意的合理神经通路。接下来,我们分析和比较了以前的综述没有系统地总结的不同的持续关注计算模型.然后,我们提供了用于自动检测警觉状态和评估持续注意力的计算模型。最后,我们概述了持续关注研究领域未来可能的趋势。