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Sleep Deprivation and Sustained Attention Performance: Integrating Mathematical and Cognitive Modeling

机译:睡眠剥夺和持续注意力表现:整合数学和认知模型

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A long history of research has revealed many neurophysiological changes and concomitant behavioral impacts of sleep deprivation, sleep restriction, and circadian rhythms. Little research, however, has been conducted in the area of computational cognitive modeling to understand the information processing mechanisms through which neurobehavioral factors operate to produce degradations in human performance. Our approach to understanding this relationship is to link predictions of overall cognitive functioning, or alertness, from existing biomathematical models to information processing parameters in a cognitive architecture, leveraging the strengths from each to develop a more comprehensive explanation. The integration of these methodologies is used to account for changes in human performance on a sustained attention task across 88 h of total sleep deprivation. The integrated model captures changes due to time awake and circadian rhythms, and it also provides an account for underlying changes in the cognitive processes that give rise to those effects. The results show the potential for developing mechanistic accounts of how fatigue impacts cognition, and they illustrate the increased explanatory power that is possible by combining theoretical insights from multiple methodologies.
机译:悠久的研究历史揭示了许多神经生理变化以及睡眠剥夺,睡眠受限和昼夜节律的伴随行为影响。但是,在计算认知建模领域中,很少有研究来了解信息处理机制,神经行为因素通过该信息处理机制来降低人类性能。我们理解这种关系的方法是将整体的认知功能或机敏性的预测从现有的生物数学模型链接到认知体系结构中的信息处理参数,并利用各自的优势进行更全面的解释。这些方法学的整合被用来解释人类在整个88小时的睡眠剥夺持续关注任务中的表现变化。集成模型捕获了由于时间清醒和昼夜节律引起的变化,并且还为引起这些影响的认知过程中的潜在变化提供了解释。结果显示了开发有关疲劳如何影响认知的机械方法的潜力,并且它们说明了通过结合多种方法的理论见解而可能增强的解释能力。

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