School of Psychological Science.
Department of Psychology.
J Exp Psychol Gen. 2019 Dec;148(12):2181-2206. doi: 10.1037/xge0000599. Epub 2019 Apr 22.
Performing deferred actions in the future relies upon Prospective Memory (PM). Often, PM demands arise in complex dynamic tasks. Not only can PM be challenging in such environments, the processes required for PM may affect the performance of other tasks. To adapt to PM demands in such environments, humans may use a range of strategies, including flexible allocation of cognitive resources and cognitive control mechanisms. We sought to understand such mechanisms by using the Prospective Memory Decision Control (Strickland, Loft, Remington, & Heathcote, 2018) model to provide a comprehensive, quantitative account of dual task performance in a complex dynamic environment (a simulated air traffic control conflict detection task). We found that PM demands encouraged proactive control over ongoing task decisions, but that this control was reduced at high time pressure to facilitate fast responding. We found reactive inhibitory control over ongoing task processes when PM targets were encountered, and that time pressure and PM demand both affect the attentional system, increasing the amount of cognitive resources available. However, as demands exceeded the capacity limit of the cognitive system, resources were reallocated (shared) between the ongoing and PM tasks. As the ongoing task used more resources to compensate for additional time pressure demands, it drained resources that would have otherwise been available for PM task processing. This study provides the first detailed quantitative understanding of how attentional resources and cognitive control mechanisms support PM and ongoing task performance in complex dynamic environments. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
未来执行延迟的行动依赖于前瞻性记忆(PM)。通常,PM 需求在复杂的动态任务中出现。PM 在这种环境中不仅具有挑战性,而且 PM 所需的过程可能会影响其他任务的性能。为了适应这种环境中的 PM 需求,人类可能会使用一系列策略,包括灵活分配认知资源和认知控制机制。我们试图通过使用前瞻性记忆决策控制(Strickland、Loft、Remington 和 Heathcote,2018)模型来理解这些机制,为复杂动态环境(模拟空中交通管制冲突检测任务)中的双重任务性能提供全面、定量的解释。我们发现,PM 需求鼓励对正在进行的任务决策进行主动控制,但在高时间压力下,这种控制会减少,以促进快速响应。当遇到 PM 目标时,我们发现对正在进行的任务过程进行了反应性抑制控制,并且时间压力和 PM 需求都会影响注意力系统,增加可用的认知资源量。然而,随着需求超过认知系统的容量限制,资源在正在进行的任务和 PM 任务之间重新分配(共享)。由于正在进行的任务使用更多资源来补偿额外的时间压力需求,因此会耗尽原本可用于 PM 任务处理的资源。这项研究首次详细地理解了注意力资源和认知控制机制如何在复杂的动态环境中支持 PM 和正在进行的任务性能。(PsycINFO 数据库记录(c)2019 APA,保留所有权利)。