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首页> 外文期刊>Journal of Experimental Psychology. General >Cognitive Control and Capacity for Prospective Memory in Complex Dynamic Environments
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Cognitive Control and Capacity for Prospective Memory in Complex Dynamic Environments

机译:复杂动态环境中潜在记忆的认知控制和能力

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摘要

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.
机译:在未来执行延期行动依赖预期记忆(PM)。通常,PM要求在复杂的动态任务中出现。在此类环境中,PM不仅可以具有挑战性,PM所需的过程可能会影响其他任务的性能。为了适应在这种环境中的下午需求,人类可以使用一系列策略,包括灵活地配置认知资源和认知控制机制。我们试图通过使用潜在的记忆决策控制(Strickland,Loft,Remington,&Heathcote,2018)模型来了解这些机制,以在复杂的动态环境中提供全面的定量定量令双重任务性能(模拟空中交通管制冲突检测任务)。我们发现PM要求鼓励积极控制在持续的任务决策上,但这种控制在高时间压力下减少,以便于快速响应。当遇到PM目标时,我们发现反应性抑制对正在进行的任务过程中的控制,并且时间压力和PM对注意力系统影响,增加可用的认知资源量。但是,随着需求超过认知系统的容量限制,资源在正在进行的和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,它会排出任何可用于PM任务处理的资源。本研究提供了首次详细的定量理解注意力资源和认知控制机制如何支持PM和在复杂的动态环境中的持续任务性能。

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