Department of Psychological and Brain Sciences.
J Exp Psychol Learn Mem Cogn. 2021 Oct;47(10):1563-1584. doi: 10.1037/xlm0001056. Epub 2021 Sep 27.
Existing approaches in the literature on cognitive control in conflict tasks almost exclusively target the outcome of control (by comparing mean congruency effects) and not the processes that shape control. These approaches are limited in addressing a current theoretical issue-what contribution does learning make to adjustments in cognitive control? In the present study, we evaluated an alternative approach by reanalyzing existing data sets using generalized linear mixed models that enabled us to examine trial-level changes in control within abbreviated lists that varied in theoretically significant ways (e.g., probability of conflict; presence vs. absence of a precue). For the first time, this allowed us to characterize (a) the trial-by-trial signature of experience-based processes that support control as a list unfolds under various conditions and (b) how explicit precues conveying the expected probability of conflict within a list influence control learning. This approach uncovered novel theoretical insights: First, slopes representing control learning varied depending on whether a cue was available or not suggesting that explicit expectations about conflict affected whether and the rate at which control learning occurred; and second, this pattern was modulated by task demands and incentives. Additionally, analyses revealed a cue-induced heightening of control in high conflict likelihood lists that mean level analyses had failed to capture. The present study showed how control is shaped by the adaptive weighting of experience and expectations on a trial-by-trial basis and demonstrated the utility of a novel method for revealing the contributions of learning to control, and modulation of learning via precues. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
现有的冲突任务认知控制文献中的方法几乎完全针对控制的结果(通过比较均值一致性效应),而不是控制的形成过程。这些方法在解决当前一个理论问题方面存在局限性,即学习对认知控制的调整有什么贡献?在本研究中,我们通过使用广义线性混合模型重新分析现有的数据集,评估了一种替代方法,这种方法使我们能够在理论上有显著差异的缩写列表中检查控制的试验水平变化(例如,冲突的可能性;存在或不存在前测)。这是第一次使我们能够描述(a)随着列表在各种条件下展开,支持控制的基于经验的过程的试验到试验特征;以及(b)在列表中明确传达冲突预期可能性的前测如何影响控制学习。这种方法揭示了新的理论见解:首先,代表控制学习的斜率因是否有提示而有所不同,这表明对冲突的明确期望影响了控制学习是否发生以及发生的速度;其次,这种模式受到任务需求和激励的调节。此外,分析还揭示了在高冲突可能性列表中,提示引起的控制增强,而平均水平分析未能捕捉到这一点。本研究表明了控制是如何通过经验和期望的自适应加权在试验到试验的基础上形成的,并展示了一种新方法的实用性,该方法揭示了学习对控制的贡献,以及通过前测对学习的调节。(PsycInfo 数据库记录(c)2022 APA,保留所有权利)。