Cognitive control has been theorized operating through two distinct mechanisms, proactive and reactive control, as posited by the dual mechanism of control model. Despite its potential to explain cognitive control variability, the supporting evidence for this model remains inconclusive. Prior studies frequently employed the Stroop task to assess this model, manipulating the proportion congruency (PC) at the list-wide and/or item-specific levels to target proactive and reactive control, respectively. However, these manipulations have been questioned as they may invoke low-level associative learning instead of control-driven mechanisms. Although solutions have been proposed to address these concerns, they still have limitations and impracticalities. In pursuit of a clearer understanding of this issue, we manipulated proactive and reactive control simultaneously to more directly investigate their separability. We conducted two experiments using a peripheral and a perifoveal spatial Stroop task version, respectively, and we adopted state-of-the-art methodologies, leveraging trial-level multilevel modeling analytical approaches, to effectively estimate the Stroop effect and its control-related modulations while controlling for confounding factors. Notably, we manipulated both list-wide and item-specific PCs at the trial level, allowing for a fine-grained analysis. Our results provide compelling evidence for the existence of a list-wide, PC-dependent proactive control mechanism, influencing Stroop performance independently of reactive control and confounding factors. Additionally, an item-specific PC-dependent reactive control effect was found to influence Stroop performance only in interaction with proactive control. These findings contribute to a better understanding of the interplay between proactive and reactive control mechanisms, shedding light on the intricate nature of cognitive control. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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控制探戈：主动控制和被动控制之间的相互作用。


正如控制模型的双重机制所假设的，认知控制已被理论化，通过两种不同的机制（主动控制和反应控制）进行操作。尽管它有可能解释认知控制变异性，但该模型的支持证据仍然没有定论。先前的研究经常使用 Stroop 任务来评估该模型，在列表范围和/或特定项目级别上操纵比例一致性 (PC)，分别以主动和被动控制为目标。然而，这些操作受到质疑，因为它们可能会调用低级联想学习而不是控制驱动机制。尽管已经提出了解决这些问题的解决方案，但它们仍然具有局限性和不切实际。为了更清楚地理解这个问题，我们同时操纵主动和被动控制，以更直接地研究它们的可分离性。我们分别使用外围和中心凹周围空间 Stroop 任务版本进行了两项实验，并采用最先进的方法，利用试验级多级建模分析方法，有效估计 Stroop 效应及其控制相关的调制同时控制混杂因素。值得注意的是，我们在试验级别操作了列表范围的 PC 和特定项目的 PC，从而可以进行细粒度的分析。我们的结果提供了令人信服的证据，证明存在列表范围内的、依赖于 PC 的主动控制机制，该机制独立于反应控制和混杂因素影响 Stroop 性能。此外，发现特定于 PC 的反应控制效应仅在与主动控制相互作用时才会影响 Stroop 性能。 这些发现有助于更好地理解主动和反应控制机制之间的相互作用，揭示认知控制的复杂本质。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。