Generalization of attentional control strategies across distinct tasks
Generalization of attentional control strategies across distinct tasks
复制标题
跨不同任务的注意力控制策略的概括
作者：
Walden Y. Li;Molly R. McKinney;Jessica L. Irons;Andrew B. Leber
注意控制策略是否适用于不同的视觉搜索任务？先前的研究未能观察到不同视觉搜索任务之间策略度量的显著相关性（Clarke et al., 2020），这表明策略不是单一的，或由单个特征变量决定。在这里，我们质疑策略的异质性（非单一），假设一个相似梯度帐户，该帐户认为策略确实在某种程度上泛化，特别是在具有相似注意力成分的任务中。为了验证这一说法，我们采用了自适应选择视觉搜索（ACVS; Irons & Leber, 2018a），这是一种旨在直接测量注意力控制策略的视觉搜索范式。在两项研究中，我们让参与者完成ACVS和一个修改过的，但类似的任务，其中一个改变了注意成分（具体来说，分别要求使用基于特征的注意和枚举）。我们发现，在需要和不需要基于特征的注意的任务之间（r = .38, p = .0068），以及在需要和不需要枚举的任务之间（r = .33, p = .018），策略最优性呈正相关。因此，注意控制策略确实在足够相似的任务中一般化，尽管相关性的强度弱于策略测量的任务内测试-重测信度。这些结果支持相似性梯度说。
Does attentional control strategy generalize across different visual search tasks? Previous research has failed to observe significant correlations in strategy metrics between different visual search tasks (Clarke et al., 2020), suggesting that strategy is not unitary, or determined by a single trait variable. Here we question just how heterogeneous (non-unitary) strategies are, hypothesizing a similarity gradient account, which holds that strategy does generalize to some degree, specifically across tasks with similar attentional components. To test this account, we employed the Adaptive Choice Visual Search (ACVS; Irons & Leber, 2018a), a visual search paradigm designed to directly measure attentional control strategy. In two studies, we had participants complete the ACVS and a modified, but similar, task with one altered attentional component (specifically, the requirement to use feature-based attention and enumeration, respectively). We found positive correlations in strategy optimality between tasks that do vs. do not involve feature-based attention (r = .38, p = .0068) and across tasks that do vs. do not require enumeration (r = .33, p = .018). Thus, attentional control strategies did generalize across sufficiently similar tasks, although the strength of the correlations was weaker than the within-task test-retest reliability of strategy measure. These results support the similarity gradient account.