There Is no Theory-Free Measure of "Swaps" in Visual Working Memory Experiments.

Jamal R Williams, Maria M Robinson, Timothy F Brady
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引用次数: 5

Abstract

Visual working memory is highly limited, and its capacity is tied to many indices of cognitive function. For this reason, there is much interest in understanding its architecture and the sources of its limited capacity. As part of this research effort, researchers often attempt to decompose visual working memory errors into different kinds of errors, with different origins. One of the most common kinds of memory error is referred to as a "swap," where people report a value that closely resembles an item that was not probed (e.g., an incorrect, non-target item). This is typically assumed to reflect confusions, like location binding errors, which result in the wrong item being reported. Capturing swap rates reliably and validly is of great importance because it permits researchers to accurately decompose different sources of memory errors and elucidate the processes that give rise to them. Here, we ask whether different visual working memory models yield robust and consistent estimates of swap rates. This is a major gap in the literature because in both empirical and modeling work, researchers measure swaps without motivating their choice of swap model. Therefore, we use extensive parameter recovery simulations with three mainstream swap models to demonstrate how the choice of measurement model can result in very large differences in estimated swap rates. We find that these choices can have major implications for how swap rates are estimated to change across conditions. In particular, each of the three models we consider can lead to differential quantitative and qualitative interpretations of the data. Our work serves as a cautionary note to researchers as well as a guide for model-based measurement of visual working memory processes.

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在视觉工作记忆实验中,没有“交换”的无理论测量。
视觉工作记忆是高度有限的,它的容量与认知功能的许多指标有关。由于这个原因,人们非常有兴趣了解它的体系结构及其有限容量的来源。作为这项研究的一部分,研究人员经常试图将视觉工作记忆错误分解为不同类型的错误,这些错误具有不同的来源。最常见的一种内存错误被称为“交换”,在这种情况下,人们报告的值与未探测的项非常相似(例如,不正确的非目标项)。这通常被认为反映了混淆,比如位置绑定错误,这会导致错误的项目被报告。可靠而有效地捕获交换率非常重要,因为它使研究人员能够准确地分解内存错误的不同来源,并阐明产生这些错误的过程。在这里,我们问不同的视觉工作记忆模型是否产生稳健和一致的交换率估计。这是文献中的一个主要空白,因为在实证和建模工作中,研究人员在测量交换时没有激励他们选择交换模型。因此,我们使用三种主流交换模型的广泛参数恢复模拟来证明测量模型的选择如何导致估计的交换率的巨大差异。我们发现,这些选择可能会对如何估计掉期利率在不同条件下的变化产生重大影响。特别是,我们考虑的三种模型中的每一种都可能导致对数据的不同定量和定性解释。我们的研究为研究人员提供了一个警示,也为基于模型的视觉工作记忆过程测量提供了指导。
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