Bays Paul M
University of Cambridge, Department of Psychology, Downing St, Cambridge, UK.
Sci Rep. 2016 Jan 13;6:19203. doi: 10.1038/srep19203.
When observers retrieve simple visual features from working memory, two kinds of error are typically confounded in their recall. First, responses reflect noise or variability within the feature dimension they were asked to report. Second, responses are corrupted by "swap errors", in which a different item from the memory set is reported in place of the one that was probed. Independent evaluation of these error sources is vital for understanding the structure of internal representations and their binding. However, previous methods for disentangling these errors have been critically dependent on assumptions about the noise distribution, which is a priori unknown. Here I address this question with novel non-parametric (NP) methods, which estimate swap frequency and feature variability with fewer prior assumptions, and without a fitting procedure. The results suggest that swap errors are considerably more prevalent than previously appreciated (accounting for more than a third of responses at set size 8). These methods also identify which items are swapped in for targets: when the target item is cued by location, the items in closest spatial proximity are most likely to be incorrectly reported, thus implicating noise in the probe feature dimension as a source of swap errors.
当观察者从工作记忆中提取简单视觉特征时，他们的回忆中通常会混淆两种错误。首先，反应反映了他们被要求报告的特征维度内的噪声或变异性。其次，反应会被“交换错误”破坏，即报告记忆集中的另一个项目来代替被探测的项目。对这些错误来源进行独立评估对于理解内部表征的结构及其绑定至关重要。然而，以前用于区分这些错误的方法严重依赖于关于噪声分布的假设，而噪声分布是先验未知的。在这里，我用新颖的非参数（NP）方法解决这个问题，这些方法在较少的先验假设下估计交换频率和特征变异性，并且无需拟合程序。结果表明，交换错误比以前认为的要普遍得多（在集合大小为8时占反应的三分之一以上）。这些方法还能确定哪些项目被交换来代替目标：当目标项目由位置提示时，空间上最接近的项目最有可能被错误报告，从而暗示探测特征维度中的噪声是交换错误的一个来源。
