Our interactions with the visual world are guided by attention and visual working memory. Things that we look for and those we ignore are stored as templates that reflect our goals and the tasks at hand. The nature of such templates has been widely debated. A recent proposal is that these templates can be thought of as probabilistic representations of task-relevant features. Crucially, such probabilistic templates should accurately reflect feature probabilities in the environment. Here we ask whether observers can quickly form a correct internal model of a complex (bimodal) distribution of distractor features. We assessed observers' representations by measuring the slowing of visual search when target features unexpectedly match a distractor template. Distractor stimuli were heterogeneous, randomly drawn on each trial from a bimodal probability distribution. Using two targets on each trial, we tested whether observers encode the full distribution, only one peak of it, or the average of the two peaks. Search was slower when the two targets corresponded to the two modes of a previous distractor distribution than when one target was at one of the modes and another between them or outside the distribution range. Furthermore, targets on the modes were reported later than targets between the modes that, in turn, were reported later than targets outside this range. This shows that observers use a correct internal model, representing both distribution modes using templates based on the full probability distribution rather than just one peak or simple summary statistics. The findings further confirm that performance in odd-one out search with repeated distractors cannot be described by a simple decision rule. Our findings indicate that probabilistic visual working memory templates guiding attention, dynamically adapt to task requirements, accurately reflecting the probabilistic nature of the input.

中文翻译：

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视觉工作记忆中的概率拒绝模板。

我们与视觉世界的互动以注意力和视觉工作记忆为指导。我们寻找和忽略的事物都存储为模板，以反映我们的目标和手头的任务。这种模板的性质已被广泛争论。最近的提议是可以将这些模板视为任务相关功能的概率表示。至关重要的是，此类概率模板应准确反映环境中的特征概率。在这里，我们问观察者是否可以迅速形成干扰物特征的复杂（双峰）分布的正确内部模型。当目标特征意外匹配干扰项模板时，我们通过测量视觉搜索的速度来评估观察者的表示。干扰物刺激是异质的，从双峰概率分布的每个试验中随机抽取。在每个试验中使用两个目标，我们测试了观察者是对完整分布进行编码，还是对其中一个峰进行编码，还是对两个峰的平均值进行编码。当两个目标对应于先前的干扰因素分布的两种模式时，搜索速度要慢于一个目标处于其中一个模式，而另一个目标位于两个模式之间或分布范围之外时。此外，模式下的目标要晚于模式之间的目标，而模式之间的目标要晚于此范围之外的目标。这表明观察者使用正确的内部模型，使用基于完全概率分布的模板而不是仅仅一个峰值或简单的摘要统计量来代表两种分布模式。这些发现进一步证实，用简单的决策规则无法描述具有重复干扰物的单向搜索的性能。我们的发现表明，概率视觉工作记忆模板可以引导注意力，动态地适应任务要求，准确反映输入的概率性质。