Department of Psychology, Arizona State University, Tempe, AZ 85287-1104, USA.
J Exp Psychol Hum Percept Perform. 2012 Feb;38(1):90-112. doi: 10.1037/a0023894. Epub 2011 May 16.
When observers search for a target object, they incidentally learn the identities and locations of "background" objects in the same display. This learning can facilitate search performance, eliciting faster reaction times for repeated displays. Despite these findings, visual search has been successfully modeled using architectures that maintain no history of attentional deployments; they are amnesic (e.g., Guided Search Theory). In the current study, we asked two questions: 1) under what conditions does such incidental learning occur? And 2) what does viewing behavior reveal about the efficiency of attentional deployments over time? In two experiments, we tracked eye movements during repeated visual search, and we tested incidental memory for repeated nontarget objects. Across conditions, the consistency of search sets and spatial layouts were manipulated to assess their respective contributions to learning. Using viewing behavior, we contrasted three potential accounts for faster searching with experience. The results indicate that learning does not result in faster object identification or greater search efficiency. Instead, familiar search arrays appear to allow faster resolution of search decisions, whether targets are present or absent.
当观察者搜索目标对象时，他们会偶然学习到同一显示中的“背景”对象的身份和位置。这种学习可以促进搜索性能，使重复显示的反应时间更快。尽管有这些发现，但视觉搜索已经成功地使用不保留注意力部署历史的架构进行建模；它们是健忘的（例如，引导搜索理论）。在当前的研究中，我们提出了两个问题：1）在什么条件下会发生这种偶然学习？2） 观看行为如何揭示随时间推移注意力部署的效率？在两项实验中，我们在重复视觉搜索期间跟踪眼动，并测试了对重复非目标对象的偶然记忆。在各种条件下，我们操纵搜索集和空间布局的一致性，以评估它们各自对学习的贡献。使用观看行为，我们对比了三种潜在的解释，以说明经验如何使搜索更快。结果表明，学习不会导致对象识别更快或搜索效率更高。相反，熟悉的搜索数组似乎可以更快地做出搜索决策，无论目标是否存在。
