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Visual statistical learning can drive object-based attentional selection

机译:视觉统计学习可以推动基于对象的注意力选择

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摘要

Recent work on statistical learning has demonstrated that environmental regularities can influence aspects of perception, such as familiarity judgments. Here, we ask if statistical co-occurrences accumulated from visual statistical learning could form objects that serve as the units of attention (i.e., object-based attention). Experiment 1 demonstrated that, after observers first viewed pairs of shapes that co-occurred in particular spatial relationships, they were able to recognize the co-occurring pairs, and were faster to discriminate two targets when they appeared within a learned pair ("object") than when the targets appeared between learned pairs, demonstrating an equivalent of an object-based attention effect. Experiment 2 replicated the results of Experiment 1 using a different set of shape pairs, and revealed a negative association between the attention effect and familiarity judgments of the co-occurred pairs. Experiment 3 reports three control experiments that validated the task procedure and ruled out alternative accounts.
机译:有关统计学习的最新工作表明,环境规律性可以影响感知的各个方面,例如熟悉程度的判断。在这里,我们询问从视觉统计学习中累积的统计共现是否可以形成用作关注单元(即基于对象的关注)的对象。实验1表明,在观察者首先查看以特定空间关系共存的形状对之后,他们能够识别并存的对,并且在它们出现在学习对中时能更快地区分两个目标(“对象” ),而不是当目标出现在已学习的配对之间时,表明等效的基于对象的注意力效应。实验2使用一组不同的形状对复制了实验1的结果,并揭示了注意力和共同出现的对的熟悉程度判断之间的负相关。实验3报告了三个控制实验,这些实验验证了任务过程并排除了其他帐户。

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