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空间预测性情境通过偏向局部注意力竞争加速视觉搜索。

Spatial Predictive Context Speeds Up Visual Search by Biasing Local Attentional Competition.

作者信息

Bouwkamp Floortje G, de Lange Floris P, Spaak Eelke

机构信息

Radboud University.

出版信息

J Cogn Neurosci. 2025 Jan 2;37(1):28-42. doi: 10.1162/jocn_a_02254.

Abstract

The human visual system is equipped to rapidly and implicitly learn and exploit the statistical regularities in our environment. Within visual search, contextual cueing demonstrates how implicit knowledge of scenes can improve search performance. This is commonly interpreted as spatial context in the scenes becoming predictive of the target location, which leads to a more efficient guidance of attention during search. However, what drives this enhanced guidance is unknown. First, it is under debate whether the entire scene (global context) or more local context drives this phenomenon. Second, it is unclear how exactly improved attentional guidance is enabled by target enhancement and distractor suppression. In the present magnetoencephalography experiment, we leveraged rapid invisible frequency tagging to answer these two outstanding questions. We found that the improved performance when searching implicitly familiar scenes was accompanied by a stronger neural representation of the target stimulus, at the cost specifically of those distractors directly surrounding the target. Crucially, this biasing of local attentional competition was behaviorally relevant when searching familiar scenes. Taken together, we conclude that implicitly learned spatial predictive context improves how we search our environment by sharpening the attentional field.

摘要

人类视觉系统能够快速且隐性地学习并利用我们周围环境中的统计规律。在视觉搜索中,情境线索揭示了对场景的隐性知识如何提高搜索性能。这通常被解释为场景中的空间背景变得能够预测目标位置,从而在搜索过程中更有效地引导注意力。然而,驱动这种增强引导的因素尚不清楚。首先,是整个场景(全局背景)还是更多的局部背景驱动了这一现象,这仍存在争议。其次,尚不清楚目标增强和干扰项抑制究竟是如何实现注意力引导的改善的。在当前的脑磁图实验中,我们利用快速不可见频率标记来回答这两个悬而未决的问题。我们发现,在隐性搜索熟悉场景时性能的提高伴随着目标刺激更强的神经表征,代价则是直接围绕目标的那些干扰项。至关重要的是,在搜索熟悉场景时,这种局部注意力竞争的偏向在行为上是相关的。综上所述,我们得出结论,隐性学习的空间预测背景通过锐化注意力场来改善我们搜索周围环境的方式。

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