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在隐蔽空间定向过程中解决视觉干扰:通过先前视觉经验的静态记录进行在线注意力控制。

Resolving visual interference during covert spatial orienting: online attentional control through static records of prior visual experience.

作者信息

Awh Edward, Sgarlata Antoinette Marie, Kliestik John

机构信息

Department of Psychology, University of Oregon, Eugene, 97403, USA.

出版信息

J Exp Psychol Gen. 2005 May;134(2):192-206. doi: 10.1037/0096-3445.134.2.192.

Abstract

Models of attentional control usually describe online shifts in control settings that accommodate changing task demands. The current studies suggest that online control over distractor exclusion--a core component of visual selection--can be accomplished without online shifts in top-down settings. Measurements of target discrimination accuracy suggested that the degree of distractor exclusion was guided by retinotopic maps of the prior probability of distractor interference at the attended locations. These probability maps can be retrieved via object-based cues, and they interact with shifts of attention to elicit increased levels of distractor exclusion when it is most needed. Thus, static probability maps can provide an internal template that guides the resolution of visual interference as spatial attention traverses the visual field.

摘要

注意力控制模型通常描述了控制设置的在线变化,以适应不断变化的任务需求。当前的研究表明,对干扰物排除(视觉选择的核心组成部分)的在线控制可以在不进行自上而下设置的在线变化的情况下完成。目标辨别准确性的测量表明,干扰物排除的程度是由所关注位置上干扰物干扰的先验概率的视网膜拓扑图引导的。这些概率图可以通过基于对象的线索检索,并且当最需要时,它们与注意力转移相互作用以引发更高水平的干扰物排除。因此,静态概率图可以提供一个内部模板,当空间注意力遍历视野时,该模板指导视觉干扰的解决。

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