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类别偏见作为视觉工作记忆的关键参数:记忆负荷和保持间隔的影响。

Categorical bias as a crucial parameter in visual working memory: The effect of memory load and retention interval.

机构信息

University of Groningen, Netherlands.

University of Groningen, Netherlands.

出版信息

Cortex. 2022 Sep;154:311-321. doi: 10.1016/j.cortex.2022.05.007. Epub 2022 May 26.

Abstract

Visual information can be stored as continuous as well as categorical representations in visual working memory (VWM) to guide subsequent behavior. Yet it is still unclear what determines whether VWM is represented as continuous or categorical information, or as a mix of both. Recent studies have shown that color VWM representations adjust flexibly depending on the number of memory items as well as the duration that these items need to be maintained for. The current study aims to extend and replicate these crucial effects. In a delayed estimation task, participants memorized one to four colored objects presented at different spatial locations, followed by a delay of 100, 500, 1000, or 2000 msec. Next, a probe indicated the location of the color that participants needed to report. We measured the extent to which responses were biased in the direction of prototypical colors. Crucially, we implemented this categorical bias in an extension to the classic mixture model (Zhang & Luck, 2008) in which the center of the error distribution is a crucial parameter that characterizes the extent to which VWM is biased by color categories. We found that VWM shows a strong categorical bias in all cases, and that this bias increases with increasing memory load; strikingly, this effect of memory load on categorical bias is stronger at longer intervals (1000 msec or longer), as compared to shorter intervals, yet it peaks for intermediate memory loads as opposed to the highest memory load. Overall, our results suggest that when visual information needs to be maintained for one second or longer, VWM becomes more reliant on categorical representations as memory load increases.

摘要

视觉信息可以在视觉工作记忆 (VWM) 中以连续和分类的形式存储,以指导后续行为。然而,目前仍不清楚是什么决定了 VWM 是以连续还是分类的形式,或者是两者的混合形式来表示。最近的研究表明,颜色 VWM 表示会根据记忆项目的数量以及这些项目需要保持的时间而灵活调整。本研究旨在扩展和复制这些关键效应。在延迟估计任务中,参与者记忆一到四个呈现在不同空间位置的彩色物体,然后延迟 100、500、1000 或 2000 毫秒。接下来,一个探针指示参与者需要报告的颜色的位置。我们测量了响应偏向原型颜色的程度。至关重要的是,我们在经典混合模型(Zhang 和 Luck,2008)的扩展中实现了这种分类偏差,其中误差分布的中心是一个关键参数,它描述了 VWM 受到颜色分类的程度。我们发现,在所有情况下,VWM 都表现出强烈的分类偏差,并且这种偏差随着记忆负荷的增加而增加;令人惊讶的是,这种记忆负荷对分类偏差的影响在较长的间隔(1000 毫秒或更长)比在较短的间隔更强,但它在中等记忆负荷时达到峰值,而不是最高记忆负荷时。总的来说,我们的结果表明,当视觉信息需要保持一秒或更长时间时,随着记忆负荷的增加,VWM 会更加依赖于分类表示。

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