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视觉统计学习需要注意力。

Visual statistical learning requires attention.

作者信息

Duncan Dock H, van Moorselaar Dirk, Theeuwes Jan

机构信息

Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

Institute Brain and Behavior Amsterdam (iBBA), Amsterdam, the Netherlands.

出版信息

Psychon Bull Rev. 2025 Jun;32(3):1240-1253. doi: 10.3758/s13423-024-02605-1. Epub 2024 Nov 4.

DOI:10.3758/s13423-024-02605-1
PMID:39497006
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12092514/
Abstract

Statistical learning is a person's ability to automatically learn environmental regularities through passive exposure. Since the earliest studies of statistical learning in infants, it has been debated exactly how "passive" this learning can be (i.e., whether attention is needed for learning to occur). In Experiment 1 of the current study, participants performed a serial feature search task where they searched for a target shape among heterogenous nontarget shapes. Unbeknownst to the participants, one of these nontarget shapes was presented much more often in location. Even though the regularity concerned a nonsalient, nontarget item that did not receive any attentional priority during search, participants still learned its regularity (responding faster when it was presented at this high-probability location). While this may suggest that not much, if any, attention is needed for learning to occur, follow-up experiments showed that if an attentional strategy (i.e., color subset search or exogenous cueing) effectively prevents attention from being directed to this critical regularity, incidental learning is no longer observed. We conclude that some degree of attention to a regularity is needed for visual statistical learning to occur.

摘要

统计学习是指个体通过被动接触自动学习环境规律的能力。自最早对婴儿统计学习的研究以来,关于这种学习究竟有多“被动”(即学习发生时是否需要注意力)一直存在争议。在本研究的实验1中,参与者执行了一项序列特征搜索任务,他们在异质的非目标形状中搜索目标形状。参与者并不知道,这些非目标形状中的一个在位置上出现的频率要高得多。尽管这种规律涉及到一个在搜索过程中没有得到任何注意力优先对待的不突出的非目标项目,但参与者仍然学会了它的规律(当它出现在这个高概率位置时反应更快)。虽然这可能表明学习发生时不需要太多注意力(如果需要的话),但后续实验表明,如果一种注意力策略(即颜色子集搜索或外部提示)有效地阻止注意力指向这个关键规律,就不再会观察到附带学习。我们得出结论,视觉统计学习的发生需要对规律有一定程度的注意力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/cb6e9d834fed/13423_2024_2605_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/093234b0b013/13423_2024_2605_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/e240f42f2450/13423_2024_2605_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/9391960ea724/13423_2024_2605_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/cb6e9d834fed/13423_2024_2605_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/093234b0b013/13423_2024_2605_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/e240f42f2450/13423_2024_2605_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/9391960ea724/13423_2024_2605_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76a/12092514/cb6e9d834fed/13423_2024_2605_Fig4_HTML.jpg

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本文引用的文献

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Contextual cueing of visual search reflects the acquisition of an optimal, one-for-all oculomotor scanning strategy.视觉搜索的情境线索反映了一种最优的、适用于所有人的眼动扫描策略的习得。
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Object-based suppression in target search but not in distractor inhibition.基于对象的目标搜索抑制,但不是分心物抑制。
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Spatial transfer of object-based statistical learning.基于对象的统计学习的空间转移。
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Statistical learning of target and distractor spatial probability shape a common attentional priority computation.目标和干扰物空间概率的统计学习形成了一种共同的注意力优先计算。
Cortex. 2023 Dec;169:95-117. doi: 10.1016/j.cortex.2023.08.013. Epub 2023 Sep 30.
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No evidence for contextual cueing beyond explicit recognition.没有证据表明语境线索能超越明确的识别。
Psychon Bull Rev. 2024 Jun;31(3):907-930. doi: 10.3758/s13423-023-02358-3. Epub 2023 Oct 16.
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The Electrophysiological Markers of Statistically Learned Attentional Enhancement: Evidence for a Saliency-based Mechanism.统计学习注意力增强的电生理标志物:基于显着性的机制证据。
J Cogn Neurosci. 2023 Dec 1;35(12):2110-2125. doi: 10.1162/jocn_a_02066.
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Pinging the brain to reveal the hidden attentional priority map using encephalography.利用脑电图技术对大脑进行探测,揭示隐藏的注意力优先图。
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The effect of load on spatial statistical learning.负荷对空间统计学习的影响。
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The Attentional Capture Debate: When Can We Avoid Salient Distractors and When Not?注意力捕获之争:何时我们能够避开显著干扰物,何时不能?
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