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视觉工作记忆中的遗忘:内部噪声解释了特征表示的衰减。

Forgetting in visual working memory: Internal noise explains decay of feature representations.

机构信息

Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.

出版信息

J Vis. 2022 Jul 11;22(8):8. doi: 10.1167/jov.22.8.8.

DOI:10.1167/jov.22.8.8
PMID:35838485
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9296891/
Abstract

The precision of visual working memory (VWM) representations decreases as time passes. It is often assumed that VWM decay is random and caused by internal noise accumulation. However, forgetting in VWM could occur systematically, such that some features deteriorate more rapidly than others. There exist only a few studies testing these two models of forgetting, with conflicting results. Here, decay of features in VWM was thoroughly tested using signal detection theory methods: psychophysical classification images, internal noise estimation, and receiver operant characteristic (ROC). A modified same-different memory task was employed with two retention times (500 and 4000 ms). Experiment 1 investigated VWM decay using a compound grating memory task, and Experiment 2 tested shape memory using radial frequency patterns. Memory performance dropped some 15% with increasing retention time in both experiments. Interestingly, classification images showed virtually indistinguishable weighting of stimulus features at both retention times, suggesting that VWM decay is not feature specific. Instead, we found a 77% increase in stimulus-independent internal noise at the longer retention time. Finally, the slope of the ROC curve plotted as z-scores was shallower at the longer retention time, indicating that the amount of stimulus-independent internal noise increased. Together these findings provide strong support for the idea that VWM decay does not result from a systematic loss of some stimulus features but instead is caused by uniformly increasing random internal noise.

摘要

视觉工作记忆 (VWM) 表示的精度会随着时间的推移而降低。通常认为,VWM 的衰减是随机的,是由于内部噪声的积累造成的。然而,VWM 中的遗忘也可能是系统的,即某些特征比其他特征更快地恶化。目前只有少数研究检验了这两种遗忘模型,结果相互矛盾。在这里,我们使用信号检测理论方法(心理物理分类图像、内部噪声估计和接收者操作特征 (ROC))对 VWM 中的特征衰减进行了彻底的测试。采用了一种改进的相同-不同记忆任务,有两个保持时间(500 毫秒和 4000 毫秒)。实验 1 使用复合光栅记忆任务研究了 VWM 衰减,实验 2 使用径向频率模式测试了形状记忆。在这两个实验中,随着保持时间的增加,记忆性能下降了约 15%。有趣的是,分类图像显示,在两个保持时间下,刺激特征的权重几乎没有区别,这表明 VWM 衰减不是特定于特征的。相反,我们发现,在较长的保持时间内,刺激无关的内部噪声增加了 77%。最后,ROC 曲线的斜率作为 z 分数绘制时,在较长的保持时间上变得更平缓,这表明刺激无关的内部噪声增加了。这些发现共同为这样一种观点提供了有力支持,即 VWM 衰减不是由于某些刺激特征的系统丢失造成的,而是由均匀增加的随机内部噪声引起的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/5f3ddf4218d5/jovi-22-8-8-f008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/a9511979cee5/jovi-22-8-8-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/f461bf3d5027/jovi-22-8-8-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/d39ef32bb736/jovi-22-8-8-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/b629508eeb1d/jovi-22-8-8-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/f5379d7cc215/jovi-22-8-8-f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/1bff7cf14773/jovi-22-8-8-f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/1cbae6a41d5e/jovi-22-8-8-f007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/5f3ddf4218d5/jovi-22-8-8-f008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/a9511979cee5/jovi-22-8-8-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/f461bf3d5027/jovi-22-8-8-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/d39ef32bb736/jovi-22-8-8-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/b629508eeb1d/jovi-22-8-8-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/f5379d7cc215/jovi-22-8-8-f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/1bff7cf14773/jovi-22-8-8-f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/1cbae6a41d5e/jovi-22-8-8-f007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20ee/9296891/5f3ddf4218d5/jovi-22-8-8-f008.jpg

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