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本文引用的文献

1
Category-Induced Transfer of Visual Perceptual Learning.类别诱导的视觉感知学习迁移。
Curr Biol. 2019 Apr 22;29(8):1374-1378.e3. doi: 10.1016/j.cub.2019.03.003. Epub 2019 Mar 28.
2
Consolidation and reconsolidation share behavioral and neurochemical mechanisms.巩固和重新巩固具有共同的行为和神经化学机制。
Nat Hum Behav. 2018 Jul;2(7):507-513. doi: 10.1038/s41562-018-0366-8. Epub 2018 Jul 9.
3
The incidence of fatal breast cancer measures the increased effectiveness of therapy in women participating in mammography screening.致命性乳腺癌的发病率衡量了参加乳房 X 线照片筛查的女性中治疗效果的提高。
Cancer. 2019 Feb 15;125(4):515-523. doi: 10.1002/cncr.31840. Epub 2018 Nov 8.
4
Deep Neural Networks for Modeling Visual Perceptual Learning.深度神经网络在视觉感知学习建模中的应用。
J Neurosci. 2018 Jul 4;38(27):6028-6044. doi: 10.1523/JNEUROSCI.1620-17.2018. Epub 2018 May 23.
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Visual Perceptual Learning and Models.视觉感知学习与模型。
Annu Rev Vis Sci. 2017 Sep 15;3:343-363. doi: 10.1146/annurev-vision-102016-061249. Epub 2017 Jul 19.
6
Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant.过度学习通过迅速使神经化学处理以抑制为主导,从而使技能超稳定。
Nat Neurosci. 2017 Mar;20(3):470-475. doi: 10.1038/nn.4490. Epub 2017 Jan 30.
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Architectural Distortion on Mammography: Correlation With Pathologic Outcomes and Predictors of Malignancy.乳腺摄影中的结构扭曲:与病理结果的相关性及恶性肿瘤的预测因素。
AJR Am J Roentgenol. 2015 Dec;205(6):1339-45. doi: 10.2214/AJR.15.14628.
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Perceptual learning: toward a comprehensive theory.知觉学习:迈向一种综合理论
Annu Rev Psychol. 2015 Jan 3;66:197-221. doi: 10.1146/annurev-psych-010814-015214. Epub 2014 Sep 10.
9
Performance-optimized hierarchical models predict neural responses in higher visual cortex.性能优化的层次模型预测高级视觉皮层中的神经反应。
Proc Natl Acad Sci U S A. 2014 Jun 10;111(23):8619-24. doi: 10.1073/pnas.1403112111. Epub 2014 May 8.
10
Two-stage model in perceptual learning: toward a unified theory.两阶段模型在感知学习中的应用:走向统一理论。
Ann N Y Acad Sci. 2014 May;1316:18-28. doi: 10.1111/nyas.12419. Epub 2014 Apr 23.

监督学习发生在复杂自然图像的视觉感知学习中。

Supervised Learning Occurs in Visual Perceptual Learning of Complex Natural Images.

机构信息

Brown University, Department of Cognitive, Linguistic, and Psychological Sciences, 190 Thayer Street, Providence, RI 02912, USA.

Brown University, Department of Cognitive, Linguistic, and Psychological Sciences, 190 Thayer Street, Providence, RI 02912, USA.

出版信息

Curr Biol. 2020 Aug 3;30(15):2995-3000.e3. doi: 10.1016/j.cub.2020.05.050. Epub 2020 Jun 4.

DOI:10.1016/j.cub.2020.05.050
PMID:32502415
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7415644/
Abstract

There have been long-standing debates regarding whether supervised or unsupervised learning mechanisms are involved in visual perceptual learning (VPL) [1-14]. However, these debates have been based on the effects of simple feedback only about response accuracy in detection or discrimination tasks of low-level visual features such as orientation [15-22]. Here, we examined whether the content of response feedback plays a critical role for the acquisition and long-term retention of VPL of complex natural images. We trained three groups of human subjects (n = 72 in total) to better detect "grouped microcalcifications" or "architectural distortion" lesions (referred to as calcification and distortion in the following) in mammograms either with no trial-by-trial feedback, partial trial-by-trial feedback (response correctness only), or detailed trial-by-trial feedback (response correctness and target location). Distortion lesions consist of more complex visual structures than calcification lesions [23-26]. We found that partial feedback is necessary for VPL of calcifications, whereas detailed feedback is required for VPL of distortions. Furthermore, detailed feedback during training is necessary for VPL of distortion and calcification lesions to be retained for 6 months. These results show that although supervised learning is heavily involved in VPL of complex natural images, the extent of supervision for VPL varies across different types of complex natural images. Such differential requirements for VPL to improve the detectability of lesions in mammograms are potentially informative for the professional training of radiologists.

摘要

关于视觉感知学习(VPL)是否涉及监督或无监督学习机制,一直存在着长期的争论[1-14]。然而,这些争论仅仅基于简单反馈的效果,这些反馈仅涉及检测或辨别任务中低水平视觉特征(如方向)的响应准确性[15-22]。在这里,我们研究了响应反馈的内容是否对复杂自然图像的 VPL 的获得和长期保留起着关键作用。我们训练了三组人类受试者(总共有 72 名),以更好地检测乳房 X 光片中的“分组微钙化”或“结构扭曲”病变(在以下内容中分别称为钙化和扭曲),分别为无逐次反馈、部分逐次反馈(仅反馈响应正确性)或详细逐次反馈(反馈响应正确性和目标位置)。与钙化病变相比,扭曲病变包含更复杂的视觉结构[23-26]。我们发现,部分反馈对于钙化的 VPL 是必要的,而详细反馈对于扭曲的 VPL 是必需的。此外,在训练过程中详细的反馈对于保持 6 个月的扭曲和钙化病变的 VPL 是必需的。这些结果表明,尽管监督学习在复杂自然图像的 VPL 中起着重要作用,但 VPL 的监督程度因不同类型的复杂自然图像而异。这种在改善乳房 X 光片中病变检测能力方面对 VPL 的不同需求,对于放射科医生的专业培训可能具有信息意义。