• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

多方位特征检测学习中特征可变性决定特异性和迁移性。

Feature variability determines specificity and transfer in multiorientation feature detection learning.

机构信息

School of Psychological and Cognitive Sciences, and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.

出版信息

J Vis. 2024 May 1;24(5):2. doi: 10.1167/jov.24.5.2.

DOI:10.1167/jov.24.5.2
PMID:38691087
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11079675/
Abstract

Historically, in many perceptual learning experiments, only a single stimulus is practiced, and learning is often specific to the trained feature. Our prior work has demonstrated that multi-stimulus learning (e.g., training-plus-exposure procedure) has the potential to achieve generalization. Here, we investigated two important characteristics of multi-stimulus learning, namely, roving and feature variability, and their impacts on multi-stimulus learning and generalization. We adopted a feature detection task in which an oddly oriented target bar differed by 16° from the background bars. The stimulus onset asynchrony threshold between the target and the mask was measured with a staircase procedure. Observers were trained with four target orientation search stimuli, either with a 5° deviation (30°-35°-40°-45°) or with a 45° deviation (30°-75°-120°-165°), and the four reference stimuli were presented in a roving manner. The transfer of learning to the swapped target-background orientations was evaluated after training. We found that multi-stimulus training with a 5° deviation resulted in significant learning improvement, but learning failed to transfer to the swapped target-background orientations. In contrast, training with a 45° deviation slowed learning but produced a significant generalization to swapped orientations. Furthermore, a modified training-plus-exposure procedure, in which observers were trained with four orientation search stimuli with a 5° deviation and simultaneously passively exposed to orientations with high feature variability (45° deviation), led to significant orientation learning generalization. Learning transfer also occurred when the four orientation search stimuli with a 5° deviation were presented in separate blocks. These results help us to specify the condition under which multistimuli learning produces generalization, which holds potential for real-world applications of perceptual learning, such as vision rehabilitation and expert training.

摘要

从历史上看,在许多感知学习实验中,只使用单个刺激进行训练,并且学习通常是针对所训练特征的。我们之前的工作已经证明,多刺激学习(例如,训练加暴露程序)有可能实现泛化。在这里,我们研究了多刺激学习的两个重要特征,即游动和特征可变性,以及它们对多刺激学习和泛化的影响。我们采用了一种特征检测任务,其中一个奇怪定向的目标条与背景条相差 16°。使用阶梯程序测量目标和掩蔽之间的刺激起始异步阈值。观察者接受四种目标方向搜索刺激的训练,或者以 5°的偏差(30°-35°-40°-45°),或者以 45°的偏差(30°-75°-120°-165°),并且以游动的方式呈现四个参考刺激。在训练后评估学习对交换目标-背景方向的转移情况。我们发现,5°偏差的多刺激训练导致显著的学习改善,但学习无法转移到交换的目标-背景方向。相比之下,45°偏差的训练会减缓学习速度,但会产生对交换方向的显著泛化。此外,一种改进的训练加暴露程序,其中观察者接受四种方向搜索刺激,以 5°的偏差进行训练,同时被动地暴露于具有高特征可变性的方向(45°的偏差),导致显著的方向学习泛化。当以 5°的偏差呈现四个方向搜索刺激时,也会发生学习转移。这些结果帮助我们确定了多刺激学习产生泛化的条件,这对感知学习的实际应用具有潜在价值,例如视力康复和专家培训。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/37a087a1882b/jovi-24-5-2-f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/3dad7ba307fe/jovi-24-5-2-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/07218da74521/jovi-24-5-2-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/46b8172fe491/jovi-24-5-2-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/4c7be538b6b0/jovi-24-5-2-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/151aca501470/jovi-24-5-2-f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/37a087a1882b/jovi-24-5-2-f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/3dad7ba307fe/jovi-24-5-2-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/07218da74521/jovi-24-5-2-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/46b8172fe491/jovi-24-5-2-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/4c7be538b6b0/jovi-24-5-2-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/151aca501470/jovi-24-5-2-f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7037/11079675/37a087a1882b/jovi-24-5-2-f006.jpg

相似文献

1
Feature variability determines specificity and transfer in multiorientation feature detection learning.多方位特征检测学习中特征可变性决定特异性和迁移性。
J Vis. 2024 May 1;24(5):2. doi: 10.1167/jov.24.5.2.
2
Transfer of visual perceptual learning over a task-irrelevant feature through feature-invariant representations: Behavioral experiments and model simulations.通过特征不变表示实现与任务无关特征的视觉知觉学习的转移:行为实验和模型模拟。
J Vis. 2024 Jun 3;24(6):17. doi: 10.1167/jov.24.6.17.
3
Feature reliability determines specificity and transfer of perceptual learning in orientation search.特征可靠性决定了定向搜索中知觉学习的特异性和迁移。
PLoS Comput Biol. 2017 Dec 14;13(12):e1005882. doi: 10.1371/journal.pcbi.1005882. eCollection 2017 Dec.
4
Perceptual Learning at a Conceptual Level.概念层面的知觉学习。
J Neurosci. 2016 Feb 17;36(7):2238-46. doi: 10.1523/JNEUROSCI.2732-15.2016.
5
Transfer of perceptual learning between different visual tasks.不同视觉任务间的知觉学习迁移
J Vis. 2012 Oct 9;12(11):4. doi: 10.1167/12.11.4.
6
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.
7
Feature-based attention enables robust, long-lasting location transfer in human perceptual learning.基于特征的注意力可实现人类感知学习中稳健、持久的位置迁移。
Sci Rep. 2021 Jul 6;11(1):13914. doi: 10.1038/s41598-021-93016-y.
8
Perceptual learning improves adult amblyopic vision through rule-based cognitive compensation.知觉学习通过基于规则的认知补偿改善成人弱视视力。
Invest Ophthalmol Vis Sci. 2014 Apr 1;55(4):2020-30. doi: 10.1167/iovs.13-13739.
9
An integrated reweighting theory of perceptual learning.一种整合的知觉学习重加权理论。
Proc Natl Acad Sci U S A. 2013 Aug 13;110(33):13678-83. doi: 10.1073/pnas.1312552110. Epub 2013 Jul 29.
10
Push-pull training reduces foveal sensory eye dominance within the early visual channels.推拉训练可降低早期视觉通道内的中央凹感觉眼优势。
Vision Res. 2012 May 15;61:48-59. doi: 10.1016/j.visres.2011.06.005. Epub 2011 Jun 13.

引用本文的文献

1
A Systematic Review and Meta-Analysis of Perceptual Learning and Video Game Training for Adults with Monocular Amblyopia.单眼弱视成人的知觉学习与视频游戏训练的系统评价和荟萃分析
Ophthalmol Ther. 2025 May;14(5):857-881. doi: 10.1007/s40123-025-01128-9. Epub 2025 Mar 27.

本文引用的文献

1
Current directions in visual perceptual learning.视觉感知学习的当前发展方向。
Nat Rev Psychol. 2022 Nov;1(11):654-668. doi: 10.1038/s44159-022-00107-2. Epub 2022 Sep 27.
2
Perceptual learning: Breaking specificity by variability.知觉学习:通过变异性打破特异性。
Curr Biol. 2023 Mar 13;33(5):R182-R185. doi: 10.1016/j.cub.2023.01.025.
3
Variability in training unlocks generalization in visual perceptual learning through invariant representations.训练中的变异性通过不变表征实现视觉感知学习中的泛化。
Curr Biol. 2023 Mar 13;33(5):817-826.e3. doi: 10.1016/j.cub.2023.01.011. Epub 2023 Jan 31.
4
A supramodal and conceptual representation of subsecond time revealed with perceptual learning of temporal interval discrimination.通过对时间间隔辨别进行感知学习,揭示了亚秒级时间的超模态和概念性表示。
Sci Rep. 2022 Jun 23;12(1):10668. doi: 10.1038/s41598-022-14698-6.
5
How variability shapes learning and generalization.变异性如何塑造学习和泛化。
Trends Cogn Sci. 2022 Jun;26(6):462-483. doi: 10.1016/j.tics.2022.03.007.
6
Assessing the functions underlying learning using by-trial and by-participant models: Evidence from two visual perceptual learning paradigms.使用逐试和逐参与者模型评估学习的功能:来自两个视觉感知学习范式的证据。
J Vis. 2021 Dec 1;21(13):5. doi: 10.1167/jov.21.13.5.
7
Perceptual learning evidence for supramodal representation of stimulus orientation at a conceptual level.知觉学习证据表明刺激方向在概念水平上存在超模式表征。
Vision Res. 2021 Oct;187:120-128. doi: 10.1016/j.visres.2021.06.010. Epub 2021 Jul 9.
8
Stimulus variation-based training enhances artificial grammar learning.基于刺激变化的训练增强了人工语法学习。
Acta Psychol (Amst). 2021 Mar;214:103252. doi: 10.1016/j.actpsy.2021.103252. Epub 2021 Feb 12.
9
Roving: The causes of interference and re-enabled learning in multi-task visual training.巡回:多任务视觉训练中干扰和重新启用学习的原因。
J Vis. 2020 Jun 3;20(6):9. doi: 10.1167/jov.20.6.9.
10
Sequential perceptual learning of letter identification and "uncrowding" in normal peripheral vision: Effects of task, training order, and cholinergic enhancement.正常周边视觉中字母识别和“去拥挤化”的连续知觉学习:任务、训练顺序和胆碱能增强的影响。
J Vis. 2020 Apr 9;20(4):24. doi: 10.1167/jov.20.4.24.