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元认知准确性随着低水平而非高水平面部特征的知觉学习而提高。

Metacognitive Accuracy Improves With the Perceptual Learning of a Low- but Not High-Level Face Property.

作者信息

Chen Benjamin, Mundy Matthew, Tsuchiya Naotsugu

机构信息

School of Psychological Sciences, Faculty of Biomedical and Psychological Sciences, Monash University, Melbourne, VIC, Australia.

Monash Institute of Cognitive and Clinical Neuroscience, Monash University, Melbourne, VIC, Australia.

出版信息

Front Psychol. 2019 Jul 24;10:1712. doi: 10.3389/fpsyg.2019.01712. eCollection 2019.

Abstract

Experience with visual stimuli can improve their perceptual performance, a phenomenon termed visual perceptual learning (VPL). VPL has been found to improve metacognitive measures, suggesting increased conscious accessibility to the knowledge supporting perceptual decision-making. However, such studies have largely failed to control objective task accuracy, which typically correlates with metacognition. Here, using a staircase method to control this confound, we investigated whether VPL improves the metacognitive accuracy of perceptual decision-making. Across 3 days, subjects were trained to discriminate faces based on their high-level identity or low-level contrast. Holding objective accuracy constant across training days, perceptual thresholds decreased in both tasks, demonstrating VPL in our protocol. However, whilemetacognitive accuracy was not affected by face contrast VPL, it was decreased by face identity VPL. Our findings couldbe parsimoniously explained by a dual-stage signal detection theory-based model involving an initial perceptual decision-making stage and a second confidence judgment stage. Within this model, internal noise reductions for both stages accounts for our face contrast VPL result, while only first stage noise reductions accounts for our face identity VPL result. In summary, we found evidence suggesting that conscious knowledge accessibility was improved by the VPL of face contrast but not face identity.

摘要

视觉刺激的经验可以提高其感知性能,这一现象被称为视觉感知学习(VPL)。研究发现,视觉感知学习可以改善元认知测量,这表明支持感知决策的知识的意识可及性增加。然而,这类研究在很大程度上未能控制客观任务准确性,而客观任务准确性通常与元认知相关。在此,我们使用阶梯法来控制这一混淆因素,研究视觉感知学习是否能提高感知决策的元认知准确性。在3天的时间里,受试者接受训练,根据面部的高级身份或低级对比度来区分面孔。在训练过程中保持客观准确性不变,两项任务的感知阈值均降低,这表明我们的实验方案中存在视觉感知学习。然而,虽然元认知准确性不受面部对比度视觉感知学习的影响,但它会因面部身份视觉感知学习而降低。我们的研究结果可以用一个基于双阶段信号检测理论的模型来简洁地解释,该模型包括一个初始的感知决策阶段和一个第二阶段的置信度判断阶段。在这个模型中,两个阶段的内部噪声降低解释了我们的面部对比度视觉感知学习结果,而只有第一阶段的噪声降低解释了我们的面部身份视觉感知学习结果。总之,我们发现有证据表明,面部对比度的视觉感知学习提高了意识知识的可及性,但面部身份的视觉感知学习则没有。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0282/6667671/ec120cdd1384/fpsyg-10-01712-g001.jpg

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