Evidence map›Paper›PMID 31396138›Full record

ArticleFrontiers in psychology2019

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

Benjamin Chen, Matthew Mundy, Naotsugu Tsuchiya

Abstract read
In one paragraph

Article in Frontiers in psychology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Benjamin ChenSchool of Psychological Sciences, Faculty of Biomedical and Psychological Sciences, Monash University, Melbourne, VIC, Australia.
Matthew MundySchool of Psychological Sciences, Faculty of Biomedical and Psychological Sciences, Monash University, Melbourne, VIC, Australia.
Naotsugu TsuchiyaSchool of Psychological Sciences, Faculty of Biomedical and Psychological Sciences, Monash University, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

conscious and unconscious memoryface perception and cognitionmemory and learningmetacognitionperceptual learning

Identifiers

PMID31396138
PMCPMC6667671

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.