Evidence map›Paper›PMID 32502415›Full record

ArticleCurrent biology : CB2020

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

Sebastian M Frank, Andrea Qi, Daniela Ravasio, Yuka Sasaki, Eric L Rosen, Takeo Watanabe

Abstract read
In one paragraph

Article in Current biology : CB, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Review
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  7. A hole in a piece of cardboard and predictive brain: the incomprehension of modern art in the light of the predictive coding paradigm.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  8. Review
  9. Article
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  13. Transfer of Tactile Learning from Trained to Untrained Body Parts Supported by Cortical Coactivation in Primary Somatosensory Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Article
  14. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Sebastian M FrankBrown University, Department of Cognitive, Linguistic, and Psychological Sciences, 190 Thayer Street, Providence, RI 02912, USA. Electronic address: sebastian_frank@brown.edu.
Andrea QiBrown University, Department of Cognitive, Linguistic, and Psychological Sciences, 190 Thayer Street, Providence, RI 02912, USA.
Daniela RavasioBrown University, Department of Cognitive, Linguistic, and Psychological Sciences, 190 Thayer Street, Providence, RI 02912, USA.
Yuka SasakiBrown University, Department of Cognitive, Linguistic, and Psychological Sciences, 190 Thayer Street, Providence, RI 02912, USA.
Eric L RosenStanford University, Department of Radiology, 300 Pasteur Drive, Stanford, CA 94305, USA; University of Colorado Denver, Department of Radiology, 12401 East 17th Avenue, Aurora, CO 80045, USA.
Takeo WatanabeBrown University, Department of Cognitive, Linguistic, and Psychological Sciences, 190 Thayer Street, Providence, RI 02912, USA. Electronic address: takeo_watanabe@brown.edu.

Funding

SYSTEMATIC PSYCHOPHYSICAL INVESTIGATION OF VISUAL LEARNINGR01EY019466 · NEI · BROWN UNIVERSITY · PI Takeo Watanabe · 2009 to 2026
$6.6M
Comprehensive frameworks of perceptual learningR01EY027841 · NEI · BROWN UNIVERSITY · PI Takeo Watanabe · 2018 to 2026
$3.2M
The first night effect of sleep and visual plasticityR21EY028329 · NEI · BROWN UNIVERSITY · PI SASAKI, YUKA · 2018 to 2019
$447k
NEI NIH HHS R01 EY019466NEI NIH HHS R01 EY027841NEI NIH HHS R21 EY028329
6 · The paper itself

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.

Indexed as

MammographyAdultEducation, MedicalFemaleFormative FeedbackHumansLearningMaleMemory, Long-TermOrganization and AdministrationRadiologistsRetention, PsychologyVisual PerceptionYoung Adultbreast cancerfeedbackhigh-level visionmammogramnatural stimuliradiologysupervised learningunsupervised learningvisual perceptual learning

Identifiers

PMID32502415
PMCPMC7415644

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

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.