Evidence map›Paper›PMID 34905053›Full record

ArticleJournal of vision2021

Assessing the functions underlying learning using by-trial and by-participant models: Evidence from two visual perceptual learning paradigms.

Aaron Cochrane, C Shawn Green

Abstract read
In one paragraph

Article in Journal of vision, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Task-Irrelevant Phase but not Contrast Variability Unlocks Generalization in Visual Perceptual Learning.Journal of cognitive enhancement : towards the integration of theory and practice · 2025
    Article
  5. Article
  6. Article
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  9. Article
  10. Repetition learning is neither a continuous nor an implicit process.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  11. Comparisons in Adaptive Perceptual Category Learning.CogSci ... Annual Conference of the Cognitive Science Society. Cognitive Science Society (U.S.). Conference · 2022
    Article
  12. 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

2 authors.

Aaron CochraneFaculty of Psychology and Education Sciences, University of Geneva, Geneva, Switzerland.
C Shawn GreenDepartment of Psychology, University of Wisconsin-Madison, Madison, WI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inferred mechanisms of learning, such as those involved in improvements resulting from perceptual training, are reliant on (and reflect) the functional forms that models of learning take. However, previous investigations of the functional forms of perceptual learning have been limited in ways that are incompatible with the known mechanisms of learning. For instance, previous work has overwhelmingly aggregated learning data across learning participants, learning trials, or both. Here we approach the study of the functional form of perceptual learning on the by-person and by-trial levels at which the mechanisms of learning are expected to act. Each participant completed one of two visual perceptual learning tasks over the course of two days, with the first 75% of task performance using a single reference stimulus (i.e., "training") and the last 25% using an orthogonal reference stimulus (to test generalization). Five learning functions, coming from either the exponential or the power family, were fit to each participant's data. The exponential family was uniformly supported by Bayesian Information Criteria (BIC) model comparisons. The simplest exponential function was the best fit to learning on a texture oddball detection task, while a Weibull (augmented exponential) function tended to be the best fit to learning on a dot-motion discrimination task. The support for the exponential family corroborated previous by-person investigations of the functional form of learning, while the novel evidence supporting the Weibull learning model has implications for both the analysis and the mechanistic bases of the learning.

Indexed as

Generalization, PsychologicalTask Performance and AnalysisBayes TheoremHumansSpatial LearningVisual Perception

Identifiers

PMID34905053
PMCPMC8684311

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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.