Evidence map›Paper›PMID 31038458›Full record

ArticleeLife2019

Image content is more important than Bouma's Law for scene metamers.

Thomas Sa Wallis, Christina M Funke, Alexander S Ecker, Leon A Gatys, Felix A Wichmann, Matthias Bethge

Abstract read
In one paragraph

Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Generating metamers of human scene understanding.... International Conference on Learning Representations · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Responses of neurons in macaque V4 to object and texture images.bioRxiv : the preprint server for biology · 2025
    Article
  12. Neural Correlates of Crowding in Macaque Area V4.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  13. Neural correlates of crowding in macaque area V4.bioRxiv : the preprint server for biology · 2023
    Article
  14. Measuring uncertainty in human visual segmentation.PLoS computational biology · 2023
    Article
  15. Article
  16. Texture-like representation of objects in human visual cortex.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. Dissecting (un)crowding.Journal of vision · 2021
    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

6 authors.

Thomas Sa Wallis *Werner Reichardt Center for Integrative Neuroscience, Eberhard Karls Universität Tübingen, Tübingen, Germany.ORCID 0000-0001-7431-4852
Christina M Funke *Werner Reichardt Center for Integrative Neuroscience, Eberhard Karls Universität Tübingen, Tübingen, Germany.
Alexander S EckerWerner Reichardt Center for Integrative Neuroscience, Eberhard Karls Universität Tübingen, Tübingen, Germany.ORCID 0000-0003-2392-5105
Leon A GatysWerner Reichardt Center for Integrative Neuroscience, Eberhard Karls Universität Tübingen, Tübingen, Germany.
Felix A WichmannNeural Information Processing Group, Faculty of Science, Eberhard Karls Universität Tübingen, Tübingen, Germany.ORCID 0000-0002-2592-634X
Matthias BethgeCenter for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States.ORCID 0000-0002-6417-7812

Funding

Alexander von Humboldt-Stiftung Thomas WallisBundesministerium für Bildung und Forschung FKZ: 01GQ1002Deutsche Forschungsgemeinschaft 276693517; SFB 1233Deutsche Forschungsgemeinschaft BE 3848/2-1Deutsche Forschungsgemeinschaft Priority program 1527
6 · The paper itself

Abstract

We subjectively perceive our visual field with high fidelity, yet peripheral distortions can go unnoticed and peripheral objects can be difficult to identify (crowding). Prior work showed that humans could not discriminate images synthesised to match the responses of a mid-level ventral visual stream model when information was averaged in receptive fields with a scaling of about half their retinal eccentricity. This result implicated ventral visual area V2, approximated 'Bouma's Law' of crowding, and has subsequently been interpreted as a link between crowding zones, receptive field scaling, and our perceptual experience. However, this experiment never assessed natural images. We find that humans can easily discriminate real and model-generated images at V2 scaling, requiring scales at least as small as V1 receptive fields to generate metamers. We speculate that explaining why scenes look as they do may require incorporating segmentation and global organisational constraints in addition to local pooling.

Indexed as

CrowdingDiscrimination, PsychologicalFixation, OcularHumansPattern Recognition, VisualPerceptual MaskingPhotic StimulationSpace PerceptionVisual FieldsVisual Perceptioncrowdinghumanneurosciencescene appearancetexture perceptionvisual perception

Identifiers

PMID31038458
PMCPMC6491040

What OpenQuestion holds

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LicenceCC BY
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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.