Cited by 417Visual perception and processing mechanismsMultisensory perception and integrationVisual Attention and Saliency Detection

Can attention selectively bias bistable perception? Differences between binocular rivalry and ambiguous figures

Open access
Meng, Ming, Tong, Frank·2004·Journal of Vision

Abstract

It is debated whether different forms of bistable perception result from common or separate neural mechanisms. Binocular rivalry involves perceptual alternations between competing monocular images, whereas ambiguous figures such as the Necker cube lead to alternations between two possible pictorial interpretations. Previous studies have shown that observers can voluntarily control the alternation rate of both rivalry and Necker cube reversal, perhaps suggesting that bistable perception results from a common mechanism of top-down selection. However, according to the biased competition model of selective attention, attention should be able to enhance the attended percept and suppress the unattended percept. Here, we investigated selective attentional modulation of dominance durations in bistable perception. Observers consistently showed much weaker selective attentional control for rivalry than for Necker cube reversal, even for rivalry displays that maximized the opportunities for feature-, object-, or space-based attentional selection. In contrast, nonselective control of alternation rate was comparably strong for both forms of bistable perception and corresponded poorly with estimates of selective attentional control. Our results support the notion that binocular rivalry involves a more automatic, stimulus-driven form of visual competition than Necker cube reversal, and as a consequence, is less easily biased by selective attention.

Integrity signals

Registry

Crossref · 10.1167/4.7.2

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The predictive processing framework explains why we have much more control over the alternation rate in ambiguous figures.

    “This also explains, within the present framework, why we have much more control over the alternation rate in the case of ambiguous fi gures (as demonstrated by Meng & Tong 2004).”

Cites

Flagged first, then by citations

5 of the 45 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Meng, M., & Tong, F.
Affiliations
Princeton University (US)
Venue
Journal of Vision
Published
2004-07-01
Volume
4
Issue
7
Pages
2
ISSN
1534-7362 (ISSN-L)
OpenAlex
W2117776204
Cited by
417
References
45
Citations by year
2026: 8 · 2025: 10 · 2024: 8 · 2023: 27 · 2022: 14 · 2021: 16 · 2020: 20 · 2019: 15 · 2018: 13 · 2017: 15 · 2016: 13 · 2015: 17 · 2014: 28 · 2013: 32 · 2012: 20
FWCI
8.91
Type
journal article
Language
en
Open access
Locations
  • Journal of Vision (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institute of Mental Health (P50 MH62196, P50MH062196)
  • National Eye Institute (R01-EY14202, R01EY014202)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
Keywords
bistable perception, binocular rivalry, ambiguous figures, Necker cube, selective attention, biased competition model, top-down control, visual competition, attentional modulation
MeSH terms
Attention, Cognition, Humans, Retina, Visual Perception, Vision, Binocular, Selection Bias

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review