ArticleNature communications2022
Crowding results from optimal integration of visual targets with contextual information.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed.
- Large-scale mega-analysis indicates that serial dependence deteriorates perceptual decision-making.Nature human behaviour · 2026Article
- Non-uniform signal pooling across the foveola.Current biology : CB · 2025Article
- Target-flanker similarity alters the spatial profile of visual crowding.Journal of vision · 2025Article
- Failure to replicate a superiority effect in crowding.Nature communications · 2025Article
- Reply to: Failure to replicate a superiority effect in crowding.Nature communications · 2025Article
- Color crowding considered as adaptive spatial integration.Journal of vision · 2024Article
- Oculomotor Contributions to Foveal Crowding.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Super recognizers: Increased sensitivity or reduced biases? Insights from serial dependence.Journal of vision · 2024Article
- Probing the Bottleneck of Awareness Formed by Foveal Crowding: A Neurophysiological Study.Brain sciences · 2024Article
- Serial dependence improves performance and biases confidence-based decisions.Journal of vision · 2023Article
- Modeling facial perception in group context from a serial perception perspective.Journal of vision · 2023Article
- Crowding results from optimal integration of visual targets with contextual information.Nature communications · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Crowding is the inability to recognize an object in clutter, usually considered a fundamental low-level bottleneck to object recognition. Here we advance and test an alternative idea, that crowding, like predictive phenomena such as serial dependence, results from optimizing strategies that exploit redundancies in natural scenes. This notion leads to several testable predictions: crowding should be greatest for unreliable targets and reliable flankers; crowding-induced biases should be maximal when target and flankers have similar orientations, falling off for differences around 20°; flanker interference should be associated with higher precision in orientation judgements, leading to lower overall error rate; effects should be maximal when the orientation of the target is near that of the average of the flankers, rather than to that of individual flankers. Each of these predictions were supported, and could be simulated with ideal-observer models that maximize performance. The results suggest that while crowding can affect object recognition, it may be better understood not as a processing bottleneck, but as a consequence of efficient exploitation of the spatial redundancies of the natural world.
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Registered trials
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.