Evidence map›Paper›PMID 33649371›Full record

Trial reportScientific reports2021

Binocular summation is affected by crowding and tagging.

Ziv Siman-Tov, Maria Lev, Uri Polat

Abstract readClinical Trial
In one paragraph

Trial report in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Effect of Visual Crowding on Quality of Life in Glaucoma Patients.Investigative ophthalmology & visual science · 2026
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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

3 authors.

Ziv Siman-TovSchool of Optometry and Vision Sciences, Bar-Ilan University, Ramat Gan, Israel.
Maria LevSchool of Optometry and Vision Sciences, Bar-Ilan University, Ramat Gan, Israel.
Uri PolatSchool of Optometry and Vision Sciences, Bar-Ilan University, Ramat Gan, Israel. uri.polat@biu.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In perceptual crowding, a letter easily recognized on its own, becomes unrecognizable if it is surrounded by other letters, an effect that confers a limit on the visual processing. Models assume that crowding is a hallmark of the periphery but that it is almost absent in the fovea. However, recently it was shown that crowding occurs in the fovea of people with an abnormal development of functional vision (amblyopia), when the stimulus is presented for a very short time. When targets and flankers are dissimilar, the crowding is reduced (tagging). Since a combination of binocular inputs increases the processing load, we investigated whether color tagging the target reduces crowding in the fovea of subjects with normal vision and determined how crowding is combined with binocular vision. The crowding effect at the fovea was significantly reduced by tagging with a color target. Interestingly, whereas binocular summation for a single letter was expected to be about 40%, it was significantly reduced and almost absent under crowding conditions. Our results are consistent with the notion that the crowding effect produces a high processing load on visual processing, which interferes with other processes such as binocular summation. We assume that the tagging effect in our experiment improved the subject's abilities (sensitivity and RT) by creating a "segmentation", i.e., a visual simulated separation between the target letter and the background. Interestingly, tagging the target with a distinct color can eliminate or reduce the crowding effect and consequently, binocular summation recovers.

Indexed as

Pattern Recognition, VisualVision, BinocularAdultAmblyopiaFemaleHumansMale

Identifiers

PMID33649371
PMCPMC7921124

What OpenQuestion holds

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Registered trials

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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.