Evidence map›Paper›PMID 28245491›Full record

ArticleJournal of vision2017

Texture segmentation influences the spatial profile of presaccadic attention.

Saeideh Ghahghaei, Preeti Verghese

Abstract read
In one paragraph

Article in Journal of vision, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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  5. 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.

Saeideh GhahghaeiThe Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA.
Preeti VergheseThe Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA.

Funding

Recovery of Stereopsis in Age-Related Macular DegenerationR01EY022394 · NEI · SMITH-KETTLEWELL EYE RESEARCH INSTITUTE · PI VERGHESE, PREETI · 2012 to 2014
$1.1M
NEI NIH HHS R01 EY022394
6 · The paper itself

Abstract

Attention is important for selecting targets for action. Several studies have shown that attentional selection precedes eye movements to a target, and results in an enhanced sensitivity at the saccade goal. Typically these studies have used isolated targets on blank backgrounds, which are rare in real-world situations. Here, we examine the spatial profile of sensitivity around a saccade target on a textured background and how the influence of the surrounding context develops over time. We used two textured backgrounds: a uniform texture, and a concentric arrangement of an inner and an outer texture with orthogonal orientations. For comparison, we also measured sensitivity around the target on a blank background. The spatial profile of sensitivity was measured with a brief, dim, probe flashed around the saccade target. When the target was on a blank or a uniformly textured background, spatial sensitivity peaked near the target location around 350 ms after cue onset and declined with distance from the target. However, when the background was made up of an inner and outer texture, sensitivity to the inner texture was uniformly high, peaking at about 350 ms after cue onset, suggesting that the entire inner texture was selected along with the target. The enhancement of sensitivity on the inner texture was much smaller when observers attended the target covertly and performed the probe-detection task. Thus, our results suggest that the surface representation around the target is taken into account when an observer actively plans to interact with the target.

Indexed as

AdultAttentionFemaleHumansMaleMiddle AgedOrientationPattern Recognition, VisualSaccades

Identifiers

PMID28245491
PMCPMC5338474

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.