Evidence map›Paper›PMID 26114678›Full record

ArticleJournal of vision2015

Single neural code for blur in subjects with different interocular optical blur orientation.

Aiswaryah Radhakrishnan, Lucie Sawides, Carlos Dorronsoro, Eli Peli, Susana Marcos

Open access · goldAbstract read
In one paragraph

Article in Journal of vision, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
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

5 authors at 3 institutions in 2 countries.

Aiswaryah Radhakrishnan
Lucie Sawides
Carlos Dorronsoro
Eli Peli
Susana Marcos
Consejo Superior de Investigaciones Científicas · ESInstituto de Óptica "Daza de Valdés" · ESHarvard University · US

Funding

MODEL-BASED IMAGE ENHANCEMENT FOR THE VISUALLY IMPAIREDR01EY005957 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI PELI, ELI · 1986 to 2013
$5.6M
European Research Council 294099NEI NIH HHS R01 EY005957NEI NIH HHS R01EY05957
6 · The paper itself

Abstract

The ability of the visual system to compensate for differences in blur orientation between eyes is not well understood. We measured the orientation of the internal blur code in both eyes of the same subject monocularly by presenting pairs of images blurred with real ocular point spread functions (PSFs) of similar blur magnitude but varying in orientations. Subjects assigned a level of confidence to their selection of the best perceived image in each pair. Using a classification-images-inspired paradigm and applying a reverse correlation technique, a classification map was obtained from the weighted averages of the PSFs, representing the internal blur code. Positive and negative neural PSFs were obtained from the classification map, representing the neural blur for best and worse perceived blur, respectively. The neural PSF was found to be highly correlated in both eyes, even for eyes with different ocular PSF orientations (rPos = 0.95; rNeg = 0.99; p < 0.001). We found that in subjects with similar and with different ocular PSF orientations between eyes, the orientation of the positive neural PSF was closer to the orientation of the ocular PSF of the eye with the better optical quality (average difference was ∼10°), while the orientation of the positive and negative neural PSFs tended to be orthogonal. These results suggest a single internal code for blur with orientation driven by the orientation of the optical blur of the eye with better optical quality.

Indexed as

OrientationAdultFemaleHumansMaleNeuronsVision DisordersVisual CortexYoung Adult

Identifiers

PMID26114678
PMCPMC4484355
OpenAlexW1553778601

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.