Evidence map›Paper›PMID 38450381›Full record

ArticleFrontiers in aging neuroscience2024

tRNS boosts visual perceptual learning in participants with bilateral macular degeneration.

Giulio Contemori, Marcello Maniglia, Jade Guénot, Vincent Soler, Marta Cherubini, Benoit R Cottereau, Yves Trotter

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

10 citing papers in PubMed, 12 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Trial
  4. Article
  5. Review
  6. Article
  7. Review
  8. Motion Processing in Visual Cortex of Maculopathy Patients.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  9. Article
  10. 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

7 authors at 6 institutions in 3 countries.

Giulio Contemori *Department of General Psychology, University of Padova, Padua, Italy.
Marcello Maniglia *Department of Psychology, University of California, Riverside, Riverside, CA, United States.
Jade GuénotCentre de Recherche Cerveau et Cognition, Université de Toulouse, Toulouse, France.
Vincent SolerService d'Ophtalmologie Centre Hospitalier Universitaire de Toulouse, Toulouse, France.
Marta CherubiniCentre National de la Recherche Scientifique, Toulouse, France.
Benoit R CottereauCentre de Recherche Cerveau et Cognition, Université de Toulouse, Toulouse, France.
Yves TrotterCentre de Recherche Cerveau et Cognition, Université de Toulouse, Toulouse, France.
Université de Toulouse · FRCentre de recherche cerveau et cognition · FRCentre Hospitalier Universitaire de Toulouse · FRUniversity of California, Riverside · USUniversity of Padua · ITUniversity of Trento · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Perceptual learning (PL) has shown promise in enhancing residual visual functions in patients with age-related macular degeneration (MD), however it requires prolonged training and evidence of generalization to untrained visual functions is limited. Recent studies suggest that combining transcranial random noise stimulation (tRNS) with perceptual learning produces faster and larger visual improvements in participants with normal vision. Thus, this approach might hold the key to improve PL effects in MD. To test this, we trained two groups of MD participants on a contrast detection task with (

Indexed as

contrast detectionmacular degenerationperceptual learningtransfer of learningtRNS

Identifiers

PMID38450381
PMCPMC10914974
OpenAlexW4392002856

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.