Evidence map›Paper›PMID 37901071›Full record

ArticleFrontiers in psychology2023

Reliability of on-line visual feedback influences learning of continuous motor task of healthy young adults.

Marie Bernardo, Yannick Blandin, Géry Casiez, Cécile R Scotto

Abstract read
In one paragraph

Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Marie BernardoCentre de Recherche sur la Cognition et l'Apprentissage, Université de Poitiers, Université François Rabelais de Tours, Poitiers, France.
Yannick BlandinCentre de Recherche sur la Cognition et l'Apprentissage, Université de Poitiers, Université François Rabelais de Tours, Poitiers, France.
Géry CasiezUniv. Lille, CNRS, Inria, Centrale Lille, UMR 9189 CRIStAL, Lille, France.
Cécile R ScottoCentre de Recherche sur la Cognition et l'Apprentissage, Université de Poitiers, Université François Rabelais de Tours, Poitiers, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A continuous task was used to determine how the reliability of on-line visual feedback during acquisition impacts motor learning. Participants performed a right hand pointing task of a repeated sequence with a visual cursor that was either reliable, moderately unreliable, or largely unreliable. Delayed retention tests were administered 24 h later, as well as intermanual transfer tests (performed with the left hand). A visuospatial transfer test was performed with the same targets' sequence (same visuospatial configuration) while a motor transfer test was performed with the visual mirror of the targets' sequence (same motor patterns). Results showed that pointing was slower and long-term learning disrupted in the largely unreliable visual cursor condition, compared with the reliable and moderately unreliable conditions. Also, analysis of transfers revealed classically better performance on visuospatial transfer than on motor transfer for the reliable condition. However, here we first show that such difference disappears when the cursor was moderately or largely unreliable. Interestingly, these results indicated a difference in the type of sequence coding, depending on the reliability of the on-line visual feedback. This recourse to mixed coding opens up interesting perspectives, as it is known to promote better learning of motor sequences.

Indexed as

cue reliabilitymotor sequencesensorimotor codingsensorimotor learningvisual feedback

Identifiers

PMID37901071
PMCPMC10600441

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.