Evidence map›Paper›PMID 38753411›Full record

ArticleJournal of experimental psychology. Human perception and performance2024

"Leap before you look": Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation.

Tejas Savalia, Rosemary A Cowell, David E Huber

Abstract read
In one paragraph

Article in Journal of experimental psychology. Human perception and performance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tejas SavaliaDepartment of Psychological and Brain Sciences, University of Massachusetts Amherst.ORCID 0000-0002-9886-2738
Rosemary A CowellInstitute of Cognitive Science, University of Colorado Boulder.
David E HuberDepartment of Psychology and Neuroscience, University of Colorado Boulder.

Funding

Using fMRI to Measure the Neural-level Signals Underlying Population-level ResponsesRF1MH114277 · NIMH · UNIVERSITY OF MASSACHUSETTS AMHERST · PI COWELL, ROSEMARY ALICE, HUBER, DAVID ERNEST · 2017 to 2017
$2.4M
NIH HHSNIMH NIH HHS RF1 MH114277
6 · The paper itself

Abstract

When learning a novel visuomotor mapping (e.g., mirror writing), accuracy can improve quickly through explicit, knowledge-based learning (e.g., aim left to go right), but after practice, implicit or procedural learning takes over, producing fast, natural movements. This procedural learning occurs automatically, whereas it has recently been found that knowledge-based learning can be suppressed by the gradual introduction of the novel mapping when participants must make fast movements and visuomotor perturbations are small (e.g., 30° rotations). We explored the range of task instructions, perturbation parameters, and feedback that preclude or encourage this suppression. Using a reaching task with a rotation between screen position and movement direction, we found that knowledge-based learning could be suppressed even for an extreme 90° rotation, but only if it was introduced gradually and only under instructions to move quickly. If the rotation was introduced abruptly or if instructions emphasized accuracy over speed, knowledge-based learning occurred. A second experiment indicated that knowledge-based learning always occurred in the absence of continuous motion feedback, evidenced by the time course of learning, the aftereffects of learning when the rotation was abruptly removed, and the outcome of formal model comparison between a dual-state (procedural and knowledge-based) versus a single-state (procedural only) learning model of the data. A third experiment replicated the findings and verified that the knowledge-based component of the dual-state model corresponded to explicit aiming, whereas the procedural component was slow to unlearn. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Indexed as

LearningPsychomotor PerformanceAdultFemaleHumansMaleMotor ActivityVisual PerceptionYoung Adult

Identifiers

PMID38753411
PMCPMC11412309

What OpenQuestion holds

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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.