Evidence map›Paper›PMID 35320276›Full record

ArticlePLoS computational biology2022

Interactions between sensory prediction error and task error during implicit motor learning.

Jonathan S Tsay, Adrian M Haith, Richard B Ivry, Hyosub E Kim

Abstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Trial
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  7. Predictive interception across speed profiles.Frontiers in neural circuits · 2026
    Article
  8. Article
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  10. Uncovering the Role of the Human Hippocampus in Procedural Motor Learning: Insights from Implicit Sensorimotor Adaptation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
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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.

Jonathan S TsayDepartment of Psychology, University of California, Berkeley, California, United States of America.ORCID 0000-0002-3992-9023
Adrian M HaithDepartment of Neurology, Johns Hopkins University, Baltimore, Maryland, United States of America.ORCID 0000-0002-5658-8654
Richard B IvryDepartment of Psychology, University of California, Berkeley, California, United States of America.ORCID 0000-0003-4728-5130
Hyosub E KimDepartment of Physical Therapy, University of Delaware, Newark, Delaware, United States of America.ORCID 0000-0003-0109-593X

Funding

MULTICENTER CAREER DEVELOPMENT PROGRAM FOR PHYSICAL AND OCCUPATIONAL THERAPYK12HD055931 · NICHD · WASHINGTON UNIVERSITY · PI HAYES, MARCIE HARRIS · 2007 to 2021
$12.7M
Human Cerebellar Function in Multiple Task DomainsR35NS116883 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI RICHARD IVRY · 2020 to 2026
$5.3M
The role of the cerebellum in speechR01DC017091 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI John Francis Houde, RICHARD IVRY · 2019 to 2026
$4.5M
Neural Mechanisms Supporting Implicit and Explicit Sensorimotor LearningF31NS120448 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI TSAY, JONATHAN · 2022 to 2023
$62k
NICHD NIH HHS K12 HD055931NIDCD NIH HHS R01 DC017091NINDS NIH HHS F31 NS120448NINDS NIH HHS R35 NS116883
6 · The paper itself

Abstract

Implicit motor recalibration allows us to flexibly move in novel and changing environments. Conventionally, implicit recalibration is thought to be driven by errors in predicting the sensory outcome of movement (i.e., sensory prediction errors). However, recent studies have shown that implicit recalibration is also influenced by errors in achieving the movement goal (i.e., task errors). Exactly how sensory prediction errors and task errors interact to drive implicit recalibration and, in particular, whether task errors alone might be sufficient to drive implicit recalibration remain unknown. To test this, we induced task errors in the absence of sensory prediction errors by displacing the target mid-movement. We found that task errors alone failed to induce implicit recalibration. In additional experiments, we simultaneously varied the size of sensory prediction errors and task errors. We found that implicit recalibration driven by sensory prediction errors could be continuously modulated by task errors, revealing an unappreciated dependency between these two sources of error. Moreover, implicit recalibration was attenuated when the target was simply flickered in its original location, even though this manipulation did not affect task error - an effect likely attributed to attention being directed away from the feedback cursor. Taken as a whole, the results were accounted for by a computational model in which sensory prediction errors and task errors, modulated by attention, interact to determine the extent of implicit recalibration.

Indexed as

MovementPsychomotor PerformanceAdaptation, PhysiologicalFeedback, SensoryMotivationVisual Perception

Identifiers

PMID35320276
PMCPMC8979451

What OpenQuestion holds

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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.