Evidence map›Paper›PMID 34486520›Full record

ArticleeLife2021

Motor planning under uncertainty.

Laith Alhussein, Maurice A Smith

Abstract read
In one paragraph

Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Online Movements Reflect Ongoing Deliberation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  8. Article
  9. Differential Beta and Gamma Activity Modulation during Unimanual and Bimanual Motor Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  10. Article
  11. Sequential Effects in Reaching Reveal Efficient Coding in Motor Planning.bioRxiv : the preprint server for biology · 2024
    Article
  12. Review
  13. The cerebellum acts as the analog to the medial temporal lobe for sensorimotor memory.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

2 authors.

Laith AlhusseinJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States.ORCID 0000-0003-0411-1683
Maurice A SmithJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States.ORCID 0000-0003-4214-1277

Funding

Dissociating Intrinsic and Extrinsic Motor Learning in Alzheimer's DiseaseR01AG041878 · NIA · HARVARD UNIVERSITY · PI SMITH, MAURICE A · 2012 to 2016
$1.7M
Specifying the constraints on cerebellar dependent sensorimotor adaptationR01NS105839 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI IVRY, RICHARD · 2018 to 2019
$709k
NIA NIH HHS R01 AG041878NINDS NIH HHS R01 NS105839
6 · The paper itself

Abstract

Actions often require the selection of a specific goal amongst a range of possibilities, like when a softball player must precisely position her glove to field a fast-approaching ground ball. Previous studies have suggested that during goal uncertainty the brain prepares for all potential goals in parallel and averages the corresponding motor plans to command an intermediate movement that is progressively refined as additional information becomes available. Although intermediate movements are widely observed, they could instead reflect a neural decision about the single best action choice given the uncertainty present. Here we systematically dissociate these possibilities using novel experimental manipulations and find that when confronted with uncertainty, humans generate a motor plan that optimizes task performance rather than averaging potential motor plans. In addition to accurate predictions of population-averaged changes in motor output, a novel computational model based on this performance-optimization theory accounted for a majority of the variance in individual differences between participants. Our findings resolve a long-standing question about how the brain selects an action to execute during goal uncertainty, providing fundamental insight into motor planning in the nervous system.

Indexed as

UncertaintyAdolescentAdultBrainDecision MakingFemaleHumansMaleModels, BiologicalMovementYoung Adultdecision makingforce-fieldhumanmovement planningneurosciencereachingsafety marginuncertainty

Identifiers

PMID34486520
PMCPMC8421070

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.