Evidence map›Paper›PMID 26719992›Full record

ReviewCurrent opinion in neurobiology2016

Computations underlying sensorimotor learning.

Daniel M Wolpert, J Randall Flanagan

Abstract readReview
In one paragraph

Review in Current opinion in neurobiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 1 pooled it
–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

45 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Predictive interception across speed profiles.Frontiers in neural circuits · 2026
    Article
  7. The multisensory control of sequential actions.Experimental brain research · 2024
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Identifying Transfer Learning in the Reshaping of Inductive Biases.Open mind : discoveries in cognitive science · 2024
    Article
  14. Review
  15. Article
  16. Flexible intentions: An Active Inference theory.Frontiers in computational neuroscience · 2023
    Article
  17. Article
  18. Hypothalamic Control of Forelimb Motor Adaptation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Article
  19. Review
  20. Review
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.

Daniel M WolpertDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK. Electronic address: wolpert@eng.cam.ac.uk.
J Randall FlanaganDepartment of Psychology and Centre for Neuroscience Studies, Queen's University, Kingston, ON K7L 3N6, Canada.

Funding

CIHRWellcome Trust
6 · The paper itself

Abstract

The study of sensorimotor learning has a long history. With the advent of innovative techniques for studying learning at the behavioral and computational levels new insights have been gained in recent years into how the sensorimotor system acquires, retains, represents, retrieves and forgets sensorimotor tasks. In this review we highlight recent advances in the field of sensorimotor learning from a computational perspective. We focus on studies in which computational models are used to elucidate basic mechanisms underlying adaptation and skill acquisition in human behavior.

Indexed as

Models, BiologicalAdaptation, PhysiologicalHumansLearning

Identifiers

PMID26719992
PMCPMC6103431

What OpenQuestion holds

Textmetadata
LicenceTDM
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.