Evidence map›Paper›PMID 31792198›Full record

ReviewNature communications2019

Hierarchical motor control in mammals and machines.

Josh Merel, Matthew Botvinick, Greg Wayne

Abstract readReview
In one paragraph

Review in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers.

0numbers the graph read from it
0cells of the map it votes in
90citing 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

90 citing papers in PubMed.

  1. Article
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  11. Theoretical neuroscience has room to grow.Nature reviews. Neuroscience · 2025
    Article
  12. Article
  13. Action-type mapping principles extend beyond evolutionarily conserved actions, even in people born without hands.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  14. Article
  15. Review
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  20. Explaining human motor coordination via the synergy expansion hypothesis.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article

30 more citing papers are in PubMed but not listed here.

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.

Josh MerelDeepMind, London, UK. jsmerel@google.com.
Matthew BotvinickDeepMind, London, UK.ORCID http://orcid.org/0000-0001-7758-6896
Greg WayneDeepMind, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in artificial intelligence are stimulating interest in neuroscience. However, most attention is given to discrete tasks with simple action spaces, such as board games and classic video games. Less discussed in neuroscience are parallel advances in "synthetic motor control". While motor neuroscience has recently focused on optimization of single, simple movements, AI has progressed to the generation of rich, diverse motor behaviors across multiple tasks, at humanoid scale. It is becoming clear that specific, well-motivated hierarchical design elements repeatedly arise when engineering these flexible control systems. We review these core principles of hierarchical control, relate them to hierarchy in the nervous system, and highlight research themes that we anticipate will be critical in solving challenges at this disciplinary intersection.

Indexed as

Deep LearningAnimalsArtificial IntelligenceHumansMammalsMotor ActivityNeurosciences

Identifiers

PMID31792198
PMCPMC6889345

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.