Evidence map›Paper›PMID 38443626›Full record

ReviewNature reviews. Neuroscience2024

Preparatory activity and the expansive null-space.

Mark M Churchland, Krishna V Shenoy

Abstract readReview
In one paragraph

Review in Nature reviews. Neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing 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

71 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Neuromotor modules revealed by direct electrical stimulation of the human primary motor cortex.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  6. Temporally structured motor and auditory representations in covert syllable production.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  7. Temporal Indexing of Motor Memory.bioRxiv : the preprint server for biology · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Premotor cortex uses a compositional neural geometry to plan words.bioRxiv : the preprint server for biology · 2026
    Article
  20. Article

11 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

2 authors.

Mark M ChurchlandDepartment of Neuroscience, Columbia University, New York, NY, USA. mc3502@columbia.edu.ORCID http://orcid.org/0000-0001-9123-6526
Krishna V ShenoyDepartment of Electrical Engineering, Stanford University, Stanford, CA, USA.

Funding

OPTICAL NEUROMODULATION TECHNOLOGY FOR LONG TIMESCALESR01MH086373 · NIMH · STANFORD UNIVERSITY · PI DEISSEROTH, KARL A. · 2010 to 2025
$9.1M
Engaging new cognitive and motor signals to improve communication prosthesesR01DC014034 · NIDCD · STANFORD UNIVERSITY · PI JAIMIE M HENDERSON · 2015 to 2026
$8.2M
Cortical basis of complex motor sequences in humans for neural interfacesU01NS123101 · NINDS · STANFORD UNIVERSITY · PI HENDERSON, JAIMIE M · 2021 to 2025
$6.3M
Single-neuron population dynamics in human speech motor cortex for a speech prosthesisU01DC019430 · NIDCD · STANFORD UNIVERSITY · PI Shaul Druckmann, JAIMIE M HENDERSON · 2021 to 2026
$4.5M
Intuitive, complete neural control of tablet computers for communicationU01DC017844 · NIDCD · BROWN UNIVERSITY · PI HOCHBERG, LEIGH R · 2019 to 2025
$4.3M
An Open Source Simulator for Multi Degree-Of-Freedom Brain-Machine InterfacesR01NS121097 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KAO, JONATHAN CHAU-YAN · 2021 to 2025
$1.9M
Large-scale recordings in Primate Prefrontal Cortex: Mechanisms of Value and AttentionR01NS116623 · NINDS · STANFORD UNIVERSITY · PI MOORE, TIRIN, WALLIS, JONI D · 2023 to 2024
$1.0M
NIDCD NIH HHS R01 DC014034NIDCD NIH HHS U01 DC017844NIDCD NIH HHS U01 DC019430NIMH NIH HHS R01 MH086373NINDS NIH HHS R01 NS116623NINDS NIH HHS R01 NS121097NINDS NIH HHS U01 NS123101
6 · The paper itself

Abstract

The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are 'output-null' factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand.

Indexed as

Motor CortexHumansMovementNeurons

Identifiers

PMID38443626
PMCPMC13271173

What OpenQuestion holds

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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.