Evidence map›Paper›PMID 33782622›Full record

ArticleNature neuroscience2021

Learning is shaped by abrupt changes in neural engagement.

Jay A Hennig, Emily R Oby, Matthew D Golub, Lindsay A Bahureksa, Patrick T Sadtler, Kristin M Quick, Stephen I Ryu, Elizabeth C Tyler-Kabara, Aaron P Batista, Steven M Chase and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing 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

39 citing papers in PubMed.

  1. Article
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  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. A neural manifold view of the brain.Nature neuroscience · 2025
    Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Nonlinear manifolds underlie neural population activity during behaviour.bioRxiv : the preprint server for biology · 2024
    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

11 authors.

Jay A HennigNeuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA. jhennig@andrew.cmu.edu.ORCID http://orcid.org/0000-0001-7982-8553
Emily R ObyCenter for the Neural Basis of Cognition, Pittsburgh, PA, USA.
Matthew D GolubCenter for the Neural Basis of Cognition, Pittsburgh, PA, USA.
Lindsay A BahureksaCenter for the Neural Basis of Cognition, Pittsburgh, PA, USA.
Patrick T SadtlerCenter for the Neural Basis of Cognition, Pittsburgh, PA, USA.
Kristin M QuickCenter for the Neural Basis of Cognition, Pittsburgh, PA, USA.
Stephen I RyuDepartment of Electrical Engineering, Stanford University, Stanford, CA, USA.
Elizabeth C Tyler-KabaraCenter for the Neural Basis of Cognition, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0003-3286-1094
Aaron P Batista *Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0002-1719-0061
Steven M Chase *Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0003-4450-6313
Byron M Yu *Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0003-2252-6938

Funding

Shaping Neural Population Dynamics to Facilitate LearningR01HD071686 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BATISTA, AARON PAUL, CHASE, STEVEN M · 2011 to 2021
$3.7M
Interrogating and Perturbing Neural DynamicsR01NS105318 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Aaron Paul Batista, Steven M Chase · 2017 to 2026
$2.3M
CRCNS: Modulating Neural Population Interactions between Cortical AreasR01MH118929 · NIMH · CARNEGIE-MELLON UNIVERSITY · PI SMITH, MATTHEW A, YU, BYRON M. · 2018 to 2022
$1.7M
Neuronal population dynamics within and across cortical areasR01EB026953 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DOIRON, BRENT D., SMITH, MATTHEW A · 2018 to 2020
$1.0M
NIBIB NIH HHS R01 EB026953NICHD NIH HHS R01 HD071686NIMH NIH HHS R01 MH118929NINDS NIH HHS R01 NS105318
6 · The paper itself

Abstract

Internal states such as arousal, attention and motivation modulate brain-wide neural activity, but how these processes interact with learning is not well understood. During learning, the brain modifies its neural activity to improve behavior. How do internal states affect this process? Using a brain-computer interface learning paradigm in monkeys, we identified large, abrupt fluctuations in neural population activity in motor cortex indicative of arousal-like internal state changes, which we term 'neural engagement.' In a brain-computer interface, the causal relationship between neural activity and behavior is known, allowing us to understand how neural engagement impacted behavioral performance for different task goals. We observed stereotyped changes in neural engagement that occurred regardless of how they impacted performance. This allowed us to predict how quickly different task goals were learned. These results suggest that changes in internal states, even those seemingly unrelated to goal-seeking behavior, can systematically influence how behavior improves with learning.

Indexed as

Brain-Computer InterfacesAction PotentialsAnimalsAttentionLearningMacaca mulattaMaleMotor CortexNeurons

Identifiers

PMID33782622

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.