Evidence map›Paper›PMID 31850844›Full record

ArticleeLife2019

Catecholaminergic modulation of meta-learning.

Jennifer L Cook, Jennifer C Swart, Monja I Froböse, Andreea O Diaconescu, Dirk Em Geurts, Hanneke Em den Ouden, Roshan Cools

Abstract read
In one paragraph

Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Orbitofrontal noradrenaline supports adaptive learning-rate adjustment in probabilistic reversal learning.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  5. Article
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  7. Article
  8. Learning environment-specific learning rates.PLoS computational biology · 2024
    Article
  9. Article
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  11. Article
  12. Article
  13. Article
  14. A Computational Model of Hopelessness and Active-Escape Bias in Suicidality.Computational psychiatry (Cambridge, Mass.) · 2022
    Article
  15. Meta-control: From psychology to computational neuroscience.Cognitive, affective & behavioral neuroscience · 2021
    Review
  16. 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

7 authors.

Jennifer L CookSchool of Psychology, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0003-4916-8667
Jennifer C SwartDonders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands.ORCID 0000-0003-0989-332X
Monja I FroböseDonders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands.
Andreea O DiaconescuTranslational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.ORCID 0000-0002-3633-9757
Dirk Em GeurtsDonders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands.
Hanneke Em den Ouden *Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands.
Roshan Cools *Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands.

Funding

EPA EP-C-14-005Swiss National Science Foundation PZ00P3_167952ZonMw 92003576
6 · The paper itself

Abstract

The remarkable expedience of human learning is thought to be underpinned by meta-learning, whereby slow accumulative learning processes are rapidly adjusted to the current learning environment. To date, the neurobiological implementation of meta-learning remains unclear. A burgeoning literature argues for an important role for the catecholamines dopamine and noradrenaline in meta-learning. Here, we tested the hypothesis that enhancing catecholamine function modulates the ability to optimise a meta-learning parameter (learning rate) as a function of environmental volatility. 102 participants completed a task which required learning in stable phases, where the probability of reinforcement was constant, and volatile phases, where probabilities changed every 10-30 trials. The catecholamine transporter blocker methylphenidate enhanced participants' ability to adapt learning rate: Under methylphenidate, compared with placebo, participants exhibited higher learning rates in volatile relative to stable phases. Furthermore, this effect was significant only with respect to direct learning based on the participants' own experience, there was no significant effect on inferred-value learning where stimulus values had to be inferred. These data demonstrate a causal link between catecholaminergic modulation and the adjustment of the meta-learning parameter learning rate.

Indexed as

AdolescentAdultDopamineDopamine Uptake InhibitorsFemaleHumansLearningMaleMethylphenidateNorepinephrinePlacebosYoung AdultDopamineDopamine Uptake InhibitorsMethylphenidateNorepinephrinePlacebosdopaminehumanlearning ratemeta-learningmethylphenidateneurosciencenoradrenalinevolatility

Identifiers

PMID31850844
PMCPMC6974360

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Registered trials

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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.