Evidence map›Paper›PMID 27846219›Full record

ArticlePLoS biology2016

Pharmacological Fingerprints of Contextual Uncertainty.

Louise Marshall, Christoph Mathys, Diane Ruge, Archy O de Berker, Peter Dayan, Klaas E Stephan, Sven Bestmann

Abstract read
In one paragraph

Article in PLoS biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing 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

74 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. A Reliable Effect of Alexithymia, but Not Autism, on Placebo Hypoalgesia.Autism : the international journal of research and practice · 2026
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. The active construction of past episodes.Translational neuroscience · 2026
    Article
  15. Article
  16. Review
  17. Article
  18. Active information sampling in health and disease.Neuroscience and biobehavioral reviews · 2025
    Review
  19. Article
  20. Article

14 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

7 authors.

Louise MarshallSobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, United Kingdom.ORCID http://orcid.org/0000-0002-7885-591X
Christoph MathysWellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.
Diane RugeSobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, United Kingdom.
Archy O de BerkerSobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, United Kingdom.ORCID http://orcid.org/0000-0002-3460-7172
Peter DayanGatsby Computational Neuroscience Unit, University College London, London, United Kingdom.ORCID http://orcid.org/0000-0003-3476-1839
Klaas E StephanWellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.
Sven BestmannSobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, United Kingdom.ORCID http://orcid.org/0000-0002-6867-9545

Funding

Wellcome Trust
6 · The paper itself

Abstract

Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses.

Indexed as

UncertaintyAdultBiogenic MonoaminesBrainHumansLikelihood FunctionsModels, TheoreticalBiogenic Monoamines

Identifiers

PMID27846219
PMCPMC5113004

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.