Evidence map›Paper›PMID 34676440›Full record

Trial reportPsychopharmacology2021

Effects of methylphenidate on reinforcement learning depend on working memory capacity.

Mojtaba Rostami Kandroodi, Jennifer L Cook, Jennifer C Swart, Monja I Froböse, Dirk E M Geurts, Abdol-Hossein Vahabie, Majid Nili Ahmadabadi, Roshan Cools, Hanneke E M den Ouden

Open access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Psychopharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 6% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
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  10. Article
  11. Dopaminergic Modulation of Dynamic Emotion Perception.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
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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

9 authors at 3 institutions in 3 countries.

Mojtaba Rostami KandroodiSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran. mojtaba.rostami@ut.ac.ir.ORCID http://orcid.org/0000-0002-5508-1421
Jennifer L CookSchool of Psychology, University of Birmingham, Birmingham, United Kingdom.
Jennifer C SwartDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
Monja I FroböseDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
Dirk E M GeurtsDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
Abdol-Hossein VahabieSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Majid Nili AhmadabadiSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Roshan Cools *Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
Hanneke E M den Ouden *Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands. h.denouden@donders.ru.nl.
Radboud University Nijmegen · NLUniversity of Tehran · IRUniversity of Birmingham · GB

Funding

H2020 European Research Council 757583Nederlandse Organisatie voor Wetenschappelijk Onderzoek 240-01-170Nederlandse Organisatie voor Wetenschappelijk Onderzoek 406- 14-028Nederlandse Organisatie voor Wetenschappelijk Onderzoek 451-11-004Nederlandse Organisatie voor Wetenschappelijk Onderzoek 453-14-015ZonMw 92003576
6 · The paper itself

Abstract

rationaleBrain catecholamines have long been implicated in reinforcement learning, exemplified by catecholamine drug and genetic effects on probabilistic reversal learning. However, the mechanisms underlying such effects are unclear. OBJECTIVES AND

methodsHere we investigated effects of an acute catecholamine challenge with methylphenidate (20 mg, oral) on a novel probabilistic reversal learning paradigm in a within-subject, double-blind randomised design. The paradigm was designed to disentangle effects on punishment avoidance from effects on reward perseveration. Given the known large individual variability in methylphenidate's effects, we stratified our effects by working memory capacity and trait impulsivity, putatively modulating the effects of methylphenidate, in a large sample (n = 102) of healthy volunteers.

resultsContrary to our prediction, methylphenidate did not alter performance in the reversal phase of the task. Our key finding is that methylphenidate altered learning of choice-outcome contingencies in a manner that depended on individual variability in working memory span. Specifically, methylphenidate improved performance by adaptively reducing the effective learning rate in participants with higher working memory capacity.

conclusionsThis finding emphasises the important role of working memory in reinforcement learning, as reported in influential recent computational modelling and behavioural work, and highlights the dependence of this interplay on catecholaminergic function.

Indexed as

MethylphenidateHumansMemory, Short-TermReinforcement, PsychologyReversal LearningRewardMethylphenidateCatecholaminesComputational modelling of behaviourDopamineMethylphenidateReversal learningWorking memory

Identifiers

PMID34676440
PMCPMC8629893
OpenAlexW3206618060

What OpenQuestion holds

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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.