Evidence map›Paper›PMID 40643705›Full record

ArticleExperimental brain research2025

Intact reinforcement learning in healthy ageing.

Wei-Hsiang Lin, Karin S Pilz, Michael H Herzog, Marina Kunchulia

Abstract read
In one paragraph

Article in Experimental brain research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Wei-Hsiang LinLaboratory of Psychophysics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. weishung1@gmail.com.ORCID http://orcid.org/0000-0001-6083-315X
Karin S PilzCito Institute for Educational Measurement, Arnhem, The Netherlands.
Michael H HerzogLaboratory of Psychophysics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Marina KunchuliaInstitute of Cognitive Neurosciences, Free University of Tbilisi, Tbilisi, Georgia.

Funding

Swiss National Science Foundation 147636
6 · The paper itself

Abstract

What changes with age? Results in reinforcement learning (RL) are mixed. Some studies found deteriorated RL performance in older participants compared to younger controls whereas other studies did not. Daniel et al. (J Neurosci 40(5):1084-1096, 2020. 10.1523/JNEUROSCI.0254-19.2019) suggested that task demand can explain these differences, with less demanding tasks showing no effect of age. Compared to classic, simple RL tasks, we used a navigation task to increase overall complexity. We found that older adults performed less efficiently initially; however, with sufficient trials, they performed as well as young adults. Our results support the idea that ageing does not universally impair performance and that even higher-level cognitive tasks remain largely intact.

Indexed as

AgingHealthy AgingPsychomotor PerformanceReinforcement, PsychologyAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedYoung AdultAgeingBehaviorLearningReinforcement learning

Identifiers

PMID40643705
PMCPMC12254157

What OpenQuestion holds

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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.