Evidence map›Paper›PMID 40348889›Full record

ArticleScientific reports2025

Fast implicit and slow explicit learning of temporal context.

Luca Mangili, Charlotte Wissing, Devika Narain

Abstract read
In one paragraph

Article in Scientific reports, 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

3 authors.

Luca Mangili *Dept. of Neuroscience, Erasmus University Medical Center, Rotterdam, The Netherlands.
Charlotte Wissing *Dept. of Neuroscience, Erasmus University Medical Center, Rotterdam, The Netherlands.
Devika NarainDept. of Neuroscience, Erasmus University Medical Center, Rotterdam, The Netherlands. d.narain@erasmusmc.nl.

Funding

AINED/ Nationaal Groeifonds NGF.1609.241.021Nederlandse Organisatie voor Wetenschappelijk Onderzoek Vidi-VI.193.076
6 · The paper itself

Abstract

One is seldom aware of the anticipatory and preemptive feats that the eyeblink system achieves in daily life but it frequently protects the eye from projectiles gone awry and insects on apparent collision courses. This poor awareness is why predictive eyeblinks are considered a form of implicit learning. In motor neuroscience, implicit learning is considered to be slow and, eyeblink conditioning, in particular, is believed to be a rigid and inflexible cerebellar-dependent behavior. In cognitive neuroscience, however, implicit and automatic processes are thought to be rapidly acquired. Here we show that the eyeblink system is, in fact, capable of remarkable cognitive flexibility and can learn on more rapid timescales than previously expected. In a task where we yoked contextual learning of predictive eyeblinks and manual responses in humans, well-timed eyeblink responses flexibly adjusted to external context on each trial. The temporal precision of the predictive eyeblinks exceeded that of manual response times. Learning of the well-timed eyeblink responses was also more rapid than that for the manual response times. This pattern persevered with the use of a cognitive strategy, which seemed to accelerate both types of learning. These results suggest that behaviors associated with the cerebellar cortex that were previously believed to be inflexible and largely implicit, can demonstrate rapid and precise context-dependent temporal control.

Indexed as

BlinkingLearningAdultCognitionConditioning, EyelidFemaleHumansMaleReaction TimeYoung Adult

Identifiers

PMID40348889
PMCPMC12065811

What OpenQuestion holds

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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.