Evidence map›Paper›PMID 32729673›Full record

ReviewTopics in cognitive science2020

Non-adjacent Dependency Learning in Humans and Other Animals.

Benjamin Wilson, Michelle Spierings, Andrea Ravignani, Jutta L Mueller, Toben H Mintz, Frank Wijnen, Anne van der Kant, Kenny Smith, Arnaud Rey

Abstract readReview
In one paragraph

Review in Topics in cognitive science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
–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

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Utterance evolution: the road to generative, combinatorial communicators.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
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  11. Embodied cognitive evolution and the limits of convergence.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Review
  12. Review
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  20. Naturalistic Spoken Language Comprehension Is Supported by Alpha and Beta Oscillations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    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

9 authors.

Benjamin WilsonInstitute of Neuroscience, Newcastle University.
Michelle SpieringsDepartment of Cognitive Biology, University of Vienna.
Andrea RavignaniResearch Department, Sealcentre Pieterburen.
Jutta L MuellerInstitute of Cognitive Science, University of Osnabrueck.
Toben H MintzDepartments of Psychology and Linguistics, University of Southern California.
Frank WijnenUtrecht Institute of Linguistics OTS, Utrecht University.
Anne van der KantDepartment of Linguistics, University of Potsdam.
Kenny SmithCentre for Language Evolution, University of Edinburgh.
Arnaud ReyCNRS, Aix-Marseille University.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Learning and processing natural language requires the ability to track syntactic relationships between words and phrases in a sentence, which are often separated by intervening material. These nonadjacent dependencies can be studied using artificial grammar learning paradigms and structured sequence processing tasks. These approaches have been used to demonstrate that human adults, infants and some nonhuman animals are able to detect and learn dependencies between nonadjacent elements within a sequence. However, learning nonadjacent dependencies appears to be more cognitively demanding than detecting dependencies between adjacent elements, and only occurs in certain circumstances. In this review, we discuss different types of nonadjacent dependencies in language and in artificial grammar learning experiments, and how these differences might impact learning. We summarize different types of perceptual cues that facilitate learning, by highlighting the relationship between dependent elements bringing them closer together either physically, attentionally, or perceptually. Finally, we review artificial grammar learning experiments in human adults, infants, and nonhuman animals, and discuss how similarities and differences observed across these groups can provide insights into how language is learned across development and how these language-related abilities might have evolved.

Indexed as

Biological EvolutionHuman DevelopmentLanguageLearningLinguisticsAdultAnimalsHumansInfantArtificial grammarHumanInfantNon-adjacent dependencyNonhuman animalPrimateStructured sequence processing

Identifiers

PMID32729673
PMCPMC7496455

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.