Evidence map›Paper›PMID 32167407›Full record

ArticlePerspectives on psychological science : a journal of the Association for Psychological Science2020

Making Sense of the World: Infant Learning From a Predictive Processing Perspective.

Moritz Köster, Ezgi Kayhan, Miriam Langeloh, Stefanie Hoehl

Abstract read
In one paragraph

Article in Perspectives on psychological science : a journal of the Association for Psychological Science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

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  11. Body as First Teacher: The Role of Rhythmic Visceral Dynamics in Early Cognitive Development.Perspectives on psychological science : a journal of the Association for Psychological Science · 2025
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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

4 authors.

Moritz KösterMax Planck Institute for Human Cognitive and Brain Sciences.ORCID 0000-0002-9951-7741
Ezgi KayhanMax Planck Institute for Human Cognitive and Brain Sciences.ORCID 0000-0002-1725-220X
Miriam LangelohMax Planck Institute for Human Cognitive and Brain Sciences.ORCID 0000-0003-3250-8602
Stefanie HoehlDepartment of Developmental and Educational Psychology, Faculty of Psychology, University of Vienna.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.

Indexed as

Psychology, ChildSocial AdjustmentSocial LearningComprehensionFemaleHumansInfantInfant, NewbornMaleProprioceptionSocial ChangeSocial CognitionSocial EnvironmentSocial Skillscognitioninfant developmentneuroscienceperceptionsocial cognition

Identifiers

PMID32167407
PMCPMC7243078

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.