Evidence map›Paper›PMID 35169072›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Visual object categorization in infancy.

Céline Spriet, Etienne Abassi, Jean-Rémy Hochmann, Liuba Papeo

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
4.6field-weighted citation impact, top 4% 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

24 citing papers in PubMed, 45 citations in OpenAlex.

  1. Article
  2. Deep learning in fetal, infant, and toddler neuroimaging research.Developmental cognitive neuroscience · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Comparing color qualia structures through a similarity task in young children versus adults.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Development of Higher-Level Vision: A Network Perspective.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Review
  12. Helpless infants are learning a foundation model.Trends in cognitive sciences · 2024
    Review
  13. Early-emerging combinatorial thought: Human infants flexibly combine kind and quantity concepts.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  14. Article
  15. Infants' understanding of the causal power of agents and tools.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  16. Article
  17. Article
  18. Article
  19. Category Trumps Shape as an Organizational Principle of Object Space in the Human Occipitotemporal Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  20. Review
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 at 1 institution in 1 country.

Céline SprietInstitute of Cognitive Sciences Marc Jeannerod, UMR5229, CNRS, University Claude Bernard Lyon1, Bron 69675, France.ORCID 0000-0002-9740-4970
Etienne AbassiInstitute of Cognitive Sciences Marc Jeannerod, UMR5229, CNRS, University Claude Bernard Lyon1, Bron 69675, France.ORCID 0000-0003-4235-0001
Jean-Rémy HochmannInstitute of Cognitive Sciences Marc Jeannerod, UMR5229, CNRS, University Claude Bernard Lyon1, Bron 69675, France.ORCID 0000-0002-4613-1378
Liuba PapeoInstitute of Cognitive Sciences Marc Jeannerod, UMR5229, CNRS, University Claude Bernard Lyon1, Bron 69675, France liuba.papeo@isc.cnrs.fr.ORCID 0000-0003-3056-8679
Université Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans make sense of the world by organizing things into categories. When and how does this process begin? We investigated whether real-world object categories that spontaneously emerge in the first months of life match categorical representations of objects in the human visual cortex. Using eye tracking, we measured the differential looking time of 4-, 10-, and 19-mo-olds as they looked at pairs of pictures belonging to eight animate or inanimate categories (human/nonhuman, faces/bodies, real-world size big/small, natural/artificial). Taking infants' looking times as a measure of similarity, for each age group, we defined a representational space where each object was defined in relation to others of the same or of a different category. This space was compared with hypothesis-based and functional MRI-based models of visual object categorization in the adults' visual cortex. Analyses across different age groups showed that, as infants grow older, their looking behavior matches neural representations in ever-larger portions of the adult visual cortex, suggesting progressive recruitment and integration of more and more feature spaces distributed over the visual cortex. Moreover, the results characterize infants' visual categorization as an incremental process with two milestones. Between 4 and 10 mo, visual exploration guided by saliency gives way to an organization according to the animate-inanimate distinction. Between 10 and 19 mo, a category spurt leads toward a mature organization. We propose that these changes underlie the coupling between seeing and thinking in the developing mind.

Indexed as

AdultAge FactorsBrain MappingCognitionEye-Tracking TechnologyFemaleFixation, OcularHumansInfantMagnetic Resonance ImagingMalePattern Recognition, VisualPhotic StimulationThinkingVision, OcularVisual Cortexcategorizationcognitive developmentfMRIlooking timesvisual system

Identifiers

PMID35169072
PMCPMC8872728
OpenAlexW4213076464

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.