Evidence map›Paper›PMID 40541963›Full record

ArticleScientific reports2025

A novel approach to exploring infant gaze patterns with AI-manipulated videos.

Charlotte Viktorsson, Tobias Lundman, Kim Astor

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Charlotte ViktorssonDevelopment and Neurodiversity Lab, Department of Psychology, Uppsala University, Uppsala, Sweden. charlotte.viktorsson@psyk.uu.se.
Tobias LundmanDevelopment and Neurodiversity Lab, Department of Psychology, Uppsala University, Uppsala, Sweden.
Kim AstorUppsala Child and Baby Lab, Department of Psychology, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Eye tracking is a widely used tool to study infant development, but creating diverse stimuli while maintaining high control over confounding variables can be challenging. In this proof-of-concept study, we examined an innovative way to generate ecologically valid stimuli using AI technology, in order to create videos that can be used in culturally diverse settings. Using the eye-mouth-index (EMI), a commonly used paradigm in infant eye tracking, we examined the consistency of eye tracking measures across original videos and two types of AI-manipulated videos in a sample of 46 infants aged 12-14 months. We found a very strong correlation of the EMI across original and AI videos (r = 0.873-0.874), and there were no statistically significant differences between mean EMI in the original and AI conditions. Additionally, we created culturally diverse videos to measure gaze following, and found that children followed the gaze of the people in the AI-manipulated videos in an expected manner. In conclusion, AI technology provides promising tools to create ecologically valid and culturally diverse stimuli, that can be used to conduct studies in a wide range of settings and to examine the generalizability of earlier findings in the field of developmental psychology.

Indexed as

Artificial IntelligenceChild DevelopmentEye-Tracking TechnologyFixation, OcularEye MovementsFemaleHumansInfantMaleVideo RecordingAIEye-mouth-indexEye trackingGaze followingInfantsSocial attention

Identifiers

PMID40541963
PMCPMC12181369

What OpenQuestion holds

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LicenceCC BY
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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.