The infant brain rapidly entrains to visual statistical regularities during stimulus exposure.
Overview
- Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN2T), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
- ULBabyLab—Center for Research in Cognition and Neurosciences (CRCN), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
- Service of Translational Neuroimaging, Hôpital Erasme, Hôpital Universitaire de Bruxelles (HUB), Université libre de Bruxelles (ULB), Brussels, Belgium
- Department of Pediatric Neurology, Hôpital Erasme and Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Hôpital Universitaire de Bruxelles (HUB), Université libre de Bruxelles (ULB), Brussels, Belgium
Abstract
Statistical learning (SL) has been studied quite extensively in infancy. Still, most evidence relies on post-exposure behavioral tasks whose directionality (familiarity vs. novelty effects) may not be straightforward to predict nor to interpret. In addition, these tasks do not tell anything about the online learning dynamics and may be influenced by memory effects. In this work, we investigated online SL mechanisms by tracking neural entrainment to visual regularities in a group of 4- to 6-month-old infants exposed to a stream of shapes presented at 6 Hz. Shapes were either organized in doublets or presented randomly. Results revealed that entrainment at the doublet frequency of 3 Hz and harmonics varied across conditions and trials. Infants showed greater occipital entrainment to the doublet frequency in the deterministic condition than in the random one, especially over the first trials of exposure. This suggests that the brain can detect visual regularities from early infancy. Further, this sensitivity emerged early over the exposure period and did not show a learning curve when the evolution of the doublet-level signal-to-noise ratio (SNR) was assessed in relation with the base-level SNR over time. Hence, considering its time course and the brain regions involved, neural entrainment at the doublet frequency seems to primarily reflect a bottom-up detection mechanism rather than the full expression of learning. These findings are crucial to better understand how infants extract regularities during stimulus exposure and what neural entrainment can reveal in a visual SL task.
Reproduced under the paper's license (CC BY), from the paper cited above.
Code
The paper links to its data, not to its authors' code: see the Data section.
Tracing map
A tracing map links a paper to the code its authors published: this paper has none, so it has no map.
Data
Datasets cited
Data Availability
The data and material used in the current study are publicly available on the Open Science Framework at: https://
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.
Version 1, 30 September 2026: the first record
Recorded: type, language, journal, volume, pages, dates, 6 authors, 6 keywords, 3 funders, 75 references.
Cite
This paper
Capparini, C., Fourdin, L., Wens, V., Dontaine, P., Aeby, A., & Bertels, J. (2026). The infant brain rapidly entrains to visual statistical regularities during stimulus exposure. Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1161. https://
BibTeX
@article{capparini2026in
author = {Capparini, Chiara and Fourdin, Lauréline and Wens, Vincent and Dontaine, Pauline and Aeby, Alec and Bertels, Julie},
title = {{The infant brain rapidly entrains to visual statistical regularities during stimulus exposure}},
journal = {Imaging neuroscience (Cambridge, Mass.)},
year = {2026},
month = mar,
volume = {4},
pages = {IMAG.a.1161},
publisher = {MIT Press},
issn = {2837-6056},
doi = {10.1162/
url = {https://
pmid = {41847502},
pmcid = {PMC12990820}
}
RIS
TY - JOUR
AU - Capparini, Chiara
AU - Fourdin, Lauréline
AU - Wens, Vincent
AU - Dontaine, Pauline
AU - Aeby, Alec
AU - Bertels, Julie
TI - The infant brain rapidly entrains to visual statistical regularities during stimulus exposure
T2 - Imaging neuroscience (Cambridge, Mass.)
J2 - Imaging Neurosci (Camb)
PY - 2026
DA - 2026/
VL - 4
SP - IMAG.a.1161
SN - 2837-6056
PB - MIT Press
DO - 10.1162/
UR - https://
LA - en
ER -
CSL-JSON
{
"id": "10.1162/
"type": "article-journal",
"title": "The infant brain rapidly entrains to visual statistical regularities during stimulus exposure",
"container-title": "Imaging neuroscience (Cambridge, Mass.)",
"author": [
{
"family": "Capparini",
"given": "Chiara"
},
{
"family": "Fourdin",
"given": "Lauréline"
},
{
"family": "Wens",
"given": "Vincent"
},
{
"family": "Dontaine",
"given": "Pauline"
},
{
"family": "Aeby",
"given": "Alec"
},
{
"family": "Bertels",
"given": "Julie"
}
],
"container-title-short":
"volume": "4",
"page": "IMAG.a.1161",
"DOI": "10.1162/
"PMID": "41847502",
"PMCID": "PMC12990820",
"ISSN": "2837-6056",
"publisher": "MIT Press",
"URL": "https://
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
13
]
]
}
}
Similar papers
The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.
- [1] doi:10.1162/opmi.a.358 [code]
- Tracking Visual Statistical Learning with Steady-State Visual Evoked Potentials: Effects of Exemplar and Category Information.Journal: Open mind : discoveries in cognitive scienceIn common: EEG, 14 references
- [2] doi:10.1002/aur.70312 [code]
- Aberrant Neural Entrainment to Word-Level Speech Patterns in Fragile X Syndrome: Evidence for a Statistical Learning Deficit.Journal: Autism research : official journal of the International Society for Autism ResearchIn common: EEG, 10 references
- [3] doi:10.7554/elife.109901
- Infants at high and low likelihood for autism show different EEG developmental trajectories in speech tracking and statistical learning.Journal: eLifeIn common: EEG, 9 references
- [4] doi:10.1016/j.dcn.2026.101767
- Neural correlates of learning speed reveal developmental differences in memory.Journal: Developmental cognitive neuroscienceIn common: 9 references
- [5] doi:10.1162/imag.a.1305
- Can you &
lt;i& gt;feel& lt;/ i& gt; what I am saying? Speech-based vibrotactile stimulation enhances the cortical tracking of attended speech in a multi-talker background. Journal: Imaging neuroscience (Cambridge, Mass.)In common: 2 references, 2 authors - [6] doi:10.1016/j.isci.2026.116458 [code]
- Neural tracking of prosodic and statistical rhythms jointly supports artificial language learning.Journal: iScienceIn common: 6 references
- [7] doi:10.1111/desc.70116 [code]
- Words and Meters: Neural Evidence for a Connection Between Individual Differences in Statistical Learning and Rhythmic Ability in Infancy.Journal: Developmental scienceIn common: EEG, 5 references
- [8] doi:10.7554/elife.107088 [code]
- Development of auditory and spontaneous movement responses to music over the first postnatal year.Journal: eLifeIn common: EEG, 4 references
- [9] doi:10.1038/s41467-026-75831-x [code]
- Adult-to-infant unidirectional neural coupling mediates selective social learning in infants from the United Kingdom and Singapore.Journal: Nature communicationsIn common: 4 references
- [10] doi:10.1111/desc.70214
- Hemodynamic Responses to Word Forms in Japanese Infant-Directed Vocabulary in 5- and 9-Month-Old Infants: Early Sensitivity to Prosodic Structure and Emergence of Prosodic Representations.Journal: Developmental scienceIn common: 3 references
Contribute
The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.
Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.
Claim this paper
Correct its record
Say what each link of this record is, remove the ones that are not the paper's, add the ones that are missing. The correction becomes a new version of the record, in its Versions section.
Request its removal
To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).
Discussion, reproductions, activity
Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.
Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.
Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.
