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Babylearn SIGNED

Neural mechanisms of learning in the infant brain : from Statistics to Rules and Symbols

Total Cost €


EC-Contrib. €






 Babylearn project word cloud

Explore the words cloud of the Babylearn project. It provides you a very rough idea of what is the project "Babylearn" about.

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Project "Babylearn" data sheet

The following table provides information about the project.


Organization address
address: RUE LEBLANC 25
city: PARIS 15
postcode: 75015

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Total cost 2˙554˙923 €
 EC max contribution 2˙554˙923 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-AdG
 Funding Scheme ERC-ADG
 Starting year 2016
 Duration (year-month-day) from 2016-09-01   to  2021-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Infant is the most powerful learner: He learns in a few months to master language, complex social interactions, etc. Powerful statistical algorithms, simultaneously acting at the different levels of functional hierarchies have been proposed to explain learning. I propose here that two other elements are crucial. The first is the particular human cerebral architecture that constrains statistical computations. The second is the human’s ability to access a rich symbolic system. I have planned 6 work packages using the complementary information offered by non-invasive brain-imaging techniques (EEG, MRI and optical topography) to understand the neural bases of infant statistical computations and symbolic competence from 6 months of gestation up until the end of the first year of life. WP1 studies from which preterm age, statistical inferences can be demonstrated using hierarchical auditory oddball paradigms. WP2 investigates the consequences of a different pre-term environment (in-utero versus ex-utero) on the early statistical computations in the visual and auditory domains and their consequences on the ongoing brain activity along the first year of life. WP3 explores the neural bases of how infants infer word meaning and word category, and in particular the role of the left perisylvian areas and of their particular connectivity. WP4 questions infant symbolic competency. I propose several criteria (generalization, bidirectionality, use of algebraic rules and of logical operations) tested in successive experiments to clarify infant symbolic abilities during the first semester of life. WP5-6 are transversal to WP1-4: WP5 uses MRI to obtain accurate functional localization and maturational markers correlated with functional results. In WP6, we develop new tools to combine and analyse multimodal brain images. With this proposal, I hope to clarify the specificities of a neural functional architecture that are critical for human learning from the onset of cortical circuits.


year authors and title journal last update
List of publications.
2020 Parvaneh Adibpour, Jessica Lebenberg, Claire Kabdebon, Ghislaine Dehaene-Lambertz, Jessica Dubois
Anatomo-functional correlates of auditory development in infancy
published pages: 100752, ISSN: 1878-9293, DOI: 10.1016/j.dcn.2019.100752
Developmental Cognitive Neuroscience 42 2020-04-24
2018 Parvaneh Adibpour, Jessica Dubois, Marie-Laure Moutard, Ghislaine Dehaene-Lambertz
Early asymmetric inter-hemispheric transfer in the auditory network: insights from infants with corpus callosum agenesis
published pages: 2893-2905, ISSN: 1863-2653, DOI: 10.1007/s00429-018-1667-4
Brain Structure and Function 223/6 2019-06-13
2017 Ghislaine Dehaene-Lambertz
The human infant brain: A neural architecture able to learn language
published pages: 48-55, ISSN: 1069-9384, DOI: 10.3758/s13423-016-1156-9
Psychonomic Bulletin & Review 24/1 2019-06-13
2019 Claire Kabdebon, Ghislaine Dehaene-Lambertz
Symbolic labeling in 5-month-old human infants
published pages: 5805-5810, ISSN: 0027-8424, DOI: 10.1073/pnas.1809144116
Proceedings of the National Academy of Sciences 116/12 2019-04-18

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The information about "BABYLEARN" are provided by the European Opendata Portal: CORDIS opendata.

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