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Poster Session C: Friday, August 15, 2:00 – 5:00 pm, de Brug & E‑Hall

Sensitivity to network structures via associate learning in sleeping neonates

Claire Njoo-Deplante¹, Lucas Benjamin², Marie Palu, Ghislaine Dehaene-lambertz; ¹Université Paris Cité, ²Ecole Normale Supérieure – PSL

Presenter: Claire Njoo-Deplante

Extracting structural patterns is essential for all humans to make sense of the world - particularly so for infants, who must decipher language to acquire it. While it has been shown that infants can learn both low-level statistical regularities and higher-order structures, the neural mechanisms supporting these learning processes remain underexplored. A recent study in adults suggests that a low-level associative learning mechanism may underlie both types of learning. In this study, we investigated whether a similar mechanism is present in neonates by examining their ability to encode network structures in auditory sequences during sleep. We passively presented them with sequences of tones organised in a community network structure while recording their brain activity using electroencephalography (EEG). The preliminary results of our pilot analysis using multivariate pattern analysis (MVPA) reveal that we can successfully decode the network structure at the individual level. Complementary analysis should confirm these findings at the group level. Beyond deepening our understanding of neonates’ sensitivity to regularities, this study sheds light on the neural mechanisms behind complex structure learning, potentially bridging learning mechanisms across different structural levels within a unified theoretical framework.

Topic Area: Memory, Spatial Cognition & Skill Learning

Extended Abstract: Full Text PDF