Résumé : Introduction: Visual statistical learning allows preverbal infants to organise visual stimulation in a coherent representation. Thus far, early visual statistical learning skills have been measured with post-exposure behavioural tasks that focus on the outcome of learning. These tasks may lead to ambiguous interpretations since there is no clear consensus about the directionality of the expected learning outcome in infancy (i.e., novelty or familiarity effect). Electrophysiological measures can be acquired while learning occurs and can shed light onto the temporal course of learning.Methods: In this exploratory study, we propose an EEG frequency-tagging approach to study 4- to 6-month-old infants’ and adults’ neural entrainment in response to visual regularities. All participants were presented with 20-second sequences including a continuous stream of 8 colourful shapes presented at 6 Hz. Participants were randomly assigned to one of three conditions: a) the standard doublet condition, in which shapes were organised in doublets, b) the control doublet condition, in which only the first element of the pair followed a rule, and c) the single condition, in which individual shapes were randomly presented.Results: Preliminary results reveal that both infants and adults showed neural entrainment at the base frequency of visual stimulation (6 Hz and its harmonics) that did not differ across experimental conditions. This confirms that participants were paying attention to the visual stream of stimuli in all conditions. On the other side, activity at the doublet presentation frequency (3 Hz and its harmonics) varied across conditions. Infants assigned to the doublet conditions showed greater responses at the doublet harmonics, especially at 9 Hz, compared to the single condition. This was similar for adults, although entrainment mechanisms were evident for more harmonics than infants.Conclusion: Overall, these preliminary results suggest that visual regularities in a stream of shapes can be detected very early on. These findings will be crucial to better understand learning mechanisms during stimulus exposure.