Prior expectations shape neural responses in sensory regions of the brain, consistent with a Bayesian predictive coding account of perception. Yet, it remains unclear whether such a mechanism is already functional during early stages of development. To address this issue, we study how the infant brain responds to prediction violations using a cross-modal cueing paradigm. We record electroencephalographic responses to expected and unexpected visual events preceded by auditory cues in 12-month-old infants. We find an increased response for unexpected events. However, this effect of prediction error is only observed during late processing stages associated with conscious access mechanisms. In contrast, early perceptual components reveal an amplification of neural responses for predicted relative to surprising events, suggesting that selective attention enhances perceptual processing for expected events. Taken together, these results demonstrate that cross-modal statistical regularities are used to generate predictions that differentially influence early and late neural responses in infants.

Executive functions (EFs) play a key role in cognitive and socioemotional development. Factor analyses have revealed an age dependent structure of EFs spanning from a single common factor in early childhood to three factors in adults corresponding to inhibitory control (IC), switching and updating. IC performances change not only with age but also with cognitive training. Surprisingly, few studies have investigated training-related changes in EFs structure. We used the regularized partial correlation network model to analyze EFs structure in 137 typically developing children (9–10 years) and adolescents (15–17 years) before and after computerized cognitive training. Network models (NMs) —a graph theory-based approach allowing us to describe the structure of complex systems— can provide a priori free insight into EFs structures. We tested the hypothesis that training-related changes may mimic developmental-related changes. Quantitative and qualitative changes were detected in the EFs network structure with age and also with cognitive training. Of note, the EFs network structure in children after training was more similar to adolescents’ networks than before training. This study provided the first evidence of structural changes in EFs that are age and training-dependent and supports the hypothesis that training could accelerate the development of some structural aspects of EFs. Due to the sample size, these findings should be considered preliminary before replication in independent larger samples.