Richard Ν. Aslin

The paper provides code and a pipeline for time-resolved multivariate pattern analysis of infant EEG data using linear SVM classification, showing reliable above-chance accuracy in both infants and adults.

This study decodes visual representations from EEG data of infants and adults, finding that infants' neural representations are not linearly separable across visual domains and show developmental reorganization.

This study shows 6-7-year-olds can combine sensory cues with learned regularities statistically efficiently, but task complexity affects their performance more than adults.