A Connectionist Account of Perceptual Category-Learning in Infants 1

This paper presents a connectionist model of correlation-based categorization by 10-month-old infants (Younger, 1985). Simple autoencoder networks were exposed to the same stimuli used to test 10-month-olds. Both infants and networks used co-variation information (when available) to segregate items into separate categories. The model provides a mechanistic account of category learning within a test session. It shows how distinct categories are developed and demonstrates how categorization arises as the product of an inextricable interaction between the subject (the infant) and the environment (the stimuli).