Infant habituation: a review of current computational models and a new proposal

Habituation paradigms have become popular tools to investigate early cognitive abilities in infants. However, the level of interpretation that should be used in explaining habituation phenomena has been the object of much debate in recent years. Several neural network models of infant habituation phenomena have been proposed, and some of these are explicitly aimed at this issue. We argue that none of the previous models offer either a necessary or sufficient account of infant habituation. We look at the constraints from the behavioural and neural sciences that bound interpretations of habituation and familiarisation tasks. The main features identified at the neural level are selective inhibition in the hippocampal system, and a dynamic interaction between these subcortical processes and cortical regions. At the behavioural level, proper models should capture the temporal unfolding of responses, their exponential decrease, a shift from familiarity preference to novelty preference, the habituation of novelty preference, and the ability to discriminate between habituated stimuli. A neural network model built around these constraints is presented