title: Using dynamic field theory to rethink infant habituation.
abstract: Much of what psychologists know about infant perception and cognition is based on habituation, but the process itself is still poorly understood. Here the authors offer a dynamic field model of infant visual habituation, which simulates the known features of habituation, including familiarity and novelty effects, stimulus intensity effects, and age and individual differences. The model is based on a general class of dynamic (time-based) models that integrate environmental input in varying metric dimensions to reach a single decision. Here the authors provide simulated visual input of varying strengths, distances, and durations to 2 coupled and interacting fields. The 1st represents the activation that drives "looking," and the 2nd, the inhibition that leads to "looking away," or habituation. By varying the parameters of the field, the authors simulate the time course of habituation trials and show how these dynamics can lead to different depths of habituation, which then determine how the system dishabituates. The authors use the model to simulate a set of influential experiments by R. Baillargeon (1986, 1987a, 1987b) using the well-known "drawbridge" paradigm. The dynamic field model provides a coherent explanation without invoking infant object knowledge. The authors show that small changes in model parameters can lead to qualitatively different outcomes. Because in typical infant cognition experiments, critical parameters are unknown, effects attributed to conceptual knowledge may be explained by the dynamics of habituation.
authors.affiliation: Institut fur Neuroinformatik, Ruhr-Universität Bochum, Bochum 44780, Germany. Gregor.Schoener@rub.de
authors.forename: Gregor
authors.initials: G
authors.lastname: Schöner
authors.forename: Esther
authors.initials: E
authors.lastname: Thelen
mesh_terms: D001143:Arousal; D001288:Attention; D003210:Concept Formation; D006185:Habituation, Psychophysiologic; D006801:Humans; D007223:Infant; D015233:Models, Statistical; D010364:Pattern Recognition, Visual; D011582:Psychological Theory; D011601:Psychophysics