Comparing elemental and configural associative theories in human causal learning: A case for attention.

Abstract

In two causal learning experiments with human participants, the authors compared various associative theories that assumed either elemental (unique cue, modified unique cue, replaced elements model, and Harris' model) or configural processing of stimuli (Pearce's theory and a modification of it). The authors used modified patterning problems initially suggested by Redhead and Pearce (1995). Predictions for all theories were generated by computer simulations. Both configural theories and the unique cue approach failed to account for the observations. The replaced elements model was able to account for part of the data, but only if the replacement parameters could vary across discrimination problems. The Harris model and the modified unique cue approach, assuming that the salience of stimuli decreases with an increasing number of stimuli in a compound, successfully accounted for all of our data. This success implies that attentional factors should be explicitly taken into account in associative learning theory.