Implicit Detection of Event Interdependencies and a PDP Model of the Process

We report on an experiment in which subjects were asked to predict the location of a stimulus based on observation of a series of five events. Unbeknownst to subjects, the location of the sixth event was determined by a double contingency between the second and fourth events in the sequence. This material is therefore highly complex, since the relevant events are embedded in a large number of irrelevant contexts. The results indicated that subjects improved their prediction performance over 10 sessions encompassing over 2400 trials of training, despite the fact that they remained completely unaware of the existence of the rule, and unable to verbalize their knowledge of the contingencies in the material. We propose a model of performance in this task, in the form of a PDP model of sequence processing. The model successfully accounts for performance and illustrates how knowledge about the temporal context may develop in a way that does not necessarily yield decomposable representations. Interestingly, the model also predicts that performance would be worse if subjects were required to predict successive events rather than simply observe them.