A context-change account of temporal distinctiveness

Abstract

The distinctiveness effect refers to the finding that items that stand out from other items in a learning set are more likely to be remembered later. Traditionally, distinctiveness has been defined based on item features; specifically, an item is deemed to be distinctive if its features are different from the features of other to-be-learned items. We propose that distinctiveness can be redefined based on context change—distinctive items are those with features that deviate from the others in the current temporal context, a recency-weighted running average of experience—and that this context change modulates learning. We test this account with two novel experiments and introduce a formal mathematical model that instantiates our proposed theory. In the experiments, participants studied lists of words, with each word appearing on one of two background colors. Within each list, each color was used for 50% of the words, but the sequence of the colors was controlled so that runs of the same color for that list were common in Experiment 1 and common, rare, or random in Experiment 2. In both experiments, participants’ source memory for background color was enhanced for items where the color changed, especially if the change occurred after a stable run without color changes. Conversely, source memory was not significantly better for nonchanges after runs of alternating colors with each item. This pattern is inconsistent with theories of learning based on prediction error, but is consistent with our context-change account.