Models that allow us to perceive the world more accurately also allow us to remember past events more accurately via differentiation.

Differentiation is a theory that originally emerged from the perception literature and proposes that with experience, the representation of stimuli becomes more distinct from or less similar to the representation of other stimuli. In recent years, the role of differentiation has played a critical role in models of memory. Differentiation mechanisms have been implemented in episodic memory models by assuming that information about new experiences with a stimulus in a particular context accumulates in a single memory trace and these updated memory traces become more distinct from the representations of other stimuli. A key implication of such models is that well encoded events are less confusable with other events. This prediction is particularly relevant for two important phenomena. One is the role of encoding strength on memory. The strength based mirror effect is the finding of higher hit rates and lower false alarm rates for a list composed of all strongly encoded items compared to a list composed of all weakly encoded items. The other is output interference, the finding that accuracy decreases across a series of test trials. Results from four experiments show a tight coupling between these two empirical phenomena such that strongly encoded target items are less prone to interference. By proposing a process model and evaluating the predictions of the model, we show how a single theoretical principle, differentiation, provides a unified explanation for these effects.