Successful Prediction Is Associated With Enhanced Encoding

Forming memories requires a focus on the external world; retrieving memories requires attention to our internal world. Computational models propose that the hippocampus resolves the tension between encoding and retrieval by alternating between states that prioritize one over the other. We asked whether the success of a retrieval state affects the success of an encoding state, when both are measured in behavior. Across 3 Experiments (N = 197), we operationalized retrieval as the use of memories to make predictions about the future, and tested whether successful (vs. unsuccessful) prediction affected the likelihood of successful encoding. Participants viewed a series of scene categories that contained structure (e.g., beaches are followed by castles), which enabled memory retrieval to guide prediction. After structure learning, they completed a simultaneous prediction and encoding task. They were shown trial-unique category exemplars and made predictions about upcoming scene categories. Finally, participants completed a surprise memory test for the trial-unique images. Accurate (vs. inaccurate) predictions were associated with better encoding, and increasing prediction distance hurt both prediction and encoding. This association between encoding and prediction could not be explained by generic on- vs. off-task states. We propose that, in addition to stimulus and endogenous factors that modulate switches between encoding and retrieval, the success of one state can facilitate a switch to the other. Thus, although encoding and prediction depend on distinct and competitive computational mechanisms, the success of one in behavior can increase the likelihood of success for the other.