Abstract
As we navigate through the world, we pick up on spatial patterns of locations across repeated experiences. We previously showed that humans use these learned patterns to guide searches for new locations. But what happens to the memories of individual past locations during this pattern extraction process? Studies of statistical learning have shown that visual regularities can alter memory representations of individual items. Here we investigate whether this occurs in memory for 3-D, navigable space. Across four experiments we tested whether learning a distribution of locations biases subsequent memory for the individual locations making up the distribution. In Experiment 1, participants completed a training block in which they learned five locations, and then a test block in which they reproduced each learned location from memory by navigating to it. Reproduction behavior was sensitive to the underlying distribution, but was biased more to the best remembered location in the distribution than the distribution mean. In Experiment 2, we provided additional distribution cues by interleaving practice and test blocks. Participants demonstrated significant distribution sensitivity, with bias towards the distribution mean. In Experiment 3, we assessed whether these sensitivities persisted under high allocentric demand by starting participants in a different location on each training and test trial. They again demonstrated significant distribution sensitivity, but it was not correlated with bias towards the best remembered location or distribution mean. Thus, in Experiment 4, we increased the salience of the distribution by showing all locations on each training trial, and all locations but the target at test. Participants demonstrated both significant distribution sensitivity and a bias toward the distribution mean. Our findings indicate that, under low-to-moderate demands on spatial memory, representations of specific locations are systematically distorted by learned visual statistics in 3-D space.