Did It Move? Humans Use Spatio-Temporal Landmark Permanency Efficiently for Navigation

Visual landmarks provide crucial information for human navigation. But what characteristics define a landmark? To be uniquely recognized, a landmark should be distinctive and salient, while providing precise and accurate positional information. It should also be permanent. For example, to find back to your car, a nearby church seems a better landmark compared with a distinct truck or bicycle, because you learned that there is a chance that these objects might move. To this end, we investigated human learning of landmark permanency for navigation while treating spatiotemporal permanency as a probabilistic property. We hypothesized that humans will be able to learn the probabilistic nature of landmark permanency and assign higher weight to more permanent landmarks. To test this hypothesis, we designed a homing task where participants had to return to a position that was surrounded by three landmarks. In the learning phase we manipulated the spatiotemporal permanency of one landmark by secretly repositioning it before participants returned home. In the test phase, we investigated the weight allocated to the nonpermanent landmark by analyzing its influence on the navigational performance during homing. We conducted four experiments: In the first two experiments we altered the statistics of permanency and accordingly found an influence on participants' behavior, nonpermanent objects were used less for finding home. In the last two experiments we investigated the role of short-term learning of novel statistics versus long-term knowledge about such statistics. No carry-over effects in Experiment 3 and very little influence of object identity with different long-term permanency characteristics in Experiment 4 revealed a dominance of short-term learning over the use of long-term a priori knowledge about object permanency. This indicates that long-term prior beliefs are quickly updated by the current permanency statistics. Taken together, consistent with a Bayesian account for navigation these results indicate that humans quickly learn and update the statistics of landmark permanency and use it in an effective way, assigning gradually more weight to the more permanent landmark and making it more important for navigation.