PUB - Publikationen an der Universität Bielefeld

Our brain combines sensory inputs from various sources by dynamically weighting cues according to their reliability and relevance for a given task. In our daily lives, one such task is to navigate familiar but also unknown environments, as we move from place to place. Two pertinent cues in navigation are the spatial arrangement of landmarks, and the continuous path integration of travelled distances and changes in direction. Although several modelling studies have shown that Bayesian integration of cues provides a good explanation for navigation in environments with up to three objects at the population level, it remains unclear how navigation of individuals is affected by more complex environments. To investigate how humans process and combine cues of varying reliability about landmarks and path integration in complex environments, we conducted virtual reality experiments. We varied the number of landmarks to study navigation in environments ranging from an open steppe to a dense forest, thus going beyond environments with three landmarks that have been studied in the past. We analysed spatial behaviour at both the population and individual level with linear regression models and developed a computational model, based on maximum likelihood estimation (MLE), to infer the underlying dynamic combination of cues. With more than three landmarks, individual differences between participants in the use of cues are striking. For some, the addition of landmarks does not worsen their performance, whereas for others it seems to impair their use of landmark information. It appears that navigation success in complex environments depends on the ability to identify the correct clearing around the goal location, suggesting that some participants may not be able to see the forest for the trees while others do.