Learning-Dependent Evolution of Spatial Representations in Large-Scale Virtual Environments

An important question regards how we use environmental boundaries to anchor spatial representations during navigation. Behavioral and neurophysiological models appear to provide conflicting predictions, and this question has been difficult to answer because of technical challenges with testing navigation in novel, large-scale, realistic spatial environments. We conducted an experiment in which participants freely ambulated on an omnidirectional treadmill while viewing novel, town-sized environments in virtual reality on a head-mounted display. Participants performed interspersed judgments of relative direction (JRD) to assay their spatial knowledge and to determine when during learning they employed environmental boundaries to anchor their spatial representations. We designed JRD questions that assayed directions aligned and misaligned with the axes of the surrounding rectangular boundaries and employed structural equation modeling to better understand the learning-dependent dynamics for aligned versus misaligned pointing. Pointing accuracy showed no initial directional bias to boundaries, although such "alignment effects" did emerge after the fourth block of learning. Preexposure to a map in Experiment 2 led to similar overall findings. A control experiment in which participants studied a map but did not navigate the environment, however, demonstrated alignment effects after a brief, initial learning experience. Our results help to bridge the gap between neurophysiological models of location-specific firing in rodents and human behavioral models of spatial navigation by emphasizing the experience-dependent accumulation of route-specific knowledge. In particular, our results suggest that the use of spatial boundaries as an organizing schema during navigation of large-scale space occurs in an experience-dependent fashion.