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Abstract People use environmental knowledge to maintain a sense of direction in daily life. This knowledge is typically measured by having people point to unseen locations (judgments of relative direction) or navigate efficiently in the environment (shortcutting). Some people can estimate directions precisely, while others point randomly. Similarly, some people take shortcuts not experienced during learning, while others mainly follow learned paths. Notably, few studies have directly tested the correlation between pointing and shortcutting performance. We compared pointing and shortcutting in two experiments, one using desktop virtual reality (VR) (N = 57) and one using immersive VR (N = 48). Participants learned a new environment by following a fixed route and were then asked to point to unseen locations and navigate to targets by the shortest path. Participants’ performance was clustered into two groups using K-means clustering. One (lower ability) group pointed randomly and showed low internal consistency across trials in pointing, but were able to find efficient routes, and their pointing and efficiency scores were not correlated. The others (higher ability) pointed precisely, navigated by efficient routes, and their pointing and efficiency scores were correlated. These results suggest that with the same egocentric learning experience, the correlation between pointing and shortcutting depends on participants’ learning ability, and internal consistency and discriminating power of the measures. Inconsistency and limited discriminating power can lead to low correlations and mask factors driving human variation. Psychometric properties, largely under-reported in spatial cognition, can advance our understanding of individual differences and cognitive processes for complex spatial tasks. 

Abstract Individuals vary in the way they navigate through space. Some take novel shortcuts, while others rely on known routes to find their way around. We wondered how and why there is so much variation in the population. To address this, we first compared the trajectories of 368 human subjects navigating a virtual maze with simulated trajectories. The simulated trajectories were generated by strategy‐based path planning algorithms from robotics. Based on the similarities between human trajectories and different strategy‐based simulated trajectories, we found that there is a variation in the type of strategy individuals apply to navigate space, as well as variation within individuals on a trial‐by‐trial basis. Moreover, we observed variation within a trial when subjects occasionally switched the navigation strategies halfway through a trajectory. In these cases, subjects started with a route strategy, in which they followed a familiar path, and then switched to a survey strategy, in which they took shortcuts by considering the layout of the environment. Then we simulated a second set of trajectories using five different but comparable artificial maps. These trajectories produced the similar pattern of strategy variation within and between trials. Furthermore, we varied the relative cost, that is, the assumed mental effort or required timesteps to choose a learned route over alternative paths. When the learned route was relatively costly, the simulated agents tended to take shortcuts. Conversely, when the learned route was less costly, the simulated agents showed preference toward a route strategy. We suggest that cost or assumed mental effort may be the reason why in previous studies, subjects used survey knowledge when instructed to take the shortest path. We suggest that this variation we observe in humans may be beneficial for robotic swarms or collections of autonomous agents during information gathering. 

Humans and other animals have a remarkable capacity to translate their position from one spatial frame of reference to another. The ability to seamlessly move between top-down and first-person views is important for navigation, memory formation, and other cognitive tasks. Evidence suggests that the medial temporal lobe and other cortical regions contribute to this function. To understand how a neural system might carry out these computations, we used variational autoencoders (VAEs) to reconstruct the first-person view from the top-down view of a robot simulation, and vice versa. Many latent variables in the VAEs had similar responses to those seen in neuron recordings, including location-specific activity, head direction tuning, and encoding of distance to local objects. Place-specific responses were prominent when reconstructing a first-person view from a top-down view, but head direction–specific responses were prominent when reconstructing a top-down view from a first-person view. In both cases, the model could recover from perturbations without retraining, but rather through remapping. These results could advance our understanding of how brain regions support viewpoint linkages and transformations. 

Spatial perspective taking is an essential cognitive ability that enables people to imagine how an object or scene would appear from a perspective different from their current physical viewpoint. This process is fundamental for successful navigation, especially when people utilize navigational aids (e.g., maps) and the information provided is shown from a different perspective. Research on spatial perspective taking is primarily conducted using paper-pencil tasks or computerized figural tasks. However, in daily life, navigation takes place in a three-dimensional (3D) space and involves movement of human bodies through space, and people need to map the perspective indicated by a 2D, top down, external representation to their current 3D surroundings to guide their movements to goal locations. In this study, we developed an immersive viewpoint transformation task (iVTT) using ambulatory virtual reality (VR) technology. In the iVTT, people physically walked to a goal location in a virtual environment, using a first-person perspective, after viewing a map of the same environment from a top-down perspective. Comparing this task with a computerized version of a popular paper-and-pencil perspective taking task (SOT: Spatial Orientation Task), the results indicated that the SOT is highly correlated with angle production error but not distance error in the iVTT. Overall angular error in the iVTT was higher than in the SOT. People utilized intrinsic body axes (front/back axis or left/right axis) similarly in the SOT and the iVTT, although there were some minor differences. These results suggest that the SOT and the iVTT capture common variance and cognitive processes, but are also subject to unique sources of error caused by different cognitive processes. The iVTT provides a new immersive VR paradigm to study perspective taking ability in a space encompassing human bodies, and advances our understanding of perspective taking in the real world.