Modeling the interaction of navigational systems in a reward-based virtual navigation task

Application of Real and Virtual Radial Arm Maze Task in Human

Virtual Reality (VR) emerges as a promising technology capable of creating different scenarios in which the body, environment, and brain are closely related, proving enhancements in the diagnosis and treatment of several spatial memory deficits. In recent years, human spatial navigation has increasingly been studied in interactive virtual environments. However, navigational tasks are still not completely adapted in immersive 3D VR systems. We stipulate that an immersive Radial Arm Maze (RAM) is an excellent instrument, allowing the participants to be physically active within the maze exactly as in the walking RAM version in reality modality. RAM is a behavioral ecological task that allows the analyses of different facets of spatial memory, distinguishing declarative components from procedural ones. In addition to describing the characteristics of RAM, we will also analyze studies in which RAM has been used in virtual modality to provide suggestions into RAM building in immersive modality.

Uncertainty promotes information-seeking actions, but what information?

Navigating an unfamiliar city almost certainly brings out uncertainty about getting from place to place. This uncertainty, in turn, triggers information gathering. While navigational uncertainty is common, little is known about what type of information people seek when they are uncertain. The primary choices for information types with environments include landmarks (distal or local), landmark configurations (relation between two or more landmarks), and a distinct geometry, at least for some environments. Uncertainty could lead individuals to more likely seek one of these information types. Extant research informs both predictions about and empirical work exploring this question. This review covers relevant cognitive literature and then suggests empirical approaches to better understand information-seeking actions triggered by uncertainty. Notably, we propose that examining continuous navigation data can provide important insights into information seeking. Benefits of continuous data will be elaborated through one paradigm, spatial reorientation, which intentionally induces uncertainty through disorientation and cue conflict. While this and other methods have been used previously, data have primarily reflected only the final choice. Continuous behavior during a task can better reveal the cognition-action loop contributing to spatial learning and decision making.