Statistically Optimal Cue Integration During Human Spatial Navigation

In 2007, Cheng and colleagues published their influential review wherein they analyzed the literature on spatial cue interaction during navigation through a Bayesian lens, and concluded that models of optimal cue integration often applied in psychophysical studies could explain cue interaction during navigation. Since then, numerous empirical investigations have been conducted to assess the degree to which human navigators are optimal when integrating multiple spatial cues during a variety of navigation-related tasks. In the current review, we discuss the literature on human cue integration during navigation that has been published since Cheng et al.'s original review. Evidence from most studies demonstrate optimal navigation behavior when humans are presented with multiple spatial cues. However, applications of optimal cue integration models vary in their underlying assumptions (e.g., uninformative priors and decision rules). Furthermore, cue integration behavior depends in part on the nature of the cues being integrated and the navigational task (e.g., homing versus non-home goal localization). We discuss the implications of these models and suggest directions for future research.