Bayesian integration of spatial information

Abstract

Spatial judgments and actions are often based on multiple cues. The authors review a multitude of phenomena on the integration of spatial cues in diverse species to consider how nearly optimally animals combine the cues. Under the banner of Bayesian perception, cues are sometimes combined and weighted in a near optimal fashion. In other instances when cues are combined, how optimal the integration is might be unclear. Only 1 cue may be relied on, or cues may seem to compete with one another. The authors attempt to bring some order to the diversity by taking into account the subjective discrepancy in the dictates of multiple cues. When cues are too discrepant, it may be best to rely on 1 cue source. When cues are not too discrepant, it may be advantageous to combine cues. Such a dual principle provides an extended Bayesian framework for understanding the functional reasons for the integration of spatial cues.