An adaptive cue combination model of human spatial reorientation

•A probabilistic cue combination model is proposed for spatial reorientation in humans.•The model captures previously unaccounted cues of reorientation such as language.•The model has minimal complexity and makes accurate predictions across existing data.

Previous research has proposed an adaptive cue combination view of the development of human spatial reorientation (Newcombe & Huttenlocher, 2006), whereby information from multiple sources is combined in a weighted fashion in localizing a target, as opposed to being modular and encapsulated (Hermer & Spelke, 1996). However, no prior work has formalized this proposal and tested it against existing empirical data. We propose a computational model of human spatial reorientation that is motivated by probabilistic approaches to optimal perceptual cue integration (e.g. Ernst & Banks, 2002) and to spatial location coding (Huttenlocher, Hedges, & Duncan, 1991). We show that this model accounts for data from a variety of human reorientation experiments, providing support for the adaptive combination view of reorientation.