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.