Fig. 1: Triangle-completion task & cue integration account.
a Schematic of a typical homing task, here triangle completion, within a real14 or virtual15,16 environment with landmarks in the background and a goal location (shown in red). b Participants walk from a start position through a sequence of three-goal locations (outbound path) before returning to the first goal location (home, shown in red). c Experimental manipulations of internal and external cues at the end of the outbound path for different experimental conditions: Self-motion condition (reduced visual information), landmark condition (reduced direction and position information), combined condition (all cues available), conflict condition (covert rotation of landmarks). Endpoint data from Chen et al.16. d Cue integration accounts for endpoint variability in homing task14. Response variability is computed as the standard deviation of Euclidean distances14,16 (or heading direction15) to mean response locations (or directions) for each condition. Top-Left: Response variability for different cue conditions. Variability in landmark (blue) and self-motion (red) conditions predict reduced variability in combined conditions (green and violet) according to perceptual cue integration models (gray). Top-Right: Biased homing responses in conflict conditions are used to determine how much participants relied on either of the two cues (relative response proximity). Red and blue crosses represent target locations for exclusive reliance on either self-motion or landmarks cues. Bottom: If cues are combined optimally in conflict conditions, response variability is reduced in double cue conditions (combined and conflict) compared to single cue conditions (landmark and self-motion) and the optimal response location is biased toward the more reliable cue. e Walking trajectories of participants from the study of Zhao & Warren15 compared to simulated participants from our computational model performing the triangle-completion task (Supplementary Movie 2).
