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Gordon E Legge, Sarah J Mason, Mark Brady, Nicholas Giudice, Erik J Schlicht; Maplets: local geometrical components of human cognitive maps. Journal of Vision 2003;3(9):136. doi: https://doi.org/10.1167/3.9.136.
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© ARVO (1962-2015); The Authors (2016-present)
The cognitive representation underlying human spatial navigation is often dichotomized into “route knowledge” and “survey knowledge.” Motivated by concepts from studies of animal navigation, we propose a different form of underlying representation for human navigation. “Maplets” are small pieces of maps whose configural information can be encoded from a single location using vision. The maplet representation of a building's layout consists of a set of maplets each composed of a root node (corridor intersection) and the connecting links (branching corridors) to adjacent maplets. We have developed a computer algorithm that synthesizes global building layouts from a set of maplets, demonstrating that global layout information is implicitly retained in the maplet decomposition. Convergent evidence from two empirical studies, conducted for other purposes supports the psychological reality of maplets. In one experiment (Giudice et al., VSS 2002), human judges rated the accuracy of maps drawn by human subjects who learned building layouts by exploration. A maplet-matching score (computed by comparing the number of maplets in the subjects' drawings to the actual maplet representation of the layout) correlated better with the judges' ratings (R = .87 to .98) than did a global template matching method (R = .64 to .66). In a second experiment (Schlicht et al., ARVO 2001), subjects learned a building layout by free exploration. Then they drew a map of the layout and also performed a set of target-localization trials. The maplet-matching scores, derived from the subjects' drawings, correlated (R = 0.7) with the accuracy of performance in the localization trials. Our computational and empirical results support the proposal that configural information in human cognitive maps is stored in local maplets. Each maplet contains geometrical information that is accessible by visual inspection from within the maplet.
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