Seeing Like a Geologist: Bayesian Use of Expert Categories in Location Memory.
Memory for spatial location is typically biased, with errors trending toward the center of a surrounding region. According to the category adjustment model (CAM), this bias reflects the optimal, Bayesian combination of fine-grained and categorical representations of a location. However, there is disagreement about whether categories are malleable. For instance, can categories be redefined based on expert-level conceptual knowledge? Furthermore, if expert knowledge is used, does it dominate other information sources, or is it used adaptively so as to minimize overall error, as predicted by a Bayesian framework? We address these questions using images of geological interest. The participants were experts in structural geology, organic chemistry, or English literature. Our data indicate that expertise-based categories influence estimates of location memory-particularly when these categories better constrain errors than alternative ("novice") categories. Results are discussed with respect to the CAM.
Department of Psychology, Temple University.|Department of Psychology, University of Western Ontario.
Mark P
MP
Holden
Department of Psychology, Temple University.
Nora S
NS
Newcombe
Department of Psychology, Temple University.
Ilyse
I
Resnick
Department of Psychology, Temple University.
Thomas F
TF
Shipley
D000328:Adult; D001499:Bayes Theorem; D003210:Concept Formation / Q000502:physiology; D006801:Humans; D009483:Neuropsychological Tests; D009949:Orientation / Q000502:physiology*; D013028:Space Perception / Q000502:physiology*; D065852:Spatial Memory / Q000502:physiology*
Bayesian models; Categorization; Expertise; Location memory; Spatial cognition