Seeing Like a Geologist: Bayesian Use of Expert Categories in Location Memory

Cognitive Science 40 (2):440-454 (2016)
  Copy   BIBTEX

Abstract

Memory for spatial location is typically biased, with errors trending toward the center of a surrounding region. According to the category adjustment model, 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 categories. Results are discussed with respect to the CAM

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 101,505

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

A Bayesian Account of Reconstructive Memory.Pernille Hemmer & Mark Steyvers - 2009 - Topics in Cognitive Science 1 (1):189-202.

Analytics

Added to PP
2015-05-06

Downloads
25 (#884,004)

6 months
2 (#1,688,095)

Historical graph of downloads
How can I increase my downloads?