Trends in Cognitive Sciences
Computational approaches to the development of perceptual expertise
Section snippets
The development of perceptual expertise
It goes without saying that experts know more than novices. They can verbalize more properties, describe more relationships, make more inferences, and so forth 13, 14, 15. That is what makes them experts after all. Our focus in this review is on how expertise is manifest in more perceptually oriented tasks.
Computational models of the development of perceptual expertise
We focus on models from the object recognition and perceptual categorization literatures, two fields of visual object understanding that grew from largely separate research traditions but have recently begun to converge empirically and theoretically [8]. As this is a selective review, we necessarily omit several important alternative theoretical approaches 38, 39, but our selection was aimed at presenting a coherent theoretical package. Figure 1 outlines the relationships between the various
Concluding remarks
Expertise could entail the creation of highly specialized, modular adaptations to an object domain. However, we argue here that it is important first to try to ground explanations within existing computational models that already account for important aspects of visual object understanding. After reviewing current models from the object-recognition and perceptual-categorization literatures, we identified several hypotheses for the development of perceptual expertise. Some of these hypothesized
Acknowledgements
The authors’ work is supported by NSF Grants BCS-0218507, BCS-9910756 and BCS-0091752, NIMH Grant R01 MH61370, NEI Grant R01 EY13441, NEI Grant P30 EY008126, and a grant from the James S. McDonnell Foundation. The authors wish to thank members of the Perceptual Expertise Network (funded by JSMF) for helpful discussions.
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