Visual category learning

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Abstract

Visual categories group together different objects as the same kinds of thing. We review a selection of research on how visual categories are learned. We begin with a guide to visual category learning experiments, describing a space of common manipulations of objects, categories, and methods used in the category learning literature. We open with a guide to these details in part because throughout our review we highlight how methodological details can sometimes loom large in theoretical discussions of visual category learning, how variations in methodological details can significantly affect our understanding of visual category learning, and how manipulations of methodological details can affect how visual categories are learned. We review a number of core theories of visual category learning, specifically those theories instantiated as computational models, highlighting just some of the experimental results that help distinguish between competing models. We examine behavioral and neural evidence for single versus multiple representational systems for visual category learning. We briefly discuss how visual category learning influences visual perception, describing empirical and brain imaging results that show how learning to categorize objects can influence how those objects are represented and perceived. We close with work that can potentially impact translation, describing recent experiments that explicitly manipulate key methodological details of category learning procedures with the goal of optimizing visual category learning. WIREs Cogn Sci 2014, 5:75–94. doi: 10.1002/wcs.1268

Conflict of interest: The authors have declared no conflicts of interest for this article.

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