Automaticity of basic-level categorization accounts for labeling effects in visual recognition memory.
ABSTRACT Are there consequences of calling objects by their names? Lupyan (2008) suggested that overtly labeling objects impairs subsequent recognition memory because labeling shifts stored memory representations of objects toward the category prototype (representational shift hypothesis). In Experiment 1, we show that processing objects at the basic category level versus exemplar level in the absence of any overt labeling produces the same qualitative pattern of results. Experiment 2 demonstrates that labeling does not always disrupt memory as predicted by the representational shift hypothesis: Differences in memory following labeling versus preference are more likely an effect of judging preference, not an effect of overt labeling. Labeling does not influence memory by shifting memory representations toward the category prototype. Rather, labeling objects at the basic level produces memory representations that are simply less robust than those produced by other kinds of study tasks.
Full-textDOI: · Available from: Jenn Richler, Mar 30, 2014
- SourceAvailable from: D. Alexander VarakinSAGE Open 10/2014; DOI:10.1177/2158244014553588
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ABSTRACT: In four experiments, a total of 205 participants studied individual color patches and were given an old-new recognition test after a brief retention interval (0.5 or 5.0 s). The pattern of hue sensitivity (d') revealed hue memory shifting away from the prototype of the hue's basic color category. The shifts demonstrate that hue memory is influenced by categorization early in processing. The shifts did not depend on intentional categorization; the shifts were found even when participants made preference ratings at encoding rather than labeling judgments. Overall, we found that categorization and memory are deeply intertwined from perception onward. We discuss the impact of the results on theories of memory and categorization, including the effects of category labels on memory (e.g., Lupyan, 2008). We also put forward the hypothesis that atypical shifts in hue are related to atypical shifts that have previously observed in face recognition (Rhodes et al., 1987).Frontiers in Psychology 07/2014; 5:796. DOI:10.3389/fpsyg.2014.00796 · 2.80 Impact Factor
Article: Visual category learning[Show abstract] [Hide abstract]
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. For further resources related to this article, please visit the WIREs website.Wiley interdisciplinary reviews. Cognitive science 01/2014; 5(1). DOI:10.1002/wcs.1268 · 0.79 Impact Factor