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Different Measures of Structural Similarity Tap Different Aspects of Visual Object Processing

The structural similarity of objects has been an important variable in explaining why some objects are easier to categorize at a superordinate level than to individuate, and also why some patients with brain injury have more difficulties in recognizing natural (structurally similar) objects than art...

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Detalles Bibliográficos
Autor principal: Gerlach, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563126/
https://www.ncbi.nlm.nih.gov/pubmed/28861027
http://dx.doi.org/10.3389/fpsyg.2017.01404
Descripción
Sumario:The structural similarity of objects has been an important variable in explaining why some objects are easier to categorize at a superordinate level than to individuate, and also why some patients with brain injury have more difficulties in recognizing natural (structurally similar) objects than artifacts (structurally distinct objects). In spite of its merits as an explanatory variable, structural similarity is not a unitary construct, and it has been operationalized in different ways. Furthermore, even though measures of structural similarity have been successful in explaining task and category-effects, this has been based more on implication than on direct empirical demonstrations. Here, the direct influence of two different measures of structural similarity, contour overlap and within-item structural diversity, on object individuation (object decision) and superordinate categorization performance is examined. Both measures can account for performance differences across objects, but in different conditions. It is argued that this reflects differences between the measures in whether they tap: (i) global or local shape characteristics, and (ii) between- or within-category structural similarity.