title: Typicality sharpens category representations in object-selective cortex.
abstract: The purpose of categorization is to identify generalizable classes of objects whose members can be treated equivalently. Within a category, however, some exemplars are more representative of that concept than others. Despite long-standing behavioral effects, little is known about how typicality influences the neural representation of real-world objects from the same category. Using fMRI, we showed participants 64 subordinate object categories (exemplars) grouped into 8 basic categories. Typicality for each exemplar was assessed behaviorally and we used several multi-voxel pattern analyses to characterize how typicality affects the pattern of responses elicited in early visual and object-selective areas: V1, V2, V3v, hV4, LOC. We found that in LOC, but not in early areas, typical exemplars elicited activity more similar to the central category tendency and created sharper category boundaries than less typical exemplars, suggesting that typicality enhances within-category similarity and between-category dissimilarity. Additionally, we uncovered a brain region (cIPL) where category boundaries favor less typical categories. Our results suggest that typicality may constitute a previously unexplored principle of organization for intra-category neural structure and, furthermore, that this representation is not directly reflected in image features describing natural input, but rather built by the visual system at an intermediate processing stage.
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA 94305, USA. Electronic address: mci@cs.stanford.edu.
authors.forename: Marius Cătălin
authors.initials: MC
authors.lastname: Iordan
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA 94305, USA. Electronic address: mrgreene@stanford.edu.
authors.forename: Michelle R
authors.initials: MR
authors.lastname: Greene
authors.affiliation: Beckman Institute and Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Electronic address: dmbeck@illinois.edu.
authors.forename: Diane M
authors.initials: DM
authors.lastname: Beck
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA 94305, USA. Electronic address: feifeili@cs.stanford.edu.
authors.forename: Li
authors.initials: L
authors.lastname: Fei-Fei
mesh_terms: D000328:Adult; D001931:Brain Mapping / Q000379:methods; D003210:Concept Formation / Q000502:physiology*; D005260:Female; D005556:Form Perception / Q000502:physiology*; D006801:Humans; D008297:Male; D009415:Nerve Net / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology; D021641:Recognition, Psychology / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*
keywords: Categorization; Object; Typicality; fMRI