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Probing principles of large-scale object representation: Category preference and location encoding

Authors

  • Radoslaw Martin Cichy,

    Corresponding author
    1. Bernstein Center for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Germany
    2. Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin, Berlin, Germany
    3. Department of Psychiatry, Campus Charité Mitte, Charité—Universitätsmedizin Berlin, Germany
    • Bernstein Center for Computational Neuroscience, Charité—Universitätsmedizin Berlin, Haus 6, Philippstrasse 13, 10115 Berlin, Germany
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  • Philipp Sterzer,

    1. Bernstein Center for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Germany
    2. Department of Psychiatry, Campus Charité Mitte, Charité—Universitätsmedizin Berlin, Germany
    3. Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany
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  • Jakob Heinzle,

    1. Bernstein Center for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Germany
    2. Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin, Berlin, Germany
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  • Lloyd T. Elliott,

    1. Bernstein Center for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Germany
    2. Gatsby Computational Neuroscience Unit, University College London, United Kingdom
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  • Fernando Ramirez,

    1. Bernstein Center for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Germany
    2. Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany
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  • John-Dylan Haynes

    Corresponding author
    1. Bernstein Center for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Germany
    2. Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin, Berlin, Germany
    3. Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany
    4. Cluster of Excellence NeuroCure, Charité—Universitätsmedizin Berlin, Berlin, Germany
    • Bernstein Center for Computational Neuroscience, Charité—Universitätsmedizin Berlin, Haus 6, Philippstrasse 13, 10115 Berlin, Germany
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Abstract

Knowledge about the principles that govern large-scale neural representations of objects is central to a systematic understanding of object recognition. We used functional magnetic resonance imaging (fMRI) and multivariate pattern classification to investigate two such candidate principles: category preference and location encoding. The former designates the preferential activation of distinct cortical regions by a specific category of objects. The latter refers to information about where in the visual field a particular object is located. Participants viewed exemplars of three object categories (faces, bodies, and scenes) that were presented left or right of fixation. The analysis of fMRI activation patterns revealed the following. Category-selective regions retained their preference to the same categories in a manner tolerant to changes in object location. However, category preference was not absolute: category-selective regions also contained location-tolerant information about nonpreferred categories. Furthermore, location information was present throughout high-level ventral visual cortex and was distributed systematically across the cortical surface. We found more location information in lateral-occipital cortex than in ventral-temporal cortex. Our results provide a systematic account of the extent to which the principles of category preference and location encoding determine the representation of objects in the high-level ventral visual cortex. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.

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