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      Representations of individuals in ventral temporal cortex defined by faces and biographies.

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          Abstract

          The fusiform gyrus responds more strongly to faces than to other categories of objects. This response could reflect either categorical detection of faces or recognition of particular facial identities. Recent fMRI studies have attempted to address the question of what information is encoded in these regions, but have reported mixed results. We tested whether the creation of richer identity representations via training on visual and social information, and the use of an adaptation design, would reveal more robust representations of these identities in ventral temporal cortex. Examining the patterns of activation across voxels in bilateral fusiform gyri, we identified unique patterns for particular identities. Attaching distinctive biographical information to identities did not increase the strength of these representations, but did produce a grouping effect: faces associated with the same amount of biographical information were represented more similarly to each other. These results are consistent with the possibility that identity exemplars are represented in posterior visual areas best known for their role in representing categorical information, and suggest that these areas may be sensitive to some forms of non-visual information, including from the social domain.

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          Author and article information

          Journal
          Neuropsychologia
          Neuropsychologia
          Elsevier BV
          1873-3514
          0028-3932
          Sep 2013
          : 51
          : 11
          Affiliations
          [1 ] Department of Psychology, Harvard University, Cambridge, MA 02138, USA. Electronic address: sverosky@fas.harvard.edu.
          Article
          S0028-3932(13)00234-0 NIHMS506868
          10.1016/j.neuropsychologia.2013.07.006
          3783605
          23871881
          0926105d-c590-4132-be8c-4034c8a735ee
          History

          Facial identity,Familiarity,Learning,Multi-voxel pattern analysis,fMRI adaptation

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