Literature DB >> 24591523

Neural Trade-Offs between Recognizing and Categorizing Own- and Other-Race Faces.

Jiangang Liu1, Zhe Wang2, Lu Feng3, Jun Li4, Jie Tian5, Kang Lee6.   

Abstract

Behavioral research has suggested a trade-off relationship between individual recognition and race categorization of own- and other-race faces, which is an important behavioral marker of face processing expertise. However, little is known about the neural mechanisms underlying this trade-off. Using functional magnetic resonance imaging (fMRI) methodology, we concurrently asked participants to recognize and categorize own- and other-race faces to examine the neural correlates of this trade-off relationship. We found that for other-race faces, the fusiform face area (FFA) and occipital face area (OFA) responded more to recognition than categorization, whereas for own-race faces, the responses were equal for the 2 tasks. The right superior temporal sulcus (STS) responses were the opposite to those of the FFA and OFA. Further, recognition enhanced the functional connectivity from the right FFA to the right STS, whereas categorization enhanced the functional connectivity from the right OFA to the right STS. The modulatory effects of these 2 couplings were negatively correlated. Our findings suggested that within the core face processing network, although recognizing and categorizing own- and other-race faces activated the same neural substrates, there existed neural trade-offs whereby their activations and functional connectivities were modulated by face race type and task demand due to one's differential processing expertise with own- and other-race faces.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  cross-face processing; dynamic causal modeling; fMRI; neural trade-off; other-race effect

Mesh:

Year:  2014        PMID: 24591523      PMCID: PMC4494030          DOI: 10.1093/cercor/bhu025

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


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