4.7 Article

Mean-based neural coding of voices

期刊

NEUROIMAGE
卷 79, 期 -, 页码 351-360

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.05.002

关键词

fMRI; Inferior frontal cortex; Prototype-centered representations; Superior temporal sulcus; Voice identity learning

资金

  1. Max Planck Society
  2. Hungarian Academy of Sciences [MTA 01 031]
  3. Fundacao para a Ciencia e a Tecnologia (IBB/CBME, LA, FEDER/POCI)

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The social significance of recognizing the person who talks to us is obvious, but the neural mechanisms that mediate talker identification are unclear. Regions along the bilateral superior temporal sulcus (STS) and the inferior frontal cortex (IFC) of the human brain are selective for voices, and they are sensitive to rapid voice changes. Although it has been proposed that voice recognition is supported by prototype-centered voice representations, the involvement of these category-selective cortical regions in the neural coding of such mean voices has not previously been demonstrated. Using fMRI in combination with a voice identity learning paradigm, we show that voice-selective regions are involved in the mean-based coding of voice identities. Voice typicality is encoded on a supra-individual level in the right STS along a stimulus-dependent, identity-independent (i.e., voice-acoustic) dimension, and on an intra-individual level in the right IFC along a stimulus-independent, identity-dependent (i.e., voice identity) dimension. Voice recognition therefore entails at least two anatomically separable stages, each characterized by neural mechanisms that reference the central tendencies of voice categories. (c) 2013 Elsevier Inc. All rights reserved.

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