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Mean-based neural coding of voices

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons1650

Andics,  Attila
Language Comprehension Department, MPI for Psycholinguistics, Max Planck Society;
Mechanisms and Representations in Comprehending Speech, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour;
Comparative Ethological Research Group, Hungarian Academy of Sciences – Eötvös Loránd University, Budapest, Hungary;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons122

McQueen,  James M.
Language Comprehension Department, MPI for Psycholinguistics, Max Planck Society;
Mechanisms and Representations in Comprehending Speech, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour;
Behavioural Science Institute, Radboud University Nijmegen,;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons147

Petersson,  Karl Magnus
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour;
Cognitive Neuroscience Research Group, Institute for Biotechnology & Bioengineering, CBME, University of Algarve, Faro, Portugal;

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Andics_NeuroImage_2013.pdf
(Verlagsversion), 828KB

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Zitation

Andics, A., McQueen, J. M., & Petersson, K. M. (2013). Mean-based neural coding of voices. NeuroImage, 79, 351-360. doi:10.1016/j.neuroimage.2013.05.002.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0012-BE33-F
Zusammenfassung
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.