Journal articles
Norm-Based Coding of Voice Identity in Human Auditory Cortex
Abstract : Listeners exploit small interindividual variations around a generic acoustical structure to discriminate and identify individuals from their voice-a key requirement for social interactions. The human brain contains temporal voice areas (TVA) [1] involved in an acoustic-based representation of voice identity [2-6], but the underlying coding mechanisms remain unknown. Indirect evidence suggests that identity representation in these areas could rely on a norm-based coding mechanism [4, 7-11]. Here, we show by using fMRI that voice identity is coded in the TVA as a function of acoustical distance to two internal voice prototypes (one male, one female)-approximated here by averaging a large number of same-gender voices by using morphing [12]. Voices more distant from their prototype are perceived as more distinctive and elicit greater neuronal activity in voice-sensitive cortex than closer voices-a phenomenon not merely explained by neuronal adaptation [13, 14]. Moreover, explicit manipulations of distance-to-mean by morphing voices toward (or away from) their prototype elicit reduced (or enhanced) neuronal activity. These results indicate that voice-sensitive cortex integrates relevant acoustical features into a complex representation referenced to idealized male and female voice prototypes. More generally, they shed light on remarkable similarities in cerebral representations of facial and vocal identity.
Cited literature [43 references]
https://hal-amu.archives-ouvertes.fr/hal-02008910
Contributor : Morgane Bourhis <>
Submitted on : Wednesday, February 6, 2019 - 4:40:34 AM
Last modification on : Wednesday, October 14, 2020 - 4:21:50 AM
Long-term archiving on: : Tuesday, May 7, 2019 - 12:47:59 PM
Contributor : Morgane Bourhis <>
Submitted on : Wednesday, February 6, 2019 - 4:40:34 AM
Last modification on : Wednesday, October 14, 2020 - 4:21:50 AM
Long-term archiving on: : Tuesday, May 7, 2019 - 12:47:59 PM
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PIIS096098221300496X.pdf
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