Neural mechanisms for voice recognition

Abstract

We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training explicitly defined a voice-identity space. The pre-defined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training histories on different tests. Cortical sensitivity to voice similarity appeared over different time-scales and at different representational stages. First, there were short-term adaptation effects: increasing acoustic similarity to the directly preceding stimulus led to haemodynamic response reduction in the middle/posterior STS and in right ventrolateral prefrontal regions. Second, there were longer-term effects: response reduction was found in the orbital/insular cortex for stimuli that were most versus least similar to the acoustic mean of all preceding stimuli, and, in the anterior temporal pole, the deep posterior STS and the amygdala, for stimuli that were most versus least similar to the trained voice-identity category mean. These findings are interpreted as effects of neural sharpening of long-term stored typical acoustic and category-internal values. The analyses also reveal anatomically separable voice representations: one in a voice-acoustics space and one in a voice-identity space. Voice-identity representations flexibly followed the trained identity shift, and listeners with a greater identity effect were more accurate at recognizing familiar voices. Voice recognition is thus supported by neural voice spaces that are organized around flexible 'mean voice' representations.

Perceptual interaction of the harmonic source and noise in voice

“…Many clinical voice evaluation protocols require listeners to rate individual voice features (e.g., Kempster et al, 2009;Hirano, 1981;Laver et al, 1981), and thus implicitly assume the first model. However, the present results, as well as results of a number of behavioral and neuropsychological studies (e.g., Van Lancker et al, 1985a,b;Li and Pastore, 1995;Schweinberger et al, 1997;Andics et al, 2010;Melara and Marks, 1990), are more consistent with the second view of quality. For example, in priming experiments (Schweinberger et al, 1997) reaction times to famous voices were significantly faster when listeners had previously heard a different exemplar of the voice.…”

Direct Structural Connections between Voice- and Face-Recognition Areas

“…Our findings suggest that areas that are involved in voice identity processing show particularly strong connections to the FFA. Conversely, posterior voice-sensitive regions in STS have been found to process acoustic parameters of voices, which suggests limited need for exchange of information between posterior STS and FFA (Belin and Zatorre, 2003;von Kriegstein et al, 2003von Kriegstein et al, , 2007von Kriegstein and Giraud, 2004;Andics et al, 2010).…”

“…Posterior areas of the STS are more involved in acoustic processing and more anterior areas are responsive to voice identity (Belin and Zatorre, 2003;von Kriegstein et al, 2003;von Kriegstein and Giraud, 2004;Andics et al, 2010). Face-sensitive areas are located in occipital gyrus, fusiform gyrus, and anterior inferior temporal lobe (Kanwisher et al, 1997;Kriegeskorte et al, 2007;Rajimehr et al, 2009).…”

The functional profile of the human amygdala in affective processing: Insights from intracranial recordings

“…Evidence from neuroimaging data and neuropsychological testing reveals great heterogeneity of amygdala responses, including emotion processing (Phelps & Anderson, 1997;Vuilleumier, 2005), face-processing (Vuilleumier, 2005;Whalen, 1998), voice processing (Andics et al, 2010;Fruhholz & Grandjean, 2013;Sander et al, 2005), arousal processing (Canli, Zhao, Brewer, Gabrieli, & Cahill, 2000), novelty detection (Schwartz, Wright, Shin, Kagan, & Rauch, 2003;Zald, 2003), ambiguity resolution (Brand, Grabenhorst, Starcke, Vandekerckhove, & Markowitsch, 2007;Whalen, 1998), behavioral (Ousdal et al, 2008) and motivational (Cunningham & Brosch, 2012;Pessoa & Adolphs, 2010) relevance detection, and learning and memory consolidation (Hamann, 2009). This research may implicate a learning and memory consolidation by the human amygdala that is based on the emotional value or affective relevance imbued in the encoded event/object (Cunningham & Brosch, 2012;Sander et al, 2003).…”