Typicality effects on memory for voice: Implications for earwitness testimony

Mullennix, John W.; Ross, Amy P.; Smith, Catherine M.; Kuykendall, Kevin L.; Conard, Jacqueline M.; Barb, Scott

doi:10.1002/acp.1635

Cited by 30 publications

(27 citation statements)

References 33 publications

(46 reference statements)

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“…More specifically, we have argued for the existence of dynamic, long-lasting 'mean voice' representations at both voice-acoustic and voice-identity stages of processing. In accordance with recent findings in behavioural studies of voice processing (Papcun et al, 1989;Mullennix et al, 2009, Bruckert et al, 2010 and with those in the face processing domain (Loffler et al, 2005), our demonstrations of neural 'mean voice' representations constitute the first neuroimaging evidence that voice representations are centered around prototypes in long-term memory.…”

Section: Resultssupporting

confidence: 87%

“…In a study on face-identity processing, reduced haemodynamic responses were found in the fusiform face area for central stimuli only when those were also central in the long-term stored face space of the viewer (referred to as 'mean face' stimuli, Loffler et al, 2005), suggesting that long-term central faces are encoded more sparsely. Based on these results and on behavioural findings that have indicated a prototype-centered representation of voices in long-term memory (Papcun et al, 1989;Mullennix et al, 2009;Bruckert et al, 2010), we can expect a typicality-based neural sharpening mechanism for voices similar to that found for faces.…”

Section: Introductionmentioning

confidence: 58%

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Neural mechanisms for voice recognition

et al. 2010

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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.

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Section: Resultssupporting

confidence: 87%

Section: Introductionmentioning

confidence: 58%

Neural mechanisms for voice recognition

et al. 2010

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“…To us, this discussion fits well with the literature on distinctiveness, and links with the recent work of Brédart (2012b, see also Mullenix, Ross, Smith, Kuykendall, Conard &Barb, 2011;Sorensen, 2012;Zetterholm, Sarwar, Thorvaldsson & Allwood, 2012 for further examples of vocal distinctiveness effects). Within their study, Barsics and Brédart explored the retrieval of episodic and semantic information from distinctive and typical faces and voices.…”

Section: Not All Voices Are Created Equal: Robust Exemplarssupporting

confidence: 86%

Hearing Faces and Seeing Voices: The Integration and Interaction of Face and Voice Processing

2014

Psychologica Belgica

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“…Earlier studies have indicated that voices may be represented in prototype-centered voice spaces (Andics et al, 2010;Bruckert et al, 2010;Latinus et al, 2009;Mullennix et al, 2009;Papcun et al, 1989) and that the STS (Andics et al, 2010;Belin and Zatorre, 2003;Wong et al, 2004) and IFC (Andics et al, 2010; are core voice processing regions, showing voice selectivity and short-term sensitivity to voice similarity. But these voice-selective regions of the STS and the IFC have not previously been shown to be involved in long-term mean-based voice coding, and indeed there has to date been no other evidence of long-term neural coding of voice prototypes.…”

Section: Discussionmentioning

confidence: 99%

“…It has been argued that mean-based coding can also result from long-term adaptation (Kahn and Aguirre, 2012), a mechanism that is sensitive to stimulus distributions. Recent behavioral (Bruckert et al, 2010;Latinus et al, 2009;Mullennix et al, 2009;Papcun et al, 1989) and neuroimaging studies (Andics et al, 2010) also suggest that there is mean-based coding for voices. In other words, voice representations appear to be centered around prototypes in long-term memory.…”

Section: Introductionmentioning

confidence: 95%

Mean-based neural coding of voices

Andics¹,

McQueen²,

Petersson³

2013

NeuroImage

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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.

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Typicality effects on memory for voice: Implications for earwitness testimony

Cited by 30 publications

References 33 publications

Neural mechanisms for voice recognition

Neural mechanisms for voice recognition

Hearing Faces and Seeing Voices: The Integration and Interaction of Face and Voice Processing

Mean-based neural coding of voices

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