Crossmodal priming of unfamiliar faces supports early interactions between voices and faces in person perception

Bülthoff, I; Newell, Fiona N.

doi:10.1080/13506285.2017.1290729

Cited by 14 publications

(9 citation statements)

References 56 publications

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“…Although findings from developmental prosopagnosia (McConachie, 1976 ), that is, a severe deficit in face‐identity processing, suggest that it may be related to face processing abilities (Maguinness & von Kriegstein, 2017 ; von Kriegstein et al, 2006 ; von Kriegstein et al, 2008 ). Other evidence of interactions (Bülthoff & Newell, 2015 , 2017 ) and relationships between face‐ and voice‐identity recognition abilities in the neurotypical population (Jenkins et al, 2020 ), suggest that a common coding system may underpin this enhancement i.e., similar computations in different modalities. Interestingly, the proportion of the current sample with a face‐benefit is in line with our previous observations.…”

Section: Discussionmentioning

confidence: 98%

Visual mechanisms for voice‐identity recognition flexibly adjust to auditory noise level

Maguinness

Kriegstein

2021

Human Brain Mapping

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Recognising the identity of voices is a key ingredient of communication. Visual mechanisms support this ability: recognition is better for voices previously learned with their corresponding face (compared to a control condition). This so-called 'face-benefit' is supported by the fusiform face area (FFA), a region sensitive to facial form and identity. Behavioural findings indicate that the face-benefit increases in noisy listening conditions. The neural mechanisms for this increase are unknown. Here, using functional magnetic resonance imaging, we examined responses in face-sensitive regions while participants recognised the identity of auditory-only speakers (previously learned by face) in high (SNR À4 dB) and low (SNR +4 dB) levels of auditory noise. We observed a face-benefit in both noise levels, for most participants (16 of 21). In high-noise, the recognition of face-learned speakers engaged the right posterior superior temporal sulcus motion-sensitive face area (pSTS-mFA), a region implicated in the processing of dynamic facial cues. The face-benefit in high-noise also correlated positively with increased functional connectivity between this region and voice-sensitive regions in the temporal lobe in the group of 16 participants with a behavioural face-benefit. In low-noise, the face-benefit was robustly associated with increased responses in the FFA and to a lesser extent the right pSTS-mFA. The findings highlight the remarkably adaptive nature of the visual network supporting voiceidentity recognition in auditory-only listening conditions.

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Section: Discussionmentioning

confidence: 98%

Visual mechanisms for voice‐identity recognition flexibly adjust to auditory noise level

Maguinness

Kriegstein

2021

Human Brain Mapping

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“…For example, it has been shown to be easier to classify a face when it is accompanied with its voice (Joassin et al, 2011). Additionally, a recent cross-modal priming study suggests that face and voice information is already integrated early in the processing stream to enhance recognition (Bülthoff and Newell, 2017). Recent frameworks to account for such effects posit that dynamic information plays a crucial role for the binding of information from several modalities, including the visual (face) and auditory (voice) modalities to enhance person recognition (Yovel and Belin, 2013).…”

Section: Introductionmentioning

confidence: 99%

Matching Unfamiliar Voices to Static and Dynamic Faces: No Evidence for a Dynamic Face Advantage in a Simultaneous Presentation Paradigm

Huestegge

2019

Front. Psychol.

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Previous research has demonstrated that humans are able to match unfamiliar voices to corresponding faces and vice versa. It has been suggested that this matching ability might be based on common underlying factors that have a characteristic impact on both faces and voices. Some researchers have additionally assumed that dynamic facial information might be especially relevant to successfully match faces to voices. In the present study, static and dynamic face-voice matching ability was compared in a simultaneous presentation paradigm. Additionally, a procedure (matching additionally supported by incidental association learning) was implemented which allowed for reliably excluding participants that did not pay sufficient attention to the task. A comparison of performance between static and dynamic face-voice matching suggested a lack of substantial differences in matching ability, suggesting that dynamic (as opposed to mere static) facial information does not contribute meaningfully to face-voice matching performance. Importantly, this conclusion was not merely derived from the lack of a statistically significant group difference in matching performance (which could principally be explained by assuming low statistical power), but from a Bayesian analysis as well as from an analysis of the 95% confidence interval (CI) of the actual effect size. The extreme border of this CI suggested a maximally plausible dynamic face advantage of less than four percentage points, which was considered way too low to indicate any theoretically meaningful dynamic face advantage. Implications regarding the underlying mechanisms of face-voice matching are discussed.

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“…At a general level, unfamiliar voices elicit slower sex judgements (Burton & Bonner, 2004), difficulty during speech shadowing or comprehension (Johnsrude et al, 2013; Kreitewolf, Gaudrain, & von Kriegstein, 2014; Levi, Winters, & Pisoni, 2011; Nygaard, Sommers, & Pisoni, 1994; Souza, Gehani, Wright, & McCloy, 2013), and weaker event-related potential (ERP) waveforms during expression judgements (Pinheiro et al, 2016). When processing vocal identity, unfamiliar voices also fail to demonstrate the usual facilitation effects when presented in synchrony or near-synchrony with their corresponding face (Gonzalez et al, 2011; Schweinberger, Kawahara, Simpson, Skuk, & Zäske, 2014), and they show no benefit through repetition priming following prior presentation of the corresponding face (Ellis, Jones, & Mosdell, 1997; Schweinberger, Herholz, & Stief, 1997; Schweinberger, Robertson, & Kaufmann, 2007; Stevenage, Hugill, & Lewis, 2012) or voice (Schweinberger, 2001) (see Bülthoff & Newell, 2017). Finally, performance in a familiar voice recognition task shows no association with performance in an unfamiliar voice discrimination task (see Cook & Wilding, 1997; van Lancker & Kreiman, 1987, Supplementary Materials).…”

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confidence: 99%

Sorting through the impact of familiarity when processing vocal identity: Results from a voice sorting task

Stevenage

Symons

Fletcher

et al. 2019

Quarterly Journal of Experimental Psychology

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The present article reports on one experiment designed to examine the importance of familiarity when processing vocal identity. A voice sorting task was used with participants who were either personally familiar or unfamiliar with three speakers. The results suggested that familiarity supported both an ability to tell different instances of the same voice together, and to tell similar instances of different voices apart. In addition, the results suggested differences between the three speakers in terms of the extent to which they were confusable, underlining the importance of vocal characteristics and stimulus selection within behavioural tasks. The results are discussed with reference to existing debates regarding the nature of stored representations as familiarity develops, and the difficulty when processing voices over faces more generally.

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Crossmodal priming of unfamiliar faces supports early interactions between voices and faces in person perception

Cited by 14 publications

References 56 publications

Visual mechanisms for voice‐identity recognition flexibly adjust to auditory noise level

Visual mechanisms for voice‐identity recognition flexibly adjust to auditory noise level

Matching Unfamiliar Voices to Static and Dynamic Faces: No Evidence for a Dynamic Face Advantage in a Simultaneous Presentation Paradigm

Sorting through the impact of familiarity when processing vocal identity: Results from a voice sorting task

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