The path of voices in our brain

Morillon, Benjamin; Arnal, Luc H.; Belin, Pascal

doi:10.1371/journal.pbio.3001742

Cited by 3 publications

(2 citation statements)

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“…For instance, while selective responses to auditory categories like voices and music occur bilaterally in associative auditory regions 22 , 23 , 94 , processing of individual sentences and melodies occurs in the left and right hemispheres, respectively 16 . In other words, neural response patterns shared across all stimuli of the same domain (voices, music) are present bilaterally, while neural patterns discriminating different instances of the same domain are more focal and lateralised 95 ). Finally, the general modular organisation of the entire network and global clustering and efficiency were not significantly changed, and their stability might reflect late task-related processing remaining stable across conditions, such as decision-making for meaningful auditory stimuli.…”

Section: Discussionmentioning

confidence: 99%

Spectrotemporal cues and attention jointly modulate fMRI network topology for sentence and melody perception

Haiduk,

Zatorre,

Benjamin

et al. 2024

Sci Rep

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Speech and music are two fundamental modes of human communication. Lateralisation of key processes underlying their perception has been related both to the distinct sensitivity to low-level spectrotemporal acoustic features and to top-down attention. However, the interplay between bottom-up and top-down processes needs to be clarified. In the present study, we investigated the contribution of acoustics and attention to melodies or sentences to lateralisation in fMRI functional network topology. We used sung speech stimuli selectively filtered in temporal or spectral modulation domains with crossed and balanced verbal and melodic content. Perception of speech decreased with degradation of temporal information, whereas perception of melodies decreased with spectral degradation. Applying graph theoretical metrics on fMRI connectivity matrices, we found that local clustering, reflecting functional specialisation, linearly increased when spectral or temporal cues crucial for the task goal were incrementally degraded. These effects occurred in a bilateral fronto-temporo-parietal network for processing temporally degraded sentences and in right auditory regions for processing spectrally degraded melodies. In contrast, global topology remained stable across conditions. These findings suggest that lateralisation for speech and music partially depends on an interplay of acoustic cues and task goals under increased attentional demands.

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Section: Discussionmentioning

confidence: 99%

Spectrotemporal cues and attention jointly modulate fMRI network topology for sentence and melody perception

Haiduk,

Zatorre,

Benjamin

et al. 2024

Sci Rep

Self Cite

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“…In the auditory domain, DNNs have been shown to provide valuable representations—so called feature or latent spaces—for modeling the cerebral processing of sound (brain encoding) (speech: Kell et al, 2018, Millet et al, 2022; semantic content Caucheteux et al, 2022, Caucheteux et King, 2022, Caucheteux et al, 2023, Giordano et al, 2023; music: Güçlü et al, 2016), or reconstructing the stimuli listened by a participant (brain decoding) (Akbari et al, 2019). They have not yet been used to explain cerebral representations of identity-related information, due in part to the focus on speech information (von Kriegstein 2003; Morillon et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Reconstructing Voice Identity from Noninvasive Auditory Cortex Recordings

Lamothe,

Thoret,

Trapeau

et al. 2024

Preprint

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The cerebral processing of voice information is known to engage Temporal Voice Areas (TVAs) that respond preferentially to conspecific vocalizations. But how voice information related to the stable physical characteristics of the speaker such as gender, age or identity is represented by neuronal populations in these areas remains poorly understood. Here we used a deep neural network (DNN) to generate a high-level, small-dimension representational space of voice stimuli—the ‘voice latent space’ (VLS)—and examined its linear relation with cerebral activity via encoding, representational similarity and decoding analyses. We find that the VLS maps onto fMRI measures of cerebral activity in response to tens of thousands of voice stimuli from hundreds of different speaker identities, and better accounts for the representational geometry for speaker identity in the TVAs than in A1. Moreover, the VLS allowed TVA-based reconstructions of voice stimuli that preserved important aspects of speaker gender and identity as assessed by both machine classifiers and human listeners. These results demonstrate that a low-dimensional, DNN-derived space accounts well for cerebral voice representations and provide insights into representational differences between A1 and the TVAs, paving the way to noninvasive brain-computer interface applications.

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rTMS of the auditory association cortex improves speech intelligibility in patients with sensorineural hearing loss

Neri,

Cappello,

Viberti

et al. 2024

Clinical Neurophysiology

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The path of voices in our brain

Abstract: A recent study by Rupp and colleagues in PLOS Biology capitalises on human intracranial recordings to describe the spatiotemporal pattern of neural activity leading to voice-selective responses in associative auditory cortex.

Cited by 3 publications

References 10 publications

Spectrotemporal cues and attention jointly modulate fMRI network topology for sentence and melody perception

Spectrotemporal cues and attention jointly modulate fMRI network topology for sentence and melody perception

Reconstructing Voice Identity from Noninvasive Auditory Cortex Recordings

rTMS of the auditory association cortex improves speech intelligibility in patients with sensorineural hearing loss

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