Auditory cortical micro-networks show differential connectivity during voice and speech processing in humans

Steiner, Florence; Bobin, Marine; Frühholz, Sascha

doi:10.1038/s42003-021-02328-2

Cited by 4 publications

(4 citation statements)

References 75 publications

(133 reference statements)

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“…The neural mechanisms specifically underpinning the extraction/representation of glimpsed vocal information in noise are relatively unknown, though regions showing selective sensitivity for human vocal information are prime candidates. Auditory cortical (AC) regions are consistently implicated in similar tasks, demonstrating responsiveness to ‘human voice’ specific acoustic patterns (Staib & Frühholz, 2020); involvement in voice signal detection/discrimination tasks (Montes-Lourido et al, 2021; Staib & Frühholz, 2022; Steiner et al, 2021), and responsiveness to discriminative acoustic features of socio-affective voice information (Frühholz et al, 2012, 2016; Frühholz & Grandjean, 2013c; Pannese et al, 2016). In particular, the bilateral medial superior temporal gyrus and superior temporal sulcus have are preferentially recruited by auditory stimuli with more harmonic structure and higher harmonic-to-noise ratio (more human voice like) (Lewis et al, 2009), with a left- lateralised bias for human stimuli.…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Extracting Auditory Emotion in Noise: A distributed auxiliary auditory network supporting affect processing of non-predictably obscured vocalisations

Swanborough,

Frühholz

2024

Preprint

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Decoding affect information encoded within a vocally produced signal is a key part of daily communication. The acoustic channels that carry the affect information, however, are not uniformly distributed across a spectrotemporal space meaning that natural listening environments with dynamic, competing noise may unpredictably obscure some spectrotemporal regions of the vocalisation, reducing the potential information available to the listener. In this study, we utilise behavioural and functional MRI investigations to first assess which spectrotemporal regions of a human vocalisation contribute to affect perception in the listener, and then use a reverse-correlation fMRI analysis to see which structures underpin this perceptually challenging task when categorisation relevant acoustic information is unmasked by noise. Our results show that, despite the challenging task and non-uniformity of contributing spectral regions of affective vocalizations, a distributed network of (non-primary auditory) brain regions in the frontal cortex, basal ganglia, and lateral limbic regions supports affect processing in noise. Given the conditions for recruitment and previously established functional contributions of these regions, we propose that this task is underpinned by a reciprocal network between frontal cortical regions and ventral limbic regions that assist in flexible adaptation and tuning to stimuli, while a hippocampal and parahippocampal regions support the auditory system’s processing of the degraded auditory information via associative and contextual processing.

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Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Extracting Auditory Emotion in Noise: A distributed auxiliary auditory network supporting affect processing of non-predictably obscured vocalisations

Swanborough,

Frühholz

2024

Preprint

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“…Unlike clear affective expressions in voices which represent categorical certainty as predicted by the second hypothesis, ambiguous vocal affect might trigger computations in the IFC given their challenging perceptual and cognitive processing according to the first hypothesis. Both cases might additionally require integrated IFC-STC functioning in terms of neural connectivity (Roswandowitz, Swanborough et al 2020), either for top-down IFC-to-STC facilitations or as co-representations of categorical affective information (Steiner, Bobin et al 2021). The use of transcranial magnetic stimulation (TMS) appears to be a reliable and non-invasive option to especially inhibit a proper functioning of computations performed in the IFC in this context.…”

Section: Introductionmentioning

confidence: 99%

Disrupting inferior frontal cortex activity alters affect decoding efficiency from clear but not from ambiguous affective speech

Ceravolo

Moisa

Grandjean

et al. 2021

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The evaluation of socio-affective sound information is accomplished by the primate neural auditory cortex in collaboration with limbic and inferior frontal brain nodes. For the latter, activity in inferior frontal cortex (IFC) is often observed during classification of voice sounds, especially if they carry affective information. Partly opposing views have been proposed, with IFC either coding cognitive processing challenges in case of sensory ambiguity or representing categorical object and affect information for clear vocalizations. Here, we presented clear and ambiguous affective speech to two groups of human participants during neuroimaging, while in one group we inhibited right IFC activity with transcranial magnetic stimulation (TMS) prior to brain scanning. Inhibition of IFC activity led to partly faster affective decisions, more accurate choice probabilities and reduced auditory cortical activity for clear affective speech, while fronto-limbic connectivity increased for clear vocalizations. This indicates that IFC inhibition might lead to a more intuitive and efficient processing of affect information in voices. Contrarily, normal IFC activity might represent a more deliberate form of affective sound processing (i.e., enforcing cognitive analysis) that flags categorial sound decisions with precaution (i.e., representation of categorial uncertainty). This would point to an intermediate functional property of the IFC between previously assumed mechanisms.TeaserInferior frontal cortex enforces cognitive analyses during affect decisions with different levels of sensory ambiguity.

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“…First, we determined the general frontotemporal-limbic neural network for processing such communicative signals independent of variations on the trait dimension. This network comprised low-and higher-order AC, (pre-)motor regions, and infero-orbital frontal regions as previously described [38][39][40], with additional amygdala and ACC activity during the processing of non-speech voice sounds given their higher socioaffective nature [89]. Within this broader neural network for voice and speech processing, we then tested if activity levels would depend on psychopathic and autistic trait scores.…”

Section: Discussionmentioning

confidence: 97%

“…This social from non-social sound separation is accomplished by sensory brain systems in the auditory cortex (AC) [ 38 ]. In neurotypicals, neural “voice areas” (VA) in the STC have been identified that support voice and speech sound detection [ 39 , 40 ], and given their social voice signal detection properties, the VA neural patterns might be differentially impaired in psychopathy.…”

Section: Introductionmentioning

confidence: 99%

Psychopathic and autistic traits differentially influence the neural mechanisms of social cognition from communication signals

et al. 2022

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Psychopathy is associated with severe deviations in social behavior and cognition. While previous research described such cognitive and neural alterations in the processing of rather specific social information from human expressions, some open questions remain concerning central and differential neurocognitive deficits underlying psychopathic behavior. Here we investigated three rather unexplored factors to explain these deficits, first, by assessing psychopathy subtypes in social cognition, second, by investigating the discrimination of social communication sounds (speech, non-speech) from other non-social sounds, and third, by determining the neural overlap in social cognition impairments with autistic traits, given potential common deficits in the processing of communicative voice signals. The study was exploratory with a focus on how psychopathic and autistic traits differentially influence the function of social cognitive and affective brain networks in response to social voice stimuli. We used a parametric data analysis approach from a sample of 113 participants (47 male, 66 female) with ages ranging between 18 and 40 years (mean 25.59, SD 4.79). Our data revealed four important findings. First, we found a phenotypical overlap between secondary but not primary psychopathy with autistic traits. Second, primary psychopathy showed various neural deficits in neural voice processing nodes (speech, non-speech voices) and in brain systems for social cognition (mirroring, mentalizing, empathy, emotional contagion). Primary psychopathy also showed deficits in the basal ganglia (BG) system that seems specific to the social decoding of communicative voice signals. Third, neural deviations in secondary psychopathy were restricted to social mirroring and mentalizing impairments, but with additional and so far undescribed deficits at the level of auditory sensory processing, potentially concerning deficits in ventral auditory stream mechanisms (auditory object identification). Fourth, high autistic traits also revealed neural deviations in sensory cortices, but rather in the dorsal auditory processing streams (communicative context encoding). Taken together, social cognition of voice signals shows considerable deviations in psychopathy, with differential and newly described deficits in the BG system in primary psychopathy and at the neural level of sensory processing in secondary psychopathy. These deficits seem especially triggered during the social cognition from vocal communication signals.

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Auditory cortical micro-networks show differential connectivity during voice and speech processing in humans

Cited by 4 publications

References 75 publications

WITHDRAWN: Extracting Auditory Emotion in Noise: A distributed auxiliary auditory network supporting affect processing of non-predictably obscured vocalisations

WITHDRAWN: Extracting Auditory Emotion in Noise: A distributed auxiliary auditory network supporting affect processing of non-predictably obscured vocalisations

Disrupting inferior frontal cortex activity alters affect decoding efficiency from clear but not from ambiguous affective speech

Psychopathic and autistic traits differentially influence the neural mechanisms of social cognition from communication signals

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