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. 2022 Jul:214:102278.
doi: 10.1016/j.pneurobio.2022.102278. Epub 2022 May 2.

Affective speech modulates a cortico-limbic network in real time

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Affective speech modulates a cortico-limbic network in real time

Florence Steiner et al. Prog Neurobiol. 2022 Jul.

Abstract

Affect signaling in human communication involves cortico-limbic brain systems for affect information decoding, such as expressed in vocal intonations during affective speech. Both, the affecto-acoustic speech profile of speakers and the cortico-limbic affect recognition network of listeners were previously identified using non-social and non-adaptive research protocols. However, these protocols neglected the inherent socio-dyadic nature of affective communication, thus underestimating the real-time adaptive dynamics of affective speech that maximize listeners' neural effects and affect recognition. To approximate this socio-adaptive and neural context of affective communication, we used an innovative real-time neuroimaging setup that linked speakers' live affective speech production with listeners' limbic brain signals that served as a proxy for affect recognition. We show that affective speech communication is acoustically more distinctive, adaptive, and individualized in a live adaptive setting and more efficiently capitalizes on neural affect decoding mechanisms in limbic and associated networks than non-adaptive affective speech communication. Only live affective speech produced in adaption to listeners' limbic signals was closely linked to their emotion recognition as quantified by speakers' acoustics and listeners' emotional rating correlations. Furthermore, while live and adaptive aggressive speaking directly modulated limbic activity in listeners, joyful speaking modulated limbic activity in connection with the ventral striatum that is, amongst others, involved in the processing of pleasure. Thus, evolved neural mechanisms for affect decoding seem largely optimized for interactive and individually adaptive communicative contexts.

Keywords: Amygdala; Emotion; FMRI; Neural network; Neurofeedback; Voice.

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