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Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments
Vocal emotion recognition, a key determinant to analyzing a speaker’s emotional state, is known to be impaired following cerebellar dysfunctions. Nevertheless, its possible functional integration in the large-scale brain network subtending emotional prosody recognition has yet to be explored. We adm...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883615/ https://www.ncbi.nlm.nih.gov/pubmed/36726795 http://dx.doi.org/10.1093/texcom/tgad002 |
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author | Thomasson, Marine Ceravolo, Leonardo Corradi-Dell’Acqua, Corrado Mantelli, Amélie Saj, Arnaud Assal, Frédéric Grandjean, Didier Péron, Julie |
author_facet | Thomasson, Marine Ceravolo, Leonardo Corradi-Dell’Acqua, Corrado Mantelli, Amélie Saj, Arnaud Assal, Frédéric Grandjean, Didier Péron, Julie |
author_sort | Thomasson, Marine |
collection | PubMed |
description | Vocal emotion recognition, a key determinant to analyzing a speaker’s emotional state, is known to be impaired following cerebellar dysfunctions. Nevertheless, its possible functional integration in the large-scale brain network subtending emotional prosody recognition has yet to be explored. We administered an emotional prosody recognition task to patients with right versus left-hemispheric cerebellar lesions and a group of matched controls. We explored the lesional correlates of vocal emotion recognition in patients through a network-based analysis by combining a neuropsychological approach for lesion mapping with normative brain connectome data. Results revealed impaired recognition among patients for neutral or negative prosody, with poorer sadness recognition performances by patients with right cerebellar lesion. Network-based lesion-symptom mapping revealed that sadness recognition performances were linked to a network connecting the cerebellum with left frontal, temporal, and parietal cortices. Moreover, when focusing solely on a subgroup of patients with right cerebellar damage, sadness recognition performances were associated with a more restricted network connecting the cerebellum to the left parietal lobe. As the left hemisphere is known to be crucial for the processing of short segmental information, these results suggest that a corticocerebellar network operates on a fine temporal scale during vocal emotion decoding. |
format | Online Article Text |
id | pubmed-9883615 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98836152023-01-31 Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments Thomasson, Marine Ceravolo, Leonardo Corradi-Dell’Acqua, Corrado Mantelli, Amélie Saj, Arnaud Assal, Frédéric Grandjean, Didier Péron, Julie Cereb Cortex Commun Original Article Vocal emotion recognition, a key determinant to analyzing a speaker’s emotional state, is known to be impaired following cerebellar dysfunctions. Nevertheless, its possible functional integration in the large-scale brain network subtending emotional prosody recognition has yet to be explored. We administered an emotional prosody recognition task to patients with right versus left-hemispheric cerebellar lesions and a group of matched controls. We explored the lesional correlates of vocal emotion recognition in patients through a network-based analysis by combining a neuropsychological approach for lesion mapping with normative brain connectome data. Results revealed impaired recognition among patients for neutral or negative prosody, with poorer sadness recognition performances by patients with right cerebellar lesion. Network-based lesion-symptom mapping revealed that sadness recognition performances were linked to a network connecting the cerebellum with left frontal, temporal, and parietal cortices. Moreover, when focusing solely on a subgroup of patients with right cerebellar damage, sadness recognition performances were associated with a more restricted network connecting the cerebellum to the left parietal lobe. As the left hemisphere is known to be crucial for the processing of short segmental information, these results suggest that a corticocerebellar network operates on a fine temporal scale during vocal emotion decoding. Oxford University Press 2023-01-11 /pmc/articles/PMC9883615/ /pubmed/36726795 http://dx.doi.org/10.1093/texcom/tgad002 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Thomasson, Marine Ceravolo, Leonardo Corradi-Dell’Acqua, Corrado Mantelli, Amélie Saj, Arnaud Assal, Frédéric Grandjean, Didier Péron, Julie Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments |
title | Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments |
title_full | Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments |
title_fullStr | Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments |
title_full_unstemmed | Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments |
title_short | Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments |
title_sort | dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883615/ https://www.ncbi.nlm.nih.gov/pubmed/36726795 http://dx.doi.org/10.1093/texcom/tgad002 |
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