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On the neural networks of empathy: A principal component analysis of an fMRI study
BACKGROUND: Human emotional expressions serve an important communicatory role allowing the rapid transmission of valence information among individuals. We aimed at exploring the neural networks mediating the recognition of and empathy with human facial expressions of emotion. METHODS: A principal co...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2564949/ https://www.ncbi.nlm.nih.gov/pubmed/18798977 http://dx.doi.org/10.1186/1744-9081-4-41 |
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author | Nomi, Jason S Scherfeld, Dag Friederichs, Skara Schäfer, Ralf Franz, Matthias Wittsack, Hans-Jörg Azari, Nina P Missimer, John Seitz, Rüdiger J |
author_facet | Nomi, Jason S Scherfeld, Dag Friederichs, Skara Schäfer, Ralf Franz, Matthias Wittsack, Hans-Jörg Azari, Nina P Missimer, John Seitz, Rüdiger J |
author_sort | Nomi, Jason S |
collection | PubMed |
description | BACKGROUND: Human emotional expressions serve an important communicatory role allowing the rapid transmission of valence information among individuals. We aimed at exploring the neural networks mediating the recognition of and empathy with human facial expressions of emotion. METHODS: A principal component analysis was applied to event-related functional magnetic imaging (fMRI) data of 14 right-handed healthy volunteers (29 +/- 6 years). During scanning, subjects viewed happy, sad and neutral face expressions in the following conditions: emotion recognition, empathizing with emotion, and a control condition of simple object detection. Functionally relevant principal components (PCs) were identified by planned comparisons at an alpha level of p < 0.001. RESULTS: Four PCs revealed significant differences in variance patterns of the conditions, thereby revealing distinct neural networks: mediating facial identification (PC 1), identification of an expressed emotion (PC 2), attention to an expressed emotion (PC 12), and sense of an emotional state (PC 27). CONCLUSION: Our findings further the notion that the appraisal of human facial expressions involves multiple neural circuits that process highly differentiated cognitive aspects of emotion. |
format | Text |
id | pubmed-2564949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-25649492008-10-09 On the neural networks of empathy: A principal component analysis of an fMRI study Nomi, Jason S Scherfeld, Dag Friederichs, Skara Schäfer, Ralf Franz, Matthias Wittsack, Hans-Jörg Azari, Nina P Missimer, John Seitz, Rüdiger J Behav Brain Funct Research BACKGROUND: Human emotional expressions serve an important communicatory role allowing the rapid transmission of valence information among individuals. We aimed at exploring the neural networks mediating the recognition of and empathy with human facial expressions of emotion. METHODS: A principal component analysis was applied to event-related functional magnetic imaging (fMRI) data of 14 right-handed healthy volunteers (29 +/- 6 years). During scanning, subjects viewed happy, sad and neutral face expressions in the following conditions: emotion recognition, empathizing with emotion, and a control condition of simple object detection. Functionally relevant principal components (PCs) were identified by planned comparisons at an alpha level of p < 0.001. RESULTS: Four PCs revealed significant differences in variance patterns of the conditions, thereby revealing distinct neural networks: mediating facial identification (PC 1), identification of an expressed emotion (PC 2), attention to an expressed emotion (PC 12), and sense of an emotional state (PC 27). CONCLUSION: Our findings further the notion that the appraisal of human facial expressions involves multiple neural circuits that process highly differentiated cognitive aspects of emotion. BioMed Central 2008-09-17 /pmc/articles/PMC2564949/ /pubmed/18798977 http://dx.doi.org/10.1186/1744-9081-4-41 Text en Copyright © 2008 Nomi et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Nomi, Jason S Scherfeld, Dag Friederichs, Skara Schäfer, Ralf Franz, Matthias Wittsack, Hans-Jörg Azari, Nina P Missimer, John Seitz, Rüdiger J On the neural networks of empathy: A principal component analysis of an fMRI study |
title | On the neural networks of empathy: A principal component analysis of an fMRI study |
title_full | On the neural networks of empathy: A principal component analysis of an fMRI study |
title_fullStr | On the neural networks of empathy: A principal component analysis of an fMRI study |
title_full_unstemmed | On the neural networks of empathy: A principal component analysis of an fMRI study |
title_short | On the neural networks of empathy: A principal component analysis of an fMRI study |
title_sort | on the neural networks of empathy: a principal component analysis of an fmri study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2564949/ https://www.ncbi.nlm.nih.gov/pubmed/18798977 http://dx.doi.org/10.1186/1744-9081-4-41 |
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