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Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates
In studies of anxiety and other affective disorders, objectively measured physiological responses have commonly been used as a proxy for measuring subjective experiences associated with pathology. However, this commonly adopted “biosignal” approach has recently been called into question on the groun...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515839/ https://www.ncbi.nlm.nih.gov/pubmed/31659269 http://dx.doi.org/10.1038/s41380-019-0520-3 |
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author | Taschereau-Dumouchel, Vincent Kawato, Mitsuo Lau, Hakwan |
author_facet | Taschereau-Dumouchel, Vincent Kawato, Mitsuo Lau, Hakwan |
author_sort | Taschereau-Dumouchel, Vincent |
collection | PubMed |
description | In studies of anxiety and other affective disorders, objectively measured physiological responses have commonly been used as a proxy for measuring subjective experiences associated with pathology. However, this commonly adopted “biosignal” approach has recently been called into question on the grounds that subjective experiences and objective physiological responses may dissociate. We performed machine-learning-based analyses on functional magnetic resonance imaging (fMRI) data to assess this issue in the case of fear. Although subjective fear and objective physiological responses were correlated in general, the respective whole-brain multivoxel decoders for the two measures were different. Some key brain regions such as the amygdala and insula appear to be primarily involved in the prediction of physiological reactivity, whereas some regions previously associated with metacognition and conscious perception, including some areas in the prefrontal cortex, appear to be primarily predictive of the subjective experience of fear. The present findings are in support of the recent call for caution in assuming a one-to-one mapping between subjective sufferings and their putative biosignals, despite the clear advantages in the latter’s being objectively and continuously measurable in physiological terms. |
format | Online Article Text |
id | pubmed-7515839 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75158392020-10-07 Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates Taschereau-Dumouchel, Vincent Kawato, Mitsuo Lau, Hakwan Mol Psychiatry Article In studies of anxiety and other affective disorders, objectively measured physiological responses have commonly been used as a proxy for measuring subjective experiences associated with pathology. However, this commonly adopted “biosignal” approach has recently been called into question on the grounds that subjective experiences and objective physiological responses may dissociate. We performed machine-learning-based analyses on functional magnetic resonance imaging (fMRI) data to assess this issue in the case of fear. Although subjective fear and objective physiological responses were correlated in general, the respective whole-brain multivoxel decoders for the two measures were different. Some key brain regions such as the amygdala and insula appear to be primarily involved in the prediction of physiological reactivity, whereas some regions previously associated with metacognition and conscious perception, including some areas in the prefrontal cortex, appear to be primarily predictive of the subjective experience of fear. The present findings are in support of the recent call for caution in assuming a one-to-one mapping between subjective sufferings and their putative biosignals, despite the clear advantages in the latter’s being objectively and continuously measurable in physiological terms. Nature Publishing Group UK 2019-10-29 2020 /pmc/articles/PMC7515839/ /pubmed/31659269 http://dx.doi.org/10.1038/s41380-019-0520-3 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Taschereau-Dumouchel, Vincent Kawato, Mitsuo Lau, Hakwan Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates |
title | Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates |
title_full | Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates |
title_fullStr | Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates |
title_full_unstemmed | Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates |
title_short | Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates |
title_sort | multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515839/ https://www.ncbi.nlm.nih.gov/pubmed/31659269 http://dx.doi.org/10.1038/s41380-019-0520-3 |
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