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The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG

Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models,...

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Autores principales: Fauchon, Camille, Meunier, David, Faillenot, Isabelle, Pomares, Florence B, Bastuji, Hélène, Garcia-Larrea, Luis, Peyron, Roland
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8152828/
https://www.ncbi.nlm.nih.gov/pubmed/34296144
http://dx.doi.org/10.1093/texcom/tgaa088
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author Fauchon, Camille
Meunier, David
Faillenot, Isabelle
Pomares, Florence B
Bastuji, Hélène
Garcia-Larrea, Luis
Peyron, Roland
author_facet Fauchon, Camille
Meunier, David
Faillenot, Isabelle
Pomares, Florence B
Bastuji, Hélène
Garcia-Larrea, Luis
Peyron, Roland
author_sort Fauchon, Camille
collection PubMed
description Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models, remains unknown. Here, we used graph theory with modular analysis of fMRI data from 60 healthy participants experiencing noxious heat stimuli, of whom 36 also received audio stimulation. Brain connectivity during pain was organized in four modules matching those identified through iEEG, namely: 1) sensorimotor (SM), 2) medial fronto-cingulo-parietal (default mode-like), 3) posterior parietal-latero-frontal (central executive-like), and 4) amygdalo-hippocampal (limbic). Intrinsic overlaps existed between the pain and audio conditions in high-order areas, but also pain-specific higher small-worldness and connectivity within the sensorimotor module. Neocortical modules were interrelated via “connector hubs” in dorsolateral frontal, posterior parietal, and anterior insular cortices, the antero-insular connector being most predominant during pain. These findings provide a mechanistic picture of the brain networks architecture and support fractal-like similarities between the micro-and macrotemporal dynamics associated with pain. The anterior insula appears to play an essential role in information integration, possibly by determining priorities for the processing of information and subsequent entrance into other points of the brain connectome.
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spelling pubmed-81528282021-07-21 The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG Fauchon, Camille Meunier, David Faillenot, Isabelle Pomares, Florence B Bastuji, Hélène Garcia-Larrea, Luis Peyron, Roland Cereb Cortex Commun Original Article Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models, remains unknown. Here, we used graph theory with modular analysis of fMRI data from 60 healthy participants experiencing noxious heat stimuli, of whom 36 also received audio stimulation. Brain connectivity during pain was organized in four modules matching those identified through iEEG, namely: 1) sensorimotor (SM), 2) medial fronto-cingulo-parietal (default mode-like), 3) posterior parietal-latero-frontal (central executive-like), and 4) amygdalo-hippocampal (limbic). Intrinsic overlaps existed between the pain and audio conditions in high-order areas, but also pain-specific higher small-worldness and connectivity within the sensorimotor module. Neocortical modules were interrelated via “connector hubs” in dorsolateral frontal, posterior parietal, and anterior insular cortices, the antero-insular connector being most predominant during pain. These findings provide a mechanistic picture of the brain networks architecture and support fractal-like similarities between the micro-and macrotemporal dynamics associated with pain. The anterior insula appears to play an essential role in information integration, possibly by determining priorities for the processing of information and subsequent entrance into other points of the brain connectome. Oxford University Press 2020-11-25 /pmc/articles/PMC8152828/ /pubmed/34296144 http://dx.doi.org/10.1093/texcom/tgaa088 Text en © The Author(s) 2020. 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 (http://creativecommons.org/licenses/by/4.0/ (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
Fauchon, Camille
Meunier, David
Faillenot, Isabelle
Pomares, Florence B
Bastuji, Hélène
Garcia-Larrea, Luis
Peyron, Roland
The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG
title The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG
title_full The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG
title_fullStr The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG
title_full_unstemmed The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG
title_short The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG
title_sort modular organization of pain brain networks: an fmri graph analysis informed by intracranial eeg
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8152828/
https://www.ncbi.nlm.nih.gov/pubmed/34296144
http://dx.doi.org/10.1093/texcom/tgaa088
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