The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG.
acute pain
functional connectivity
graph theory
intracranial EEG
network hubs
Journal
Cerebral cortex communications
ISSN: 2632-7376
Titre abrégé: Cereb Cortex Commun
Pays: United States
ID NLM: 101767128
Informations de publication
Date de publication:
2020
2020
Historique:
received:
17
06
2020
revised:
05
10
2020
accepted:
16
11
2020
entrez:
23
7
2021
pubmed:
24
7
2021
medline:
24
7
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 34296144
doi: 10.1093/texcom/tgaa088
pii: tgaa088
pmc: PMC8152828
doi:
Types de publication
Journal Article
Langues
eng
Pagination
tgaa088Informations de copyright
© The Author(s) 2020. Published by Oxford University Press.
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