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Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex

Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these 2 types of neural activity remains unknown. Here, we map electromagnetic networks (m...

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Detalles Bibliográficos
Autores principales: Shafiei, Golia, Baillet, Sylvain, Misic, Bratislav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371256/
https://www.ncbi.nlm.nih.gov/pubmed/35914002
http://dx.doi.org/10.1371/journal.pbio.3001735
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author Shafiei, Golia
Baillet, Sylvain
Misic, Bratislav
author_facet Shafiei, Golia
Baillet, Sylvain
Misic, Bratislav
author_sort Shafiei, Golia
collection PubMed
description Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these 2 types of neural activity remains unknown. Here, we map electromagnetic networks (measured using magnetoencephalography (MEG)) to haemodynamic networks (measured using functional magnetic resonance imaging (fMRI)). We find that the relationship between the 2 modalities is regionally heterogeneous and systematically follows the cortical hierarchy, with close correspondence in unimodal cortex and poor correspondence in transmodal cortex. Comparison with the BigBrain histological atlas reveals that electromagnetic–haemodynamic coupling is driven by laminar differentiation and neuron density, suggesting that the mapping between the 2 modalities can be explained by cytoarchitectural variation. Importantly, haemodynamic connectivity cannot be explained by electromagnetic activity in a single frequency band, but rather arises from the mixing of multiple neurophysiological rhythms. Correspondence between the two is largely driven by MEG functional connectivity at the beta (15 to 29 Hz) frequency band. Collectively, these findings demonstrate highly organized but only partly overlapping patterns of connectivity in MEG and fMRI functional networks, opening fundamentally new avenues for studying the relationship between cortical microarchitecture and multimodal connectivity patterns.
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spelling pubmed-93712562022-08-12 Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex Shafiei, Golia Baillet, Sylvain Misic, Bratislav PLoS Biol Research Article Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these 2 types of neural activity remains unknown. Here, we map electromagnetic networks (measured using magnetoencephalography (MEG)) to haemodynamic networks (measured using functional magnetic resonance imaging (fMRI)). We find that the relationship between the 2 modalities is regionally heterogeneous and systematically follows the cortical hierarchy, with close correspondence in unimodal cortex and poor correspondence in transmodal cortex. Comparison with the BigBrain histological atlas reveals that electromagnetic–haemodynamic coupling is driven by laminar differentiation and neuron density, suggesting that the mapping between the 2 modalities can be explained by cytoarchitectural variation. Importantly, haemodynamic connectivity cannot be explained by electromagnetic activity in a single frequency band, but rather arises from the mixing of multiple neurophysiological rhythms. Correspondence between the two is largely driven by MEG functional connectivity at the beta (15 to 29 Hz) frequency band. Collectively, these findings demonstrate highly organized but only partly overlapping patterns of connectivity in MEG and fMRI functional networks, opening fundamentally new avenues for studying the relationship between cortical microarchitecture and multimodal connectivity patterns. Public Library of Science 2022-08-01 /pmc/articles/PMC9371256/ /pubmed/35914002 http://dx.doi.org/10.1371/journal.pbio.3001735 Text en © 2022 Shafiei et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shafiei, Golia
Baillet, Sylvain
Misic, Bratislav
Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex
title Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex
title_full Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex
title_fullStr Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex
title_full_unstemmed Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex
title_short Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex
title_sort human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371256/
https://www.ncbi.nlm.nih.gov/pubmed/35914002
http://dx.doi.org/10.1371/journal.pbio.3001735
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