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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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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. |
format | Online Article Text |
id | pubmed-9371256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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