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The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure

Esin Karahan, Luke Tait Orcid Logo, Ruoguang Si, Ayşegül Özkan, Maciek J. Szul Orcid Logo, Kim S. Graham, Andrew D. Lawrence Orcid Logo, Jiaxiang Zhang Orcid Logo

Communications Biology, Volume: 5, Issue: 1

Swansea University Author: Jiaxiang Zhang Orcid Logo

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DOI (Published version): 10.1038/s42003-022-03974-w

Abstract

Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multi...

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Published in: Communications Biology
ISSN: 2399-3642
Published: Springer Science and Business Media LLC 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa61343
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Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7&#x2009;T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. 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spelling 2022-10-11T12:35:48.2702623 v2 61343 2022-09-26 The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure 555e06e0ed9a87608f2d035b3bde3a87 0000-0002-4758-0394 Jiaxiang Zhang Jiaxiang Zhang true false 2022-09-26 SCS Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multimodal brain connectivity. Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7 T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. Our findings depict the inter-relationship between the ISV of brain connectivity from multiple modalities, and highlight the role of tissue microstructure underpinning the ISV. Journal Article Communications Biology 5 1 Springer Science and Business Media LLC 2399-3642 23 9 2022 2022-09-23 10.1038/s42003-022-03974-w Data availability:DWI, MEG and 7 T MRI data that support the findings of this study and data from all analyses are available in OSF with the unique identifier [https://doi.org/10.17605/osf.io/rqj8a]. A part of data used in the preparation of this work were obtained from the Cam-CAN repository (https://www.cam-can.org). COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University This study was supported by the European Research Council (716321), the UK Medical Research Council (MR/N01233X/1) and a Wellcome Trust Institutional Strategic Support Fund (ISSF). This research was funded in part by the Wellcome Trust (104943/Z/14/Z). R.S. was supported by a PhD studentship from the China Scholarship Council. A.Ö. was supported by a PhD studentship from the Turkish Ministry of National Education. M.J.S. was supported by a PhD studentship from Cardiff University School of Psychology.Cam-CAN funding was provided by the UK Biotechnology and Biological Sciences Research Council (BB/H008217/1), together with support from the UK Medical Research Council and the University of Cambridge, UK. 2022-10-11T12:35:48.2702623 2022-09-26T11:36:51.8674565 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Esin Karahan 1 Luke Tait 0000-0002-2351-5328 2 Ruoguang Si 3 Ayşegül Özkan 4 Maciek J. Szul 0000-0002-4116-8470 5 Kim S. Graham 6 Andrew D. Lawrence 0000-0001-6705-2110 7 Jiaxiang Zhang 0000-0002-4758-0394 8 61343__25408__6102cc897b994fe9965922630f12cea5.pdf 61343_VoR.pdf 2022-10-11T12:34:25.4742713 Output 2750484 application/pdf Version of Record true This article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure
spellingShingle The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure
Jiaxiang Zhang
title_short The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure
title_full The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure
title_fullStr The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure
title_full_unstemmed The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure
title_sort The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure
author_id_str_mv 555e06e0ed9a87608f2d035b3bde3a87
author_id_fullname_str_mv 555e06e0ed9a87608f2d035b3bde3a87_***_Jiaxiang Zhang
author Jiaxiang Zhang
author2 Esin Karahan
Luke Tait
Ruoguang Si
Ayşegül Özkan
Maciek J. Szul
Kim S. Graham
Andrew D. Lawrence
Jiaxiang Zhang
format Journal article
container_title Communications Biology
container_volume 5
container_issue 1
publishDate 2022
institution Swansea University
issn 2399-3642
doi_str_mv 10.1038/s42003-022-03974-w
publisher Springer Science and Business Media LLC
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
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description Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multimodal brain connectivity. Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7 T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. Our findings depict the inter-relationship between the ISV of brain connectivity from multiple modalities, and highlight the role of tissue microstructure underpinning the ISV.
published_date 2022-09-23T04:20:07Z
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