Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties
Resting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organizat...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811922009004 |
| _version_ | 1797961091846766592 |
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| author | Soojin Lee Janine D. Bijsterbosch Fidel Alfaro Almagro Lloyd Elliott Paul McCarthy Bernd Taschler Roser Sala-Llonch Christian F. Beckmann Eugene P. Duff Stephen M. Smith Gwenaëlle Douaud |
| author_facet | Soojin Lee Janine D. Bijsterbosch Fidel Alfaro Almagro Lloyd Elliott Paul McCarthy Bernd Taschler Roser Sala-Llonch Christian F. Beckmann Eugene P. Duff Stephen M. Smith Gwenaëlle Douaud |
| author_sort | Soojin Lee |
| collection | DOAJ |
| description | Resting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organization, intersubject variability in the networks’ spontaneous fluctuations may be associated with individuals’ clinical, physiological, cognitive, and genetic traits. Here, we investigated resting-state fMRI data along with extensive clinical, lifestyle, and genetic data collected from 37,842 UK Biobank participants, with the object of elucidating intersubject variability in the fluctuation amplitudes of RSNs. Functional properties of the RSN amplitudes were first examined by analyzing correlations with the well-established between-network functional connectivity. It was found that a network amplitude is highly correlated with the mean strength of the functional connectivity that the network has with the other networks. Intersubject clustering analysis showed the amplitudes are most strongly correlated with age, cardiovascular factors, body composition, blood cell counts, lung function, and sex, with some differences in the correlation strengths between sensory and cognitive RSNs. Genome-wide association studies (GWASs) of RSN amplitudes identified several significant genetic variants reported in previous GWASs for their implications in sleep duration. We provide insight into key factors determining RSN amplitudes and demonstrate that intersubject variability of the amplitudes primarily originates from differences in temporal synchrony between functionally linked brain regions, rather than differences in the magnitude of raw voxelwise BOLD signal changes. This finding additionally revealed intriguing differences between sensory and cognitive RSNs with respect to sex effects on temporal synchrony and provided evidence suggesting that synchronous coactivations of functionally linked brain regions, and magnitudes of BOLD signal changes, may be related to different genetic mechanisms. These results underscore that intersubject variability of the amplitudes in health and disease need to be interpreted largely as a measure of the sum of within-network temporal synchrony and amplitudes of BOLD signals, with a dominant contribution from the former. |
| first_indexed | 2024-04-11T00:55:03Z |
| format | Article |
| id | doaj.art-094ea34459044324aa78533eeb8a29d9 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-04-11T00:55:03Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-094ea34459044324aa78533eeb8a29d92023-01-05T06:23:23ZengElsevierNeuroImage1095-95722023-01-01265119779Amplitudes of resting-state functional networks – investigation into their correlates and biophysical propertiesSoojin Lee0Janine D. Bijsterbosch1Fidel Alfaro Almagro2Lloyd Elliott3Paul McCarthy4Bernd Taschler5Roser Sala-Llonch6Christian F. Beckmann7Eugene P. Duff8Stephen M. Smith9Gwenaëlle Douaud10Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Pacific Parkinson's Research Institute, University of British Columbia, Canada; Corresponding author at: FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford OX3 9DU, UK.Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Mallinckrodt Institute of Radiology, Washington University Medical School, Washington University in St Louis, USACentre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UKDepartment of Statistics and Actuarial Science, Simon Fraser University (SFU), CanadaCentre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UKCentre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UKDepartment of Biomedicine, Institute of Neurosciences, University of Barcelona, SpainCentre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the NetherlandsCentre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Department of Brain Sciences, Imperial College London, UK Dementia Research Institute, London UKCentre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UKCentre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UKResting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organization, intersubject variability in the networks’ spontaneous fluctuations may be associated with individuals’ clinical, physiological, cognitive, and genetic traits. Here, we investigated resting-state fMRI data along with extensive clinical, lifestyle, and genetic data collected from 37,842 UK Biobank participants, with the object of elucidating intersubject variability in the fluctuation amplitudes of RSNs. Functional properties of the RSN amplitudes were first examined by analyzing correlations with the well-established between-network functional connectivity. It was found that a network amplitude is highly correlated with the mean strength of the functional connectivity that the network has with the other networks. Intersubject clustering analysis showed the amplitudes are most strongly correlated with age, cardiovascular factors, body composition, blood cell counts, lung function, and sex, with some differences in the correlation strengths between sensory and cognitive RSNs. Genome-wide association studies (GWASs) of RSN amplitudes identified several significant genetic variants reported in previous GWASs for their implications in sleep duration. We provide insight into key factors determining RSN amplitudes and demonstrate that intersubject variability of the amplitudes primarily originates from differences in temporal synchrony between functionally linked brain regions, rather than differences in the magnitude of raw voxelwise BOLD signal changes. This finding additionally revealed intriguing differences between sensory and cognitive RSNs with respect to sex effects on temporal synchrony and provided evidence suggesting that synchronous coactivations of functionally linked brain regions, and magnitudes of BOLD signal changes, may be related to different genetic mechanisms. These results underscore that intersubject variability of the amplitudes in health and disease need to be interpreted largely as a measure of the sum of within-network temporal synchrony and amplitudes of BOLD signals, with a dominant contribution from the former.http://www.sciencedirect.com/science/article/pii/S1053811922009004Resting-state fMRINetwork amplitudeDual regressionTemporal synchronyUK BiobankGWAS |
| spellingShingle | Soojin Lee Janine D. Bijsterbosch Fidel Alfaro Almagro Lloyd Elliott Paul McCarthy Bernd Taschler Roser Sala-Llonch Christian F. Beckmann Eugene P. Duff Stephen M. Smith Gwenaëlle Douaud Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties NeuroImage Resting-state fMRI Network amplitude Dual regression Temporal synchrony UK Biobank GWAS |
| title | Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties |
| title_full | Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties |
| title_fullStr | Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties |
| title_full_unstemmed | Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties |
| title_short | Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties |
| title_sort | amplitudes of resting state functional networks investigation into their correlates and biophysical properties |
| topic | Resting-state fMRI Network amplitude Dual regression Temporal synchrony UK Biobank GWAS |
| url | http://www.sciencedirect.com/science/article/pii/S1053811922009004 |
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