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Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping
Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networ...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107614/ https://www.ncbi.nlm.nih.gov/pubmed/35189361 http://dx.doi.org/10.1016/j.neuroimage.2022.119013 |
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author | Iraji, A. Faghiri, A. Fu, Z. Kochunov, P. Adhikari, B.M. Belger, A. Ford, J.M. McEwen, S. Mathalon, D.H. Pearlson, G.D. Potkin, S.G. Preda, A. Turner, J.A. Van Erp, T.G.M. Chang, C. Calhoun, V.D. |
author_facet | Iraji, A. Faghiri, A. Fu, Z. Kochunov, P. Adhikari, B.M. Belger, A. Ford, J.M. McEwen, S. Mathalon, D.H. Pearlson, G.D. Potkin, S.G. Preda, A. Turner, J.A. Van Erp, T.G.M. Chang, C. Calhoun, V.D. |
author_sort | Iraji, A. |
collection | PubMed |
description | Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches. |
format | Online Article Text |
id | pubmed-9107614 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-91076142022-05-15 Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping Iraji, A. Faghiri, A. Fu, Z. Kochunov, P. Adhikari, B.M. Belger, A. Ford, J.M. McEwen, S. Mathalon, D.H. Pearlson, G.D. Potkin, S.G. Preda, A. Turner, J.A. Van Erp, T.G.M. Chang, C. Calhoun, V.D. Neuroimage Article Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches. 2022-05-01 2022-02-18 /pmc/articles/PMC9107614/ /pubmed/35189361 http://dx.doi.org/10.1016/j.neuroimage.2022.119013 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ) |
spellingShingle | Article Iraji, A. Faghiri, A. Fu, Z. Kochunov, P. Adhikari, B.M. Belger, A. Ford, J.M. McEwen, S. Mathalon, D.H. Pearlson, G.D. Potkin, S.G. Preda, A. Turner, J.A. Van Erp, T.G.M. Chang, C. Calhoun, V.D. Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping |
title | Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping |
title_full | Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping |
title_fullStr | Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping |
title_full_unstemmed | Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping |
title_short | Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping |
title_sort | moving beyond the ‘cap’ of the iceberg: intrinsic connectivity networks in fmri are continuously engaging and overlapping |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107614/ https://www.ncbi.nlm.nih.gov/pubmed/35189361 http://dx.doi.org/10.1016/j.neuroimage.2022.119013 |
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