Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence

The longitudinal study of typical neurodevelopment is key for understanding deviations due to specific factors, such as psychopathology. However, research utilizing repeated measurements remains scarce. Resting-state functional magnetic resonance imaging (MRI) studies have traditionally examined con...

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Autores principales: Mónica López-Vicente, Oktay Agcaoglu, Laura Pérez-Crespo, Fernando Estévez-López, José María Heredia-Genestar, Rosa H. Mulder, John C. Flournoy, Anna C. K. van Duijvenvoorde, Berna Güroğlu, Tonya White, Vince Calhoun, Henning Tiemeier, Ryan L. Muetzel
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Publicado: Frontiers Media S.A. 2021
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spelling oai:doaj.org-article:626a7cb39c5e446980b5377b46c1b51b2021-11-22T05:58:24ZDevelopmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence1662-513710.3389/fnsys.2021.724805https://doaj.org/article/626a7cb39c5e446980b5377b46c1b51b2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fnsys.2021.724805/fullhttps://doaj.org/toc/1662-5137The longitudinal study of typical neurodevelopment is key for understanding deviations due to specific factors, such as psychopathology. However, research utilizing repeated measurements remains scarce. Resting-state functional magnetic resonance imaging (MRI) studies have traditionally examined connectivity as ‘static’ during the measurement period. In contrast, dynamic approaches offer a more comprehensive representation of functional connectivity by allowing for different connectivity configurations (time varying connectivity) throughout the scanning session. Our objective was to characterize the longitudinal developmental changes in dynamic functional connectivity in a population-based pediatric sample. Resting-state MRI data were acquired at the ages of 10 (range 8-to-12, n = 3,327) and 14 (range 13-to-15, n = 2,404) years old using a single, study-dedicated 3 Tesla scanner. A fully-automated spatially constrained group-independent component analysis (ICA) was applied to decompose multi-subject resting-state data into functionally homogeneous regions. Dynamic functional network connectivity (FNC) between all ICA time courses were computed using a tapered sliding window approach. We used a k-means algorithm to cluster the resulting dynamic FNC windows from each scan session into five dynamic states. We examined age and sex associations using linear mixed-effects models. First, independent from the dynamic states, we found a general increase in the temporal variability of the connections between intrinsic connectivity networks with increasing age. Second, when examining the clusters of dynamic FNC windows, we observed that the time spent in less modularized states, with low intra- and inter-network connectivity, decreased with age. Third, the number of transitions between states also decreased with age. Finally, compared to boys, girls showed a more mature pattern of dynamic brain connectivity, indicated by more time spent in a highly modularized state, less time spent in specific states that are frequently observed at a younger age, and a lower number of transitions between states. This longitudinal population-based study demonstrates age-related maturation in dynamic intrinsic neural activity from childhood into adolescence and offers a meaningful baseline for comparison with deviations from typical development. Given that several behavioral and cognitive processes also show marked changes through childhood and adolescence, dynamic functional connectivity should also be explored as a potential neurobiological determinant of such changes.Mónica López-VicenteMónica López-VicenteOktay AgcaogluLaura Pérez-CrespoFernando Estévez-LópezFernando Estévez-LópezJosé María Heredia-GenestarRosa H. MulderRosa H. MulderJohn C. FlournoyAnna C. K. van DuijvenvoordeAnna C. K. van DuijvenvoordeBerna GüroğluBerna GüroğluTonya WhiteTonya WhiteVince CalhounHenning TiemeierHenning TiemeierRyan L. MuetzelFrontiers Media S.A.articlebrain developmentfMRIlongitudinalresting state – fMRIlinear mixed effect modelNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENFrontiers in Systems Neuroscience, Vol 15 (2021)
institution DOAJ
collection DOAJ
language EN
topic brain development
fMRI
longitudinal
resting state – fMRI
linear mixed effect model
Neurosciences. Biological psychiatry. Neuropsychiatry
RC321-571
spellingShingle brain development
fMRI
longitudinal
resting state – fMRI
linear mixed effect model
Neurosciences. Biological psychiatry. Neuropsychiatry
RC321-571
Mónica López-Vicente
Mónica López-Vicente
Oktay Agcaoglu
Laura Pérez-Crespo
Fernando Estévez-López
Fernando Estévez-López
José María Heredia-Genestar
Rosa H. Mulder
Rosa H. Mulder
John C. Flournoy
Anna C. K. van Duijvenvoorde
Anna C. K. van Duijvenvoorde
Berna Güroğlu
Berna Güroğlu
Tonya White
Tonya White
Vince Calhoun
Henning Tiemeier
Henning Tiemeier
Ryan L. Muetzel
Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence
description The longitudinal study of typical neurodevelopment is key for understanding deviations due to specific factors, such as psychopathology. However, research utilizing repeated measurements remains scarce. Resting-state functional magnetic resonance imaging (MRI) studies have traditionally examined connectivity as ‘static’ during the measurement period. In contrast, dynamic approaches offer a more comprehensive representation of functional connectivity by allowing for different connectivity configurations (time varying connectivity) throughout the scanning session. Our objective was to characterize the longitudinal developmental changes in dynamic functional connectivity in a population-based pediatric sample. Resting-state MRI data were acquired at the ages of 10 (range 8-to-12, n = 3,327) and 14 (range 13-to-15, n = 2,404) years old using a single, study-dedicated 3 Tesla scanner. A fully-automated spatially constrained group-independent component analysis (ICA) was applied to decompose multi-subject resting-state data into functionally homogeneous regions. Dynamic functional network connectivity (FNC) between all ICA time courses were computed using a tapered sliding window approach. We used a k-means algorithm to cluster the resulting dynamic FNC windows from each scan session into five dynamic states. We examined age and sex associations using linear mixed-effects models. First, independent from the dynamic states, we found a general increase in the temporal variability of the connections between intrinsic connectivity networks with increasing age. Second, when examining the clusters of dynamic FNC windows, we observed that the time spent in less modularized states, with low intra- and inter-network connectivity, decreased with age. Third, the number of transitions between states also decreased with age. Finally, compared to boys, girls showed a more mature pattern of dynamic brain connectivity, indicated by more time spent in a highly modularized state, less time spent in specific states that are frequently observed at a younger age, and a lower number of transitions between states. This longitudinal population-based study demonstrates age-related maturation in dynamic intrinsic neural activity from childhood into adolescence and offers a meaningful baseline for comparison with deviations from typical development. Given that several behavioral and cognitive processes also show marked changes through childhood and adolescence, dynamic functional connectivity should also be explored as a potential neurobiological determinant of such changes.
format article
author Mónica López-Vicente
Mónica López-Vicente
Oktay Agcaoglu
Laura Pérez-Crespo
Fernando Estévez-López
Fernando Estévez-López
José María Heredia-Genestar
Rosa H. Mulder
Rosa H. Mulder
John C. Flournoy
Anna C. K. van Duijvenvoorde
Anna C. K. van Duijvenvoorde
Berna Güroğlu
Berna Güroğlu
Tonya White
Tonya White
Vince Calhoun
Henning Tiemeier
Henning Tiemeier
Ryan L. Muetzel
author_facet Mónica López-Vicente
Mónica López-Vicente
Oktay Agcaoglu
Laura Pérez-Crespo
Fernando Estévez-López
Fernando Estévez-López
José María Heredia-Genestar
Rosa H. Mulder
Rosa H. Mulder
John C. Flournoy
Anna C. K. van Duijvenvoorde
Anna C. K. van Duijvenvoorde
Berna Güroğlu
Berna Güroğlu
Tonya White
Tonya White
Vince Calhoun
Henning Tiemeier
Henning Tiemeier
Ryan L. Muetzel
author_sort Mónica López-Vicente
title Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence
title_short Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence
title_full Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence
title_fullStr Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence
title_full_unstemmed Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence
title_sort developmental changes in dynamic functional connectivity from childhood into adolescence
publisher Frontiers Media S.A.
publishDate 2021
url https://doaj.org/article/626a7cb39c5e446980b5377b46c1b51b
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