Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study
The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time‐resolved functional connectivity are still unclear and under...
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| Published in | Human brain mapping Vol. 44; no. 6; pp. 2158 - 2175 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken, USA
John Wiley & Sons, Inc
15.04.2023
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| Online Access | Get full text |
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| Abstract | The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time‐resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time‐resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U‐shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State‐based statistical summary measures presented robust and significant group differences that also showed significant age‐related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time‐resolved brain state trajectories.
We highlight the replicable time‐resolved developmental and aging functional brain patterns in a systematic evaluation of over 47,000 youth and adult brains. Our study captured the most contrastive difference between the two life stages in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor sub‐domains, supplemented by anticorrelation with other subdomains in adults, a pattern that was consistently less modular or absent in adolescents and presented a negative association with age in adults, thus indicating an overall inverted U‐shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and the gradual decline of this pattern during the healthy aging process. |
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| AbstractList | The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time‐resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time‐resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U‐shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State‐based statistical summary measures presented robust and significant group differences that also showed significant age‐related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time‐resolved brain state trajectories. The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time‐resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time‐resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U‐shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State‐based statistical summary measures presented robust and significant group differences that also showed significant age‐related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time‐resolved brain state trajectories. We highlight the replicable time‐resolved developmental and aging functional brain patterns in a systematic evaluation of over 47,000 youth and adult brains. Our study captured the most contrastive difference between the two life stages in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor sub‐domains, supplemented by anticorrelation with other subdomains in adults, a pattern that was consistently less modular or absent in adolescents and presented a negative association with age in adults, thus indicating an overall inverted U‐shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and the gradual decline of this pattern during the healthy aging process. The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time-resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time-resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U-shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State-based statistical summary measures presented robust and significant group differences that also showed significant age-related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time-resolved brain state trajectories.The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time-resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time-resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U-shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State-based statistical summary measures presented robust and significant group differences that also showed significant age-related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time-resolved brain state trajectories. |
| Author | Wang, Yu‐Ping Stephen, Julia M. Du, Yuhui Wilson, Tony W. Calhoun, Vince D. Abrol, Anees Fu, Zening |
| AuthorAffiliation | 3 Boys Town National Research Hospital Institute for Human Neuroscience Boys Town Nebraska USA 1 Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia USA 6 The Mind Research Network Albuquerque New Mexico USA 2 School of Computer & Information Technology Shanxi University Taiyuan China 4 Department of Biomedical Engineering Tulane University New Orleans Louisiana USA 5 Department of Global Biostatistics and Data Science Tulane University New Orleans Louisiana USA |
| AuthorAffiliation_xml | – name: 2 School of Computer & Information Technology Shanxi University Taiyuan China – name: 5 Department of Global Biostatistics and Data Science Tulane University New Orleans Louisiana USA – name: 6 The Mind Research Network Albuquerque New Mexico USA – name: 3 Boys Town National Research Hospital Institute for Human Neuroscience Boys Town Nebraska USA – name: 1 Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, and Emory University Atlanta Georgia USA – name: 4 Department of Biomedical Engineering Tulane University New Orleans Louisiana USA |
| Author_xml | – sequence: 1 givenname: Anees orcidid: 0000-0001-9223-5314 surname: Abrol fullname: Abrol, Anees email: abrolanees@gmail.com organization: Georgia State University, Georgia Institute of Technology, and Emory University – sequence: 2 givenname: Zening surname: Fu fullname: Fu, Zening organization: Georgia State University, Georgia Institute of Technology, and Emory University – sequence: 3 givenname: Yuhui surname: Du fullname: Du, Yuhui organization: Shanxi University – sequence: 4 givenname: Tony W. orcidid: 0000-0002-5053-8306 surname: Wilson fullname: Wilson, Tony W. organization: Institute for Human Neuroscience – sequence: 5 givenname: Yu‐Ping surname: Wang fullname: Wang, Yu‐Ping organization: Tulane University – sequence: 6 givenname: Julia M. orcidid: 0000-0003-2486-747X surname: Stephen fullname: Stephen, Julia M. organization: The Mind Research Network – sequence: 7 givenname: Vince D. surname: Calhoun fullname: Calhoun, Vince D. organization: Georgia State University, Georgia Institute of Technology, and Emory University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36629328$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1016_j_biopsych_2023_12_019 crossref_primary_10_1016_j_tins_2024_05_011 crossref_primary_10_1007_s11357_024_01436_1 crossref_primary_10_1016_j_neuroimage_2024_120617 crossref_primary_10_1093_bfgp_elae042 |
| Cites_doi | 10.1016/j.neuroimage.2007.11.001 10.3389/fnsys.2021.724805 10.1007/s10334-010-0197-8 10.1016/j.neuroimage.2017.09.020 10.1016/j.neuroimage.2011.10.018 10.1016/j.arr.2016.02.006 10.1093/cercor/bhw082 10.1109/EMBC.2016.7591989 10.1016/j.nicl.2020.102375 10.1016/j.euroneuro.2010.03.008 10.1109/embc48229.2022.9871305 10.1109/10.391164 10.1016/j.neuroimage.2012.11.008 10.1002/hbm.23896 10.1155/2019/9027803 10.3389/fnhum.2015.00418 10.1523/jneurosci.4638-14.2015 10.1007/s00424-021-02520-7 10.1523/jneurosci.1476-16.2016 10.1002/hbm.22985 10.1371/journal.pbio.1000157 10.1016/j.neurobiolaging.2016.02.020 10.3389/fped.2020.00412 10.1016/j.dcn.2018.03.001 10.1093/cercor/bhaa367 10.21203/rs.3.rs-1514598/v1 10.1089/brain.2011.0008 10.1038/s41586-022-04492-9 10.3389/fnagi.2017.00203 10.3389/fnins.2018.00551 10.1016/j.neurobiolaging.2013.07.003 10.1186/s13643-015-0173-5 10.1523/jneurosci.2612-10.2010 10.1016/j.neuron.2010.08.017 10.1007/s10654-013-9768-0 10.1016/j.neuroimage.2018.01.040 10.1093/cercor/bhs352 10.1016/j.neuroimage.2016.12.061 10.1002/hbm.1048 10.1038/nn.4393 10.1038/sdata.2015.31 10.1038/s42003-021-02592-2 10.1002/hbm.24064 10.1016/S2352-4642(18)30022-1 10.1016/j.tics.2013.09.015 10.1016/j.neuroimage.2011.12.063 10.1109/BIBE52308.2021.9635525 10.1016/j.neuroimage.2013.05.079 10.1093/cercor/bhq104 10.1002/hbm.23346 10.1016/j.neuroimage.2020.117438 10.1162/netn_a_00116 10.1073/pnas.0705843104 10.1016/j.neubiorev.2015.08.013 10.1016/j.neuron.2014.10.015 10.1016/j.neuroimage.2013.05.041 10.1016/j.jadohealth.2008.01.007 10.1109/rbme.2012.2211076 10.1146/annurev-clinpsy-032814-112753 10.3389/fpsyg.2015.00663 10.3389/fnagi.2016.00330 |
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| Copyright | 2023 The Authors. published by Wiley Periodicals LLC. 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. 2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Keywords | brain development brain aging functional connectivity connectivity resting state fMRI time-resolved functional connectivity |
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| References | 2015; 35 2007; 104 2012; 60 2019; 2019 2015; 36 2013; 69 2013; 28 2008; 39 2016; 30 2014; 24 2012; 59 2017; 9 2016; 36 2020; 8 2010; 67 2010; 23 2018; 39 2010; 20 2020; 4 2021; 31 2018; 2 2013; 17 2018; 172 2017; 38 2016; 41 2017; 160 2011; 21 2017; 163 2021; 473 2022; 603 2018; 32 2001; 14 2010; 30 2015; 2 2015; 57 2015; 6 2021; 4 2011; 1 2016; 19 2021; 225 2017; 27 2015; 11 2014; 84 2015; 9 1995; 42 2016; 5 2021; 15 2022; 2022 2022 2021 2020; 28 2013; 80 2014; 35 2016 2009; 7 2008; 42 2018; 12 2012; 5 2016; 8 e_1_2_8_28_1 e_1_2_8_24_1 e_1_2_8_47_1 e_1_2_8_26_1 e_1_2_8_49_1 e_1_2_8_3_1 e_1_2_8_5_1 e_1_2_8_7_1 e_1_2_8_9_1 e_1_2_8_20_1 e_1_2_8_43_1 e_1_2_8_22_1 e_1_2_8_45_1 e_1_2_8_62_1 e_1_2_8_41_1 e_1_2_8_60_1 e_1_2_8_17_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_36_1 e_1_2_8_59_1 e_1_2_8_15_1 e_1_2_8_38_1 e_1_2_8_57_1 e_1_2_8_32_1 e_1_2_8_55_1 e_1_2_8_11_1 e_1_2_8_34_1 e_1_2_8_53_1 e_1_2_8_51_1 e_1_2_8_30_1 e_1_2_8_29_1 e_1_2_8_25_1 e_1_2_8_46_1 e_1_2_8_27_1 e_1_2_8_48_1 e_1_2_8_2_1 e_1_2_8_4_1 e_1_2_8_6_1 e_1_2_8_8_1 e_1_2_8_21_1 e_1_2_8_42_1 e_1_2_8_23_1 e_1_2_8_44_1 e_1_2_8_40_1 e_1_2_8_61_1 e_1_2_8_18_1 e_1_2_8_39_1 e_1_2_8_14_1 e_1_2_8_35_1 e_1_2_8_16_1 e_1_2_8_37_1 e_1_2_8_58_1 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_56_1 e_1_2_8_12_1 e_1_2_8_33_1 e_1_2_8_54_1 e_1_2_8_52_1 e_1_2_8_50_1 |
| References_xml | – volume: 6 start-page: 663 year: 2015 article-title: Reorganization of brain networks in aging: A review of functional connectivity studies publication-title: Frontiers in Psychology – volume: 7 issue: 7 year: 2009 article-title: Development of large‐scale functional brain networks in children publication-title: PLoS Biology – volume: 39 start-page: 3127 issue: 8 year: 2018 end-page: 3142 article-title: Connectivity dynamics in typical development and its relationship to autistic traits and autism spectrum disorder publication-title: Human Brain Mapping – volume: 28 year: 2020 article-title: NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders publication-title: NeuroImage: Clinical – volume: 24 start-page: 663 issue: 3 year: 2014 end-page: 676 article-title: Tracking whole‐brain connectivity dynamics in the resting state publication-title: Cerebral Cortex – year: 2021 – volume: 41 start-page: 159 year: 2016 end-page: 172 article-title: Age differences in the functional interactions among the default, frontoparietal control, and dorsal attention networks publication-title: Neurobiology of Aging – volume: 15 year: 2021 article-title: Developmental changes in dynamic functional connectivity from childhood into adolescence [original research] publication-title: Frontiers in Systems Neuroscience – volume: 2 start-page: 223 issue: 3 year: 2018 end-page: 228 article-title: The age of adolescence publication-title: The Lancet Child & Adolescent Health – volume: 30 start-page: 61 year: 2016 end-page: 72 article-title: Functional neuroimaging of normal aging: Declining brain, adapting brain publication-title: Ageing Research Reviews – volume: 104 start-page: 13507 issue: 33 year: 2007 end-page: 13512 article-title: Development of distinct control networks through segregation and integration publication-title: Proceedings of the National Academy of Sciences – volume: 4 start-page: 1073 issue: 1 year: 2021 article-title: Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder publication-title: Communications Biology – volume: 8 start-page: 412 year: 2020 article-title: Changes of dynamic functional connectivity associated with maturity in late preterm infants publication-title: Frontiers in Pediatrics – volume: 9 year: 2015 article-title: Predicting individual brain maturity using dynamic functional connectivity [original research] publication-title: Frontiers in Human Neuroscience – volume: 5 start-page: 60 year: 2012 end-page: 73 article-title: Multisubject independent component analysis of fMRI: A decade of intrinsic networks, default mode, and neurodiagnostic discovery publication-title: IEEE Reviews in Biomedical Engineering – volume: 69 start-page: 157 year: 2013 end-page: 197 article-title: Group information guided ICA for fMRI data analysis publication-title: NeuroImage – volume: 19 start-page: 1523 issue: 11 year: 2016 end-page: 1536 article-title: Multimodal population brain imaging in the UK biobank prospective epidemiological study publication-title: Nature Neuroscience – volume: 38 start-page: 97 issue: 1 year: 2017 end-page: 108 article-title: Dynamic functional connectivity of neurocognitive networks in children publication-title: Human Brain Mapping – volume: 225 year: 2021 article-title: The developmental chronnecto‐genomics (Dev‐CoG) study: A multimodal study on the developing brain publication-title: NeuroImage – volume: 2019 year: 2019 article-title: Tracking the brain state transition process of dynamic function connectivity based on resting state fMRI publication-title: Computational Intelligence and Neuroscience – volume: 60 start-page: 623 issue: 1 year: 2012 end-page: 632 article-title: Impact of in‐scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth publication-title: NeuroImage – volume: 2 issue: 1 year: 2015 article-title: Brain genomics superstruct project initial data release with structural, functional, and behavioral measures publication-title: Scientific Data – year: 2022 article-title: Functional connectivity uniqueness and variability? publication-title: Research Square – volume: 31 start-page: 2466 issue: 5 year: 2021 end-page: 2481 article-title: Whole‐brain dynamics in aging: Disruptions in functional connectivity and the role of the rich club publication-title: Cerebral Cortex – volume: 21 start-page: 385 issue: 2 year: 2011 end-page: 391 article-title: A comprehensive study of whole‐brain functional connectivity in children and young adults publication-title: Cerebral Cortex – volume: 27 start-page: 2303 issue: 3 year: 2017 end-page: 2317 article-title: The disconnected brain and executive function decline in aging publication-title: Cerebral Cortex – volume: 36 start-page: 4926 issue: 12 year: 2015 end-page: 4937 article-title: Temporal stability of network centrality in control and default mode networks: Specific associations with externalizing psychopathology in children and adolescents publication-title: Human Brain Mapping – volume: 14 start-page: 140 issue: 3 year: 2001 end-page: 151 article-title: A method for making group inferences from functional MRI data using independent component analysis publication-title: Human Brain Mapping – volume: 80 start-page: 62 year: 2013 end-page: 79 article-title: The WU‐Minn human connectome project: An overview publication-title: NeuroImage – volume: 20 start-page: 519 issue: 8 year: 2010 end-page: 534 article-title: Exploring the brain network: A review on resting‐state fMRI functional connectivity publication-title: European Neuropsychopharmacology – volume: 11 start-page: 361 year: 2015 end-page: 377 article-title: fMRI functional connectivity applied to adolescent neurodevelopment publication-title: Annual Review of Clinical Psychology – volume: 28 start-page: 99 issue: 1 year: 2013 end-page: 111 article-title: Pediatric population‐based neuroimaging and the generation R study: The intersection of developmental neuroscience and epidemiology publication-title: European Journal of Epidemiology – volume: 12 year: 2018 article-title: Resting‐state fMRI dynamics and null models: Perspectives, sampling variability, and simulations [perspective] publication-title: Frontiers in Neuroscience – volume: 23 start-page: 351 issue: 5–6 year: 2010 end-page: 366 article-title: A method for evaluating dynamic functional network connectivity and task‐modulation: Application to schizophrenia publication-title: Magma – volume: 2022 start-page: 1867 year: 2022 end-page: 1870 article-title: Spatially constrained ICA enables robust detection of schizophrenia from very short resting‐state fMRI publication-title: Annual International Conference of IEEE Engineering in Medicine and Biological Society – volume: 9 start-page: 203 year: 2017 article-title: Age‐related decline in the variation of dynamic functional connectivity: A resting state analysis publication-title: Frontiers in Aging Neuroscience – volume: 42 start-page: 658 issue: 7 year: 1995 end-page: 665 article-title: Segmentation of brain electrical activity into microstates: Model estimation and validation publication-title: IEEE Transactions on Biomedical Engineering – volume: 36 start-page: 10060 issue: 39 year: 2016 end-page: 10074 article-title: Dissociable changes of frontal and parietal cortices in inherent functional flexibility across the human life span publication-title: The Journal of Neuroscience – volume: 160 start-page: 41 year: 2017 end-page: 54 article-title: The dynamic functional connectome: State‐of‐the‐art and perspectives publication-title: NeuroImage – volume: 35 start-page: 6849 issue: 17 year: 2015 end-page: 6859 article-title: Tracking the brain's functional coupling dynamics over development publication-title: The Journal of Neuroscience – volume: 4 start-page: 30 issue: 1 year: 2020 end-page: 69 article-title: Questions and controversies in the study of time‐varying functional connectivity in resting fMRI publication-title: Network Neuroscience (Cambridge, Mass.) – volume: 84 start-page: 262 issue: 2 year: 2014 end-page: 274 article-title: The chronnectome: Time‐varying connectivity networks as the next frontier in fMRI data discovery publication-title: Neuron – volume: 603 start-page: 654 issue: 7902 year: 2022 end-page: 660 article-title: Reproducible brain‐wide association studies require thousands of individuals publication-title: Nature – year: 2016 – volume: 39 start-page: 1108 issue: 3 year: 2018 end-page: 1117 article-title: Changing brain connectivity dynamics: From early childhood to adulthood publication-title: Human Brain Mapping – volume: 1 start-page: 13 issue: 1 year: 2011 end-page: 36 article-title: Functional and effective connectivity: A review publication-title: Brain Connectivity – volume: 59 start-page: 2142 issue: 3 year: 2012 end-page: 2154 article-title: Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion publication-title: NeuroImage – volume: 163 start-page: 160 year: 2017 end-page: 176 article-title: Replicability of time‐varying connectivity patterns in large resting state fMRI samples publication-title: NeuroImage – volume: 473 start-page: 793 issue: 5 year: 2021 end-page: 803 article-title: Resting‐state networks in the course of aging‐differential insights from studies across the lifespan vs. amongst the old publication-title: Pflügers Archiv – volume: 30 start-page: 15034 issue: 45 year: 2010 end-page: 15043 article-title: Growing together and growing apart: Regional and sex differences in the lifespan developmental trajectories of functional homotopy publication-title: The Journal of Neuroscience – volume: 32 start-page: 43 year: 2018 end-page: 54 article-title: The adolescent brain cognitive development (ABCD) study: Imaging acquisition across 21 sites publication-title: Developmental Cognitive Neuroscience – volume: 8 start-page: 330 year: 2016 article-title: Early age‐related functional connectivity decline in high‐order cognitive networks publication-title: Frontiers in Aging Neuroscience – volume: 67 start-page: 735 issue: 5 year: 2010 end-page: 748 article-title: The development of human functional brain networks publication-title: Neuron – volume: 172 start-page: 31 year: 2018 end-page: 39 article-title: Changes in dynamic functional connections with aging publication-title: NeuroImage – volume: 5 start-page: 3 issue: 1 year: 2016 article-title: A systematic review of adolescent physiological development and its relationship with health‐related behaviour: A protocol publication-title: Systematic Reviews – volume: 39 start-page: 1666 issue: 4 year: 2008 end-page: 1681 article-title: A method for functional network connectivity among spatially independent resting‐state components in schizophrenia publication-title: NeuroImage – volume: 80 start-page: 360 year: 2013 end-page: 378 article-title: Dynamic functional connectivity: Promise, issues, and interpretations publication-title: NeuroImage – volume: 17 start-page: 627 issue: 12 year: 2013 end-page: 640 article-title: Developmental pathways to functional brain networks: Emerging principles publication-title: Trends in Cognitive Sciences – volume: 35 start-page: 42 issue: 1 year: 2014 end-page: 54 article-title: Age‐related functional reorganization, structural changes, and preserved cognition publication-title: Neurobiology of Aging – volume: 42 start-page: 335 issue: 4 year: 2008 end-page: 343 article-title: The teen brain: Insights from neuroimaging publication-title: The Journal of Adolescent Health – volume: 57 start-page: 156 year: 2015 end-page: 174 article-title: Putting age‐related task activation into large‐scale brain networks: A meta‐analysis of 114 fMRI studies on healthy aging publication-title: Neuroscience and Biobehavioral Reviews – ident: e_1_2_8_27_1 doi: 10.1016/j.neuroimage.2007.11.001 – ident: e_1_2_8_32_1 doi: 10.3389/fnsys.2021.724805 – ident: e_1_2_8_48_1 doi: 10.1007/s10334-010-0197-8 – ident: e_1_2_8_3_1 doi: 10.1016/j.neuroimage.2017.09.020 – ident: e_1_2_8_42_1 doi: 10.1016/j.neuroimage.2011.10.018 – ident: e_1_2_8_55_1 doi: 10.1016/j.arr.2016.02.006 – ident: e_1_2_8_19_1 doi: 10.1093/cercor/bhw082 – ident: e_1_2_8_2_1 doi: 10.1109/EMBC.2016.7591989 – ident: e_1_2_8_12_1 doi: 10.1016/j.nicl.2020.102375 – ident: e_1_2_8_58_1 doi: 10.1016/j.euroneuro.2010.03.008 – ident: e_1_2_8_14_1 doi: 10.1109/embc48229.2022.9871305 – ident: e_1_2_8_41_1 doi: 10.1109/10.391164 – ident: e_1_2_8_11_1 doi: 10.1016/j.neuroimage.2012.11.008 – ident: e_1_2_8_17_1 doi: 10.1002/hbm.23896 – ident: e_1_2_8_31_1 doi: 10.1155/2019/9027803 – ident: e_1_2_8_46_1 doi: 10.3389/fnhum.2015.00418 – ident: e_1_2_8_25_1 doi: 10.1523/jneurosci.4638-14.2015 – ident: e_1_2_8_28_1 doi: 10.1007/s00424-021-02520-7 – ident: e_1_2_8_61_1 doi: 10.1523/jneurosci.1476-16.2016 – ident: e_1_2_8_50_1 doi: 10.1002/hbm.22985 – ident: e_1_2_8_56_1 doi: 10.1371/journal.pbio.1000157 – ident: e_1_2_8_23_1 doi: 10.1016/j.neurobiolaging.2016.02.020 – ident: e_1_2_8_34_1 doi: 10.3389/fped.2020.00412 – ident: e_1_2_8_8_1 doi: 10.1016/j.dcn.2018.03.001 – ident: e_1_2_8_16_1 doi: 10.1093/cercor/bhaa367 – ident: e_1_2_8_21_1 doi: 10.21203/rs.3.rs-1514598/v1 – ident: e_1_2_8_20_1 doi: 10.1089/brain.2011.0008 – ident: e_1_2_8_35_1 doi: 10.1038/s41586-022-04492-9 – ident: e_1_2_8_9_1 doi: 10.3389/fnagi.2017.00203 – ident: e_1_2_8_40_1 doi: 10.3389/fnins.2018.00551 – ident: e_1_2_8_38_1 doi: 10.1016/j.neurobiolaging.2013.07.003 – ident: e_1_2_8_45_1 doi: 10.1186/s13643-015-0173-5 – ident: e_1_2_8_62_1 doi: 10.1523/jneurosci.2612-10.2010 – ident: e_1_2_8_43_1 doi: 10.1016/j.neuron.2010.08.017 – ident: e_1_2_8_60_1 doi: 10.1007/s10654-013-9768-0 – ident: e_1_2_8_57_1 doi: 10.1016/j.neuroimage.2018.01.040 – ident: e_1_2_8_4_1 doi: 10.1093/cercor/bhs352 – ident: e_1_2_8_44_1 doi: 10.1016/j.neuroimage.2016.12.061 – ident: e_1_2_8_6_1 doi: 10.1002/hbm.1048 – ident: e_1_2_8_39_1 doi: 10.1038/nn.4393 – ident: e_1_2_8_24_1 doi: 10.1038/sdata.2015.31 – ident: e_1_2_8_13_1 doi: 10.1038/s42003-021-02592-2 – ident: e_1_2_8_47_1 doi: 10.1002/hbm.24064 – ident: e_1_2_8_52_1 doi: 10.1016/S2352-4642(18)30022-1 – ident: e_1_2_8_37_1 doi: 10.1016/j.tics.2013.09.015 – ident: e_1_2_8_51_1 doi: 10.1016/j.neuroimage.2011.12.063 – ident: e_1_2_8_10_1 doi: 10.1109/BIBE52308.2021.9635525 – ident: e_1_2_8_26_1 doi: 10.1016/j.neuroimage.2013.05.079 – ident: e_1_2_8_29_1 doi: 10.1093/cercor/bhq104 – ident: e_1_2_8_36_1 doi: 10.1002/hbm.23346 – ident: e_1_2_8_54_1 doi: 10.1016/j.neuroimage.2020.117438 – ident: e_1_2_8_33_1 doi: 10.1162/netn_a_00116 – ident: e_1_2_8_18_1 doi: 10.1073/pnas.0705843104 – ident: e_1_2_8_30_1 doi: 10.1016/j.neubiorev.2015.08.013 – ident: e_1_2_8_7_1 doi: 10.1016/j.neuron.2014.10.015 – ident: e_1_2_8_59_1 doi: 10.1016/j.neuroimage.2013.05.041 – ident: e_1_2_8_22_1 doi: 10.1016/j.jadohealth.2008.01.007 – ident: e_1_2_8_5_1 doi: 10.1109/rbme.2012.2211076 – ident: e_1_2_8_15_1 doi: 10.1146/annurev-clinpsy-032814-112753 – ident: e_1_2_8_49_1 doi: 10.3389/fpsyg.2015.00663 – ident: e_1_2_8_53_1 doi: 10.3389/fnagi.2016.00330 |
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| SubjectTerms | Adaptation Adolescent Adolescents Adult Adults Age Aging Aging - pathology Biobanks Brain brain aging Brain architecture brain development Brain mapping Brain Mapping - methods Brain research Child Child development Cognitive ability connectivity Datasets Developmental stages functional connectivity Functional magnetic resonance imaging Functional morphology Human subjects Humans Life span Longevity Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Modularization Neural networks Neural Pathways - diagnostic imaging Neuroimaging Rest resting state fMRI Sensorimotor integration Sensory integration Strengthening Teenagers time‐resolved functional connectivity Youth |
| Title | Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study |
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