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Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat
2020
Frontiers in Aging Neuroscience
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We investigated 7.0T MRI gray matter covariance in 10 young and 10 aged adult male Fischer 344 rats to identify, using SSM VBM, the age-related regional network gray matter covariance pattern in the rodent ...
Greater expression of the age-related MRI gray matter pattern was associated with poorer spatial learning in the age groups combined. ...
ACKNOWLEDGMENTS We are grateful for support from the National Institute on Aging at the National Institutes of Health, the state of Arizona and Arizona Department of Health Services, the Arizona Advanced ...
doi:10.3389/fnagi.2020.00267
pmid:33005147
pmcid:PMC7479213
fatcat:fkggcjlwhrdljh3btdcpcdoauy
Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
2014
Aging Cell
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Here, we investigate anatomical brain networks based on structural covariance of gray matter volume among 370 middle-aged to older adults of 45-85 years. ...
After segmentation of structural MRI scans, nine anatomical networks were defined based on structural covariance of gray matter volume among subjects. ...
Fig. 1 1 Gray matter structural networks and associations with age. (A) Overview of the nine anatomical networks based on the covariation of gray matter volumes among middle-aged to older adults. ...
doi:10.1111/acel.12271
pmid:25257192
pmcid:PMC4326918
fatcat:hauiaupoqrb2ho7nicwqtsqlgm
Structural covariance networks across the life span, from 6 to 94 years of age
2017
Network Neuroscience
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Structural covariance examines covariation of gray matter morphology between brain regions and across individuals. ...
the development of structural covariance networks. ...
Future longitudinal studies of structural covariance patterns will be important to address the impact of age on specific cortical networks. ...
doi:10.1162/netn_a_00016
pmid:29855624
pmcid:PMC5874135
fatcat:674zd7spdzd6hjce6rux37smom
Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes
2016
Human Brain Mapping
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These results suggest that early-onset T1D negatively impacts the global organization of structural covariance networks and influences the trajectory of brain development in childhood. ...
This is the first study to examine structural covariance networks in young children with T1D. ...
Acknowledgements The authors thank the children and their families as well as the clinical and imaging staff at all of the investigator sites. ...
doi:10.1002/hbm.23293
pmid:27339089
pmcid:PMC5053865
fatcat:vrmael3q35fbbcqbcbkiwnk4ti
Network-level structural covariance in the developing brain
2010
Proceedings of the National Academy of Sciences of the United States of America
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-18 y) to characterize gray matter structural relationships between cortical nodes that make up large-scale functional networks. ...
In general, structural covariance in the youngest age group was limited to seed and contralateral homologous regions. ...
Hillblom Foundation, the Pediatric National Institutes of Health MRI Data Repository, and a University of California San Francisco Clinical and Translational Science Institute Resident Research Award ( ...
doi:10.1073/pnas.1003109107
pmid:20921389
pmcid:PMC2964249
fatcat:ocr2tau7ovcajdij4xycu7qzci
A forward application of age associated gray and white matter networks
2008
Human Brain Mapping
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To capture patterns of normal age-associated atrophy, we previously used a multivariate statistical approach applied to voxel based morphometry that identified age-associated gray and white matter covariance ...
The findings suggest that the previously derived age-associated covariance pattern for gray matter is reliable and may provide information that is more functionally meaningful than chronological age. ...
of 80%and specificity of r Age-Associated Structural Covariance Networks r r 1141 r 61.9% for white matter. ...
doi:10.1002/hbm.20452
pmid:17935180
pmcid:PMC2637464
fatcat:7wr6wkqmmzexpnnhce33bc5vmi
The Convergence of Maturational Change and Structural Covariance in Human Cortical Networks
2013
Journal of Neuroscience
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To test this prediction, we used a structural MRI dataset on healthy young people (N ϭ 108; aged 9 -22 years at enrollment), comprising 3-6 longitudinal scans on each participant over 6 -12 years of follow-up ...
., increase or decrease in volume at the same rate over the course of years in the same individual, are thus expected to demonstrate strong structural covariance or anatomical connectivity across individuals ...
The impact of age and in-scanner motion on structural-functional convergence. ...
doi:10.1523/jneurosci.3554-12.2013
pmid:23407947
pmcid:PMC3711653
fatcat:umar7w5cwnb5ddgtlquaolbqpa
scMRI Reveals Large-Scale Brain Network Abnormalities in Autism
2012
PLoS ONE
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We used structural covariance MRI to investigate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode ...
network, in autistic subjects and age-, gender-, and IQ-matched controls. ...
Acknowledgments The authors express their sincere gratitude to the young people and their families who participated in the study.
Author Contributions ...
doi:10.1371/journal.pone.0049172
pmid:23185305
pmcid:PMC3504046
fatcat:y7ol3xst6vejrjg6mukdq7b6bu
Decreased centrality of cortical volume covariance networks in autism spectrum disorders
2015
Journal of Psychiatric Research
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However, atypical functional and structural connectivity are likely to be also linked to abnormal development of the correlated structure of cortical gray matter. ...
Such covariations of gray matter are particularly well suited to the investigation of the complex cortical pathology of ASD, which is not confined to isolated brain regions but instead acts at the systems ...
of gray matter covariance networks. ...
doi:10.1016/j.jpsychires.2015.08.003
pmid:26343606
fatcat:ktd5hiqabbdxrk3a3f7byarntm
Discrete Alterations of Brain Network Structural Covariance in Individuals at Ultra-High Risk for Psychosis
2015
Biological Psychiatry
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Mean gray matter volume of the seed region, and global gray matter, as well as age (since UHR and HC group differed significantly in terms of mean age) were included as covariates. ...
ANCOVAs comparing UHR and HC participants ANCOVAs, with mean seed gray matter intensity, age and global gray matter volume of each seed region as covariates, revealed reduced structural covariance in the ...
doi:10.1016/j.biopsych.2014.10.023
pmid:25524754
fatcat:h4widmmocbeavjcdvagvz3hnvy
The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
2016
Neurobiology of Aging
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However, previous literature has not been consistent and, in particular, its impact on the topology organization of brain networks remains to be established. ...
Freesurfer was used to perform vertex-wise comparisons of cortical thickness, whereas the Graph Analysis Toolbox (GAT) was implemented to construct and analyze the structural covariance networks. ...
of Cambridge, and the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Newcastle on Tyne Hospitals NHS Foundation Trust and the Newcastle University. ...
doi:10.1016/j.neurobiolaging.2016.08.013
pmid:27721203
pmcid:PMC5096887
fatcat:aa6c62rk3bafnae4sxmrh4icna
Moving forward: Age effects on the cerebellum underlie cognitive and motor declines
2014
Neuroscience and Biobehavioral Reviews
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The diverse functions of the cerebellum make it an important structure to investigate in aging. Here, we review the extant literature on this topic. ...
Importantly, we provide a conceptual framework for the cerebellum influencing age differences in performance, centered on the notion of degraded internal models. ...
The network of gray matter covariance related to age included bilateral frontal, temporal, and thalamic gray matter along with gray matter in the right cerebellum located in the regions of Crus I and II ...
doi:10.1016/j.neubiorev.2014.02.011
pmid:24594194
pmcid:PMC4024443
fatcat:ae2ryw2gozhvbgx6kzxvesc6f4
Predicting Brain Age of Healthy Adults Based on Structural MRI Parcellation Using Convolutional Neural Networks
2020
Frontiers in Neurology
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In recent years, many studies have focused on estimating age using structural MRI measurements. However, the age prediction effects on different structural networks remain unclear. ...
First, based on the reference map of CorticalParcellation_Yeo2011, we obtained structural network images for each subject, including images of the following: the frontoparietal network (FPN), the dorsal ...
AUTHOR CONTRIBUTIONS HJ, LY, and XG designed the study. HJ and NL performed data analysis. HJ, KC, KL, JZ, and XG interpreted the results. HJ, NL, and XG drafted the manuscript. ...
doi:10.3389/fneur.2019.01346
pmid:31969858
pmcid:PMC6960113
fatcat:vg7y7lu5tvc5fcnlcwlt3m7erm
Neurodegenerative diseases target large-scale human brain networks
2010
Alzheimer's & Dementia
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We further discovered a direct link between intrinsic connectivity and gray matter structure. ...
During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. ...
This finding builds on existing notions of ''small worldness'' in human cortical gray matter structure (He et al., 2007) by demonstrating a direct, network-based function-structure relationship. ...
doi:10.1016/j.jalz.2010.05.522
fatcat:dd3jz4n2kfdidnqheao2lbfhu4
Neurodegenerative Diseases Target Large-Scale Human Brain Networks
2009
Neuron
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We further discovered a direct link between intrinsic connectivity and gray matter structure. ...
During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. ...
This finding builds on existing notions of ''small worldness'' in human cortical gray matter structure (He et al., 2007) by demonstrating a direct, network-based function-structure relationship. ...
doi:10.1016/j.neuron.2009.03.024
pmid:19376066
pmcid:PMC2691647
fatcat:fuqwhwxla5hkjkedtgcrfz5l34
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