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dc.contributor.authorAlexander, Gene E.
dc.contributor.authorLin, Lan
dc.contributor.authorYoshimaru, Eriko S.
dc.contributor.authorBharadwaj, Pradyumna K.
dc.contributor.authorBergfield, Kaitlin L.
dc.contributor.authorHoang, Lan T.
dc.contributor.authorChawla, Monica K.
dc.contributor.authorChen, Kewei
dc.contributor.authorMoeller, James R.
dc.contributor.authorBarnes, Carol A.
dc.contributor.authorTrouard, Theodore P.
dc.date.accessioned2021-04-02T23:59:37Z
dc.date.available2021-04-02T23:59:37Z
dc.date.issued2020-08
dc.identifier.citationAlexander, G. E., Lin, L., Yoshimaru, E. S., Bharadwaj, P. K., Bergfield, K. L., Hoang, L. T., ... & Trouard, T. P. (2020). Age-related regional network covariance of magnetic resonance imaging gray matter in the rat. Frontiers in aging neuroscience, 12, 267.
dc.identifier.issn1663-4365
dc.identifier.doi10.3389/fnagi.2020.00267
dc.identifier.urihttp://hdl.handle.net/10150/657480
dc.description.abstractHealthy human aging has been associated with brain atrophy in prefrontal and selective temporal regions, but reductions in other brain areas have been observed. We previously found regional covariance patterns of gray matter with magnetic resonance imaging (MRI) in healthy humans and rhesus macaques, using multivariate network Scaled Subprofile Model (SSM) analysis and voxel-based morphometry (VBM), supporting aging effects including in prefrontal and temporal cortices. This approach has yet to be applied to neuroimaging in rodent models of aging. 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. SSM VBM identified a regional pattern that distinguished young from aged rats, characterized by reductions in prefrontal, temporal association/perirhinal, and cerebellar areas with relative increases in somatosensory, thalamic, midbrain, and hippocampal regions. Greater expression of the age-related MRI gray matter pattern was associated with poorer spatial learning in the age groups combined. Aging in the rat is characterized by a regional network pattern of gray matter reductions corresponding to aging effects previously observed in humans and non-human primates. SSM MRI network analyses can advance translational aging neuroscience research, extending from human to small animal models, with potential for evaluating mechanisms and interventions for cognitive aging.
dc.language.isoen
dc.publisherFRONTIERS MEDIA SA
dc.rightsCopyright © 2020 Alexander, Lin, Yoshimaru, Bharadwaj, Bergfield, Hoang,Chawla, Chen, Moeller, Barnes and Trouard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectaging
dc.subjectbehavior
dc.subjectprefrontal cortex
dc.subjectperirhinal cortex
dc.subjectstructural covariance
dc.subjectscaled subprofile model
dc.titleAge-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat
dc.typeArticle
dc.typetext
dc.contributor.departmentUniv Arizona, Dept Psychol
dc.contributor.departmentUniv Arizona, Dept Psychiat
dc.contributor.departmentUniv Arizona, Evelyn F McKnight Brain Inst
dc.contributor.departmentUniv Arizona, Neurosci Grad Interdisciplinary Program
dc.contributor.departmentUniv Arizona, Physiol Sci Grad Interdisciplinary Program
dc.contributor.departmentUniv Arizona, Dept Biomed Engn
dc.contributor.departmentUniv Arizona, Div Neural Syst Memory & Aging
dc.contributor.departmentUniv Arizona, Dept Neurol
dc.contributor.departmentUniv Arizona, Dept Neurosci
dc.identifier.journalFRONTIERS IN AGING NEUROSCIENCE
dc.description.noteOpen access journal
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleFRONTIERS IN AGING NEUROSCIENCE
refterms.dateFOA2021-04-02T23:59:37Z


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Copyright © 2020 Alexander, Lin, Yoshimaru, Bharadwaj, Bergfield, Hoang,Chawla, Chen, Moeller, Barnes and Trouard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
Except where otherwise noted, this item's license is described as Copyright © 2020 Alexander, Lin, Yoshimaru, Bharadwaj, Bergfield, Hoang,Chawla, Chen, Moeller, Barnes and Trouard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).