Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat
AuthorAlexander, Gene E.
Yoshimaru, Eriko S.
Bharadwaj, Pradyumna K.
Bergfield, Kaitlin L.
Hoang, Lan T.
Chawla, Monica K.
Moeller, James R.
Barnes, Carol A.
Trouard, Theodore P.
AffiliationUniv Arizona, Dept Psychol
Univ Arizona, Dept Psychiat
Univ Arizona, Evelyn F McKnight Brain Inst
Univ Arizona, Neurosci Grad Interdisciplinary Program
Univ Arizona, Physiol Sci Grad Interdisciplinary Program
Univ Arizona, Dept Biomed Engn
Univ Arizona, Div Neural Syst Memory & Aging
Univ Arizona, Dept Neurol
Univ Arizona, Dept Neurosci
scaled subprofile model
MetadataShow full item record
PublisherFRONTIERS MEDIA SA
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.
JournalFRONTIERS IN AGING NEUROSCIENCE
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).
Collection InformationThis 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 email@example.com.
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.
NoteOpen access journal
VersionFinal published version
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).