Frontiers in Aging Neuroscience (Aug 2020)
Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat
- Gene E. Alexander,
- Gene E. Alexander,
- Gene E. Alexander,
- Gene E. Alexander,
- Gene E. Alexander,
- Gene E. Alexander,
- Lan Lin,
- Lan Lin,
- Lan Lin,
- Eriko S. Yoshimaru,
- Pradyumna K. Bharadwaj,
- Pradyumna K. Bharadwaj,
- Pradyumna K. Bharadwaj,
- Kaitlin L. Bergfield,
- Kaitlin L. Bergfield,
- Kaitlin L. Bergfield,
- Lan T. Hoang,
- Lan T. Hoang,
- Lan T. Hoang,
- Monica K. Chawla,
- Monica K. Chawla,
- Monica K. Chawla,
- Kewei Chen,
- Kewei Chen,
- James R. Moeller,
- Carol A. Barnes,
- Carol A. Barnes,
- Carol A. Barnes,
- Carol A. Barnes,
- Carol A. Barnes,
- Carol A. Barnes,
- Carol A. Barnes,
- Carol A. Barnes,
- Theodore P. Trouard,
- Theodore P. Trouard,
- Theodore P. Trouard
Affiliations
- Gene E. Alexander
- Department of Psychology, University of Arizona, Tucson, AZ, United States
- Gene E. Alexander
- Department of Psychiatry, University of Arizona, Tucson, AZ, United States
- Gene E. Alexander
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Gene E. Alexander
- Neuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United States
- Gene E. Alexander
- Physiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United States
- Gene E. Alexander
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Lan Lin
- Department of Psychology, University of Arizona, Tucson, AZ, United States
- Lan Lin
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Lan Lin
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Eriko S. Yoshimaru
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States
- Pradyumna K. Bharadwaj
- Department of Psychology, University of Arizona, Tucson, AZ, United States
- Pradyumna K. Bharadwaj
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Pradyumna K. Bharadwaj
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Kaitlin L. Bergfield
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Kaitlin L. Bergfield
- Neuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United States
- Kaitlin L. Bergfield
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Lan T. Hoang
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Lan T. Hoang
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Lan T. Hoang
- Division of Neural Systems, Memory and Aging, University of Arizona, Tucson, AZ, United States
- Monica K. Chawla
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Monica K. Chawla
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Monica K. Chawla
- Division of Neural Systems, Memory and Aging, University of Arizona, Tucson, AZ, United States
- Kewei Chen
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Kewei Chen
- Banner Samaritan PET Center and Banner Alzheimer’s Institute, Banner Good Samaritan Medical Center, Phoenix, AZ, United States
- James R. Moeller
- 0Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, Columbia University, New York, NY, United States
- Carol A. Barnes
- Department of Psychology, University of Arizona, Tucson, AZ, United States
- Carol A. Barnes
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Carol A. Barnes
- Neuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United States
- Carol A. Barnes
- Physiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United States
- Carol A. Barnes
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Carol A. Barnes
- Division of Neural Systems, Memory and Aging, University of Arizona, Tucson, AZ, United States
- Carol A. Barnes
- 1Department of Neurology, University of Arizona, Tucson, AZ, United States
- Carol A. Barnes
- 2Department of Neuroscience, University of Arizona, Tucson, AZ, United States
- Theodore P. Trouard
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
- Theodore P. Trouard
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Theodore P. Trouard
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States
- DOI
- https://doi.org/10.3389/fnagi.2020.00267
- Journal volume & issue
-
Vol. 12
Abstract
Healthy 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.
Keywords
