Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat
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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-08-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fnagi.2020.00267/full |
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| author | 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 |
| author_facet | 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 |
| author_sort | Gene E. Alexander |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T00:30:41Z |
| format | Article |
| id | doaj.art-55f80587afe64a78a364eb87e4457d1a |
| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-12-13T00:30:41Z |
| publishDate | 2020-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-55f80587afe64a78a364eb87e4457d1a2022-12-22T00:05:20ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652020-08-011210.3389/fnagi.2020.00267561567Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the RatGene E. Alexander0Gene E. Alexander1Gene E. Alexander2Gene E. Alexander3Gene E. Alexander4Gene E. Alexander5Lan Lin6Lan Lin7Lan Lin8Eriko S. Yoshimaru9Pradyumna K. Bharadwaj10Pradyumna K. Bharadwaj11Pradyumna K. Bharadwaj12Kaitlin L. Bergfield13Kaitlin L. Bergfield14Kaitlin L. Bergfield15Lan T. Hoang16Lan T. Hoang17Lan T. Hoang18Monica K. Chawla19Monica K. Chawla20Monica K. Chawla21Kewei Chen22Kewei Chen23James R. Moeller24Carol A. Barnes25Carol A. Barnes26Carol A. Barnes27Carol A. Barnes28Carol A. Barnes29Carol A. Barnes30Carol A. Barnes31Carol A. Barnes32Theodore P. Trouard33Theodore P. Trouard34Theodore P. Trouard35Department of Psychology, University of Arizona, Tucson, AZ, United StatesDepartment of Psychiatry, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesNeuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United StatesPhysiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDepartment of Psychology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, United StatesDepartment of Psychology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesNeuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDivision of Neural Systems, Memory and Aging, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDivision of Neural Systems, Memory and Aging, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesBanner Samaritan PET Center and Banner Alzheimer’s Institute, Banner Good Samaritan Medical Center, Phoenix, AZ, United States0Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, Columbia University, New York, NY, United StatesDepartment of Psychology, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesNeuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United StatesPhysiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDivision of Neural Systems, Memory and Aging, University of Arizona, Tucson, AZ, United States1Department of Neurology, University of Arizona, Tucson, AZ, United States2Department of Neuroscience, University of Arizona, Tucson, AZ, United StatesEvelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United StatesArizona Alzheimer’s Consortium, Phoenix, AZ, United StatesDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, United StatesHealthy 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.https://www.frontiersin.org/article/10.3389/fnagi.2020.00267/fullagingbehaviorprefrontal cortexperirhinal cortexstructural covariancescaled subprofile model |
| spellingShingle | 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 Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat Frontiers in Aging Neuroscience aging behavior prefrontal cortex perirhinal cortex structural covariance scaled subprofile model |
| title | Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat |
| title_full | Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat |
| title_fullStr | Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat |
| title_full_unstemmed | Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat |
| title_short | Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat |
| title_sort | age related regional network covariance of magnetic resonance imaging gray matter in the rat |
| topic | aging behavior prefrontal cortex perirhinal cortex structural covariance scaled subprofile model |
| url | https://www.frontiersin.org/article/10.3389/fnagi.2020.00267/full |
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