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.
Highlights
Healthy aging in humans has been associated with brain atrophy on magnetic resonance imaging (MRI) scans often involving prefrontal and selective temporal brain regions
We investigated the effect of aging on the regional covariance of MRI gray matter in 10 young and 10 aged male Fischer 344 rats using Scaled Subprofile Model (SSM) with voxel-based morphometry (VBM) to identify the regional age-related network pattern of gray matter in this rodent model of healthy aging
We used MRI at 7.0T on a voxel basis to evaluate the regional differences in gray matter volume between young adult and aged rats using a multivariate model of regional covariance, the SSM (Moeller et al, 1987; Alexander and Moeller, 1994), a method that has been applied in structural MRI studies of aging in humans (Alexander et al, 2006; Brickman et al, 2007, 2008; Bergfield et al, 2010) and in rhesus macaques (Alexander et al, 2008)
Summary
Healthy aging in humans has been associated with brain atrophy on magnetic resonance imaging (MRI) scans often involving prefrontal and selective temporal brain regions. Studies of human cognitive aging have shown differences between young and older adults in cognitive abilities often thought to be mediated by structures impacted by brain aging, with aspects of memory, executive function, and processing speed preferentially affected (Tisserand and Jolles, 2003; Park and Reuter-Lorenz, 2009; Alexander et al, 2012a). Such human studies, often do not exclude common health conditions of aging, like hypertension, that can contribute to both structural brain changes and the associated cognitive decline (Yoshita et al, 2005). Evaluating alterations of age-related brain networks may be relevant for understanding how aging affects cognitive functions over the lifespan (Burke and Barnes, 2006)
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