Decline variability of cortical and subcortical regions in aging: a longitudinal study

Describing the trajectories of age-related change for different brain structures has been of interest in many recent studies. However, our knowledge regarding these trajectories and their associations is still limited due to small sample sizes and low numbers of repeated measures. For the present study, we used a large longitudinal dataset (four measurements over 4 years) comprising anatomical data from a sample of healthy older adults (N = 231 at baseline). This dataset enables us to gain new insights about volumetric cortical and subcortical changes and their associations in the context of healthy aging. Brain structure volumes were derived from T1-weighted MRI scans using FreeSurfer segmentation tools. Brain structure trajectories were fitted using mixed models and latent growth curve models to gain information about the mean extent and variability of decline trajectories for different brain structures as well as the associations between individual trajectories. On the group level, our analyses indicate similar linear changes for frontal and parietal brain regions, while medial temporal regions showed an accelerated decline with advancing age. Regarding subcortical regions, some structures showed strong declines (e.g., hippocampus), others showed little decline (e.g., pallidum). Our data provide little evidence for sex differences regarding the aforementioned trajectories. Between-person variability of the person-specific slopes (random slopes) was largest in subcortical and medial temporal brain structures. When looking at the associations between the random slopes from each brain structure, we found that the decline is largely homogenous across the majority of cortical brain structures. In subcortical and medial temporal brain structures, however, more heterogeneity of the decline was observed, meaning that the extent of the decline in one structure is less predictive of the decline in another structure. Taken together, our study contributes to enhancing our understanding of structural brain aging by demonstrating (1) that average volumetric change differs across the brain and (2) that there are regional differences with respect to between-person variability in the slopes. Moreover, our data suggest (3) that random slopes are highly correlated across large parts of the cerebral cortex but (4) that some brain regions (i.e., medial temporal regions) deviate from this homogeneity

Neurogenetic Effects on Cognition in Aging Brains: A Window of Opportunity for Intervention?

Knowledge of genetic influences on cognitive aging can constrain and guide interventions aimed at limiting age-related cognitive decline in older adults. Progress in understanding the neural basis of cognitive aging also requires a better understanding of the neurogenetics of cognition. This selective review article describes studies aimed at deriving specific neurogenetic information from three parallel and interrelated phenotype-based approaches: psychometric constructs, cognitive neuroscience-based processing measures, and brain imaging morphometric data. Developments in newer genetic analysis tools, including genome wide association, are also described. In particular, we focus on models for establishing genotype–phenotype associations within an explanatory framework linking molecular, brain, and cognitive levels of analysis. Such multiple-phenotype approaches indicate that individual variation in genes central to maintaining synaptic integrity, neurotransmitter function, and synaptic plasticity are important in affecting age-related changes in brain structure and cognition. Investigating phenotypes at multiple levels is recommended as a means to advance understanding of the neural impact of genetic variants relevant to cognitive aging. Further knowledge regarding the mechanisms of interaction between genetic and preventative procedures will in turn help in understanding the ameliorative effect of various experiential and lifestyle factors on age-related cognitive decline

Rapid Quantification of White Matter Disconnection in the Human Brain

With an estimated five million new stroke survivors every year and a rapidly aging population suffering from hyperintensities and diseases of presumed vascular origin that affect white matter and contribute to cognitive decline, it is critical that we understand the impact of white matter damage on brain structure and behavior. Current techniques for assessing the impact of lesions consider only location, type, and extent, while ignoring how the affected region was connected to the rest of the brain. Regional brain function is a product of both local structure and its connectivity. Therefore, obtaining a map of white matter disconnection is a crucial step that could help us predict the behavioral deficits that patients exhibit. In the present work, we introduce a new practical method for computing lesion-based white matter disconnection maps that require only moderate computational resources. We achieve this by creating diffusion tractography models of the brains of healthy adults and assessing the connectivity between small regions. We then interrupt these connectivity models by projecting patients' lesions into them to compute predicted white matter disconnection. A quantified disconnection map can be computed for an individual patient in approximately 35 seconds using a single core CPU-based computation. In comparison, a similar quantification performed with other tools provided by MRtrix3 takes 5.47 minutes.Comment: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC

Disconnected aging: cerebral white matter integrity and age-related differences in cognition.

Cognition arises as a result of coordinated processing among distributed brain regions and disruptions to communication within these neural networks can result in cognitive dysfunction. Cortical disconnection may thus contribute to the declines in some aspects of cognitive functioning observed in healthy aging. Diffusion tensor imaging (DTI) is ideally suited for the study of cortical disconnection as it provides indices of structural integrity within interconnected neural networks. The current review summarizes results of previous DTI aging research with the aim of identifying consistent patterns of age-related differences in white matter integrity, and of relationships between measures of white matter integrity and behavioral performance as a function of adult age. We outline a number of future directions that will broaden our current understanding of these brain-behavior relationships in aging. Specifically, future research should aim to (1) investigate multiple models of age-brain-behavior relationships; (2) determine the tract-specificity versus global effect of aging on white matter integrity; (3) assess the relative contribution of normal variation in white matter integrity versus white matter lesions to age-related differences in cognition; (4) improve the definition of specific aspects of cognitive functioning related to age-related differences in white matter integrity using information processing tasks; and (5) combine multiple imaging modalities (e.g., resting-state and task-related functional magnetic resonance imaging; fMRI) with DTI to clarify the role of cerebral white matter integrity in cognitive aging

Structural brain complexity and cognitive decline in late life : A longitudinal study in the Aberdeen 1936 Birth Cohort

Copyright © 2014 Elsevier Inc. All rights reserved.Peer reviewedPostprin

Subregional Hippocampal Thickness Abnormalities in Older Adults with a History of Heavy Cannabis Use.

Background and Aims: Legalization of cannabis (CB) for both medicinal and, in some states, recreational use, has given rise to increasing usage rates across the country. Of particular concern are indications that frequent CB use may be selectively harmful to the developing adolescent brain compared with adult-onset usage. However, the long-term effects of heavy, adolescent CB use on brain structure and cognitive performance in late-life remain unknown. A critical brain region is the hippocampus (HC), where there is a striking intersection between high concentrations of cannabinoid 1 (CB1) receptors and age-related pathology. Design: We investigated whether older adults (average age=66.6+7.2 years old) with a history of early life CB use show morphological differences in hippocampal subregions compared with older, nonusers. Methods: We performed high-resolution magnetic resonance imaging combined with computational techniques to assess cortical thickness of the medial temporal lobe, neuropsychological testing, and extensive drug use histories on 50 subjects (24 formerly heavy cannabis users [CB+ group] abstinent for an average of 28.7 years, 26 nonusers [CB- group]). We investigated group differences in hippocampal subregions, controlling for age, sex, and intelligence (as measured by the Wechsler Test of Adult Reading), years of education, and cigarette use. Results: The CB+ subjects exhibited thinner cortices in subfields cornu ammonis 1 [CA1; F(1,42)=9.96, p=0.0003], and CA2, 3, and the dentate gyrus [CA23DG; F(1,42)=23.17, p<0.0001], and in the entire HC averaged over all subregions [F(1,42)=8.49, p=0.006]. Conclusions: Negative effects of chronic adolescent CB use on hippocampal structure are maintained well into late life. Because hippocampal cortical loss underlies and exacerbates age-related cognitive decline, these findings have profound implications for aging adults with a history of early life usage. Clinical Trial Registration: ClinicalTrials.gov # NCT01874886

Neural correlates of cognitive intervention in persons at risk of developing Alzheimer's disease.

Cognitive training is an emergent approach that has begun to receive increased attention in recent years as a non-pharmacological, cost-effective intervention for Alzheimer's disease (AD). There has been increasing behavioral evidence regarding training-related improvement in cognitive performance in early stages of AD. Although these studies provide important insight about the efficacy of cognitive training, neuroimaging studies are crucial to pinpoint changes in brain structure and function associated with training and to examine their overlap with pathology in AD. In this study, we reviewed the existing neuroimaging studies on cognitive training in persons at risk of developing AD to provide an overview of the overlap between neural networks rehabilitated by the current training methods and those affected in AD. The data suggest a consistent training-related increase in brain activity in medial temporal, prefrontal, and posterior default mode networks, as well as increase in gray matter structure in frontoparietal and entorhinal regions. This pattern differs from the observed pattern in healthy older adults that shows a combination of increased and decreased activity in response to training. Detailed investigation of the data suggests that training in persons at risk of developing AD mainly improves compensatory mechanisms and partly restores the affected functions. While current neuroimaging studies are quite helpful in identifying the mechanisms underlying cognitive training, the data calls for future multi-modal neuroimaging studies with focus on multi-domain cognitive training, network level connectivity, and individual differences in response to training

American Geriatrics Society and National Institute on Aging Bench-to-Bedside conference: sensory impairment and cognitive decline in older adults

This article summarizes the presentations and recommendations of the tenth annual American Geriatrics Society and National Institute on Aging Bench‐to‐Bedside research conference, “Sensory Impairment and Cognitive Decline,” on October 2–3, 2017, in Bethesda, Maryland. The risk of impairment in hearing, vision, and other senses increases with age, and almost 15% of individuals aged 70 and older have dementia. As the number of older adults increases, sensory and cognitive impairments will affect a growing proportion of the population. To limit its scope, this conference focused on sensory impairments affecting vision and hearing. Comorbid vision, hearing, and cognitive impairments in older adults are more common than would be expected by chance alone, suggesting that some common mechanisms might affect these neurological systems. This workshop explored the mechanisms and consequences of comorbid vision, hearing, and cognitive impairment in older adults; effects of sensory loss on the aging brain; and bench‐to‐bedside innovations and research opportunities. Presenters and participants identified many research gaps and questions; the top priorities fell into 3 themes: mechanisms, measurement, and interventions. The workshop delineated specific research questions that provide opportunities to improve outcomes in this growing population.Funding was provided by National Institutes of Health (NIH) Grant U13 AG054139-01. Dr. Whitson's efforts and contributions were supported by R01AG043438, R24AG045050, UH2AG056925, and 5P30AG028716. Dr. Lin's effort and contributions were also supported by R01AG055426, R01HL096812, and R33DC015062. (U13 AG054139-01 - National Institutes of Health (NIH); R01AG043438; R24AG045050; UH2AG056925; 5P30AG028716; R01AG055426; R01HL096812; R33DC015062)Accepted manuscrip