This study investigated the relationship between education and physical activity and the difference between a physiological prediction of age and chronological age. Cortical and subcortical grey matter regional volumes were calculated from 331 healthy adults (range: 19-79 years). Multivariate analyses identified a covariance pattern of brain volumes best predicting chronological age (CA)(R2 = 47%). Individual expression of this brain pattern served as a physiologic measure of brain age (BA). The difference between CA and BA was predicted by education and self-report measures of physical activity. Education and the daily number of flights of stairs climbed were the only two significant predictors of decreased brain age. Effect sizes demonstrated that brain age decreased by 0.95 years for each year of education and by 0.58 years for one additional daily FOSC. Effects of education and FOSC on regional brain volume were largely driven by temporal and subcortical volumes. These results demonstrate that higher levels of education and daily FOSC are related to larger brain volume than predicted by chronological age which supports the utility of regional grey matter volume as a biomarker of healthy brain aging.

Recent studies have found a deleterious effect of age on a wide variety of measures of functional connectivity, and some hints at a relationship between connectivity at rest and cognitive functioning. However, few studies have combined multiple functional connectivity methods, or examined them over a wide range of adult ages, to try to uncover which metrics and networks seem to be particularly sensitive to age-related decline across the adult lifespan. The present study utilized multiple resting state functional connectivity methods in a sample of adults from 20–80 years old to gain a more complete understanding of the effect of aging on network function and integrity. Whole-brain results showed that aging results in weakening average within-network connectivity, lower system segregation and local efficiency, and higher participation coefficient. Network-level results suggested that nearly every primary sensory and cognitive network faces some degree of age-related decline, including reduced within-network connectivity, higher network-based participation coefficient, and reduced network-level local efficiency. Further, some of these connectivity metrics showed relationships with cognitive performance. Thus, these results suggest that a multi-method analysis of functional connectivity data may be critical to capture the full effect of aging on the health of brain networks.

Among older adults, MeDi adherence was associated with less brain atrophy, with an effect similar to 5 years of aging. Higher fish and lower meat intake might be the 2 key food elements that contribute to the benefits of MeDi on brain structure.

We introduce and describe the Reference Ability Neural Network Study and provide initial feasibility data. Based on analyses of large test batteries administered to individuals ranging from young to old, four latent variables, or reference abilities (RAs) that capture the majority of the variance in age-related cognitive change have been identified: episodic memory, fluid reasoning, perceptual speed, and vocabulary. We aim to determine whether spatial fMRI networks can be derived that are uniquely associated with the performance of each reference ability. We plan to image 375 healthy adults (50 per decade from age 20 to 50; 75 per decade from age 50 to 80) while performing a set of 12 cognitive tasks. Data on 174 participants are reported here. Three tasks were grouped a priori into each of the four reference ability domains. We first assessed to what extent both cognitive task scores and activation patterns readily show convergent and discriminant validity, i.e. increased similarity between tasks within the same domain and decreased similarity between tasks between domains, respectively. Block-based time-series analysis of each individual task was conducted for each participant via general linear modeling. We partialled activation common to all tasks out of the imaging data. For both test scores and activation topographies, we then calculated correlations for each of 66 possible pairings of tasks, and compared the magnitude of correlation of tasks within reference ability domains to that of tasks between domains. For the behavioral data, globally there were significantly stronger inter-task correlations within than between domains. When examining individual abilities, 3 of the domains also met these criteria but memory reached only borderline significance. Overall there was greater topographic similarity within reference abilities than between them (p<0.0001), but when examined individually, statistical significance was reached only for episodic memory and perceptual speed. We then turned to a multivariate technique, linear indicator regression analysis, to derive four unique linear combinations of Principal Components (PC) of imaging data that were associated with each RA. We investigated the ability of the identified PCs to predict the reference domain associated with the activation of individual subjects for individual tasks. Median accuracy rates for associating component task activation with a particular reference ability were quite good: memory: 82%; reasoning: 87%; speed: 84%; vocabulary: 77%. These results demonstrate that even using basic GLM analysis, the topography of activation of tasks within a domain is more similar than tasks between domains. The follow-up regression analyses suggest that all tasks with each RA rely on a common network, unique to that RA. Our ultimate goal is to better characterize these RA neural networks and then study how their expression changes across the age span. Our hope is that by focusing on these networks associated with key features of cognitive aging, as opposed to t...

The concept of cognitive reserve (CR) can explain individual differences in susceptibility to cognitive or functional impairment in the presence of age or disease-related brain changes. Epidemiologic evidence indicates that CR helps maintain performance in the face of pathology across multiple cognitive domains. We therefore tried to identify a single, "task-invariant" CR network that is active during the performance of many disparate tasks. In imaging data acquired from 255 individuals age 20-80 while performing 12 different cognitive tasks, we used an iterative approach to derive a multivariate network that was expressed during the performance of all tasks, and whose degree of expression correlated with IQ, a proxy for CR. When applied to held out data or forward applied to fMRI data from an entirely different activation task, network expression correlated with IQ. Expression of the CR pattern accounted for additional variance in fluid reasoning performance over and above the influence of cortical thickness, and also moderated between cortical thickness and reasoning performance, consistent with the behavior of a CR network. The identification of a task-invariant CR network supports the idea that life experiences may result in brain processing differences that might provide reserve against age- or disease-related changes across multiple tasks.

ObjectiveTo determine efficacy of aerobic exercise for cognitive function in younger healthy adults. MethodsIn a randomized, parallel-group, observer-masked, community-based clinical trial, 132 cognitively normal individuals aged 20-67 with below median aerobic capacity were randomly assigned to one of two 6-month, 4-times-weekly conditions: aerobic exercise and stretching/ toning. Efficacy measures included aerobic capacity; cognitive function in several domains (executive function, episodic memory, processing speed, language, and attention), everyday function, body mass index (BMI), and cortical thickness. ResultsAerobic capacity increased significantly (β = 2.718; p = 0.003), and BMI decreased significantly (β = −0.596; p = 0.013) in the aerobic exercise but not in the stretching/toning condition. Executive function improved significantly in the aerobic exercise condition; this effect was moderated by age (β = 0.018 SD/y; p = 0.028). At age 40, the executive function measure increased by 0.228 SD (95% confidence interval [CI] 0.007-0.448), and by 0.596 SD (95% CI 0.219-0.973) at age 60. Cortical thickness increased significantly in the aerobic exercise group in a left frontal region and did not interact with age. Controlling for age and baseline performance, individuals with at least one APOE e4 allele showed less improvement in executive function with aerobic exercise (β = 0.5129, 95% CI 0.0381-0.988; p = 0.0346). ConclusionsThis randomized clinical trial demonstrates the efficacy of aerobic exercise for cognition in adults age 20-67. The effect of aerobic exercise on executive function was more pronounced as age increased, suggesting that it may mitigate age-related declines. Increased cortical thickness suggests that aerobic exercise contributes to brain health in individuals as young as age 20.Clinicaltrials.gov identifier NCT01179958. Classification of evidenceThis study provides Class II evidence that for adults age 20-67 with below median aerobic capacity, aerobic exercise significantly improves executive function but not other measures of cognitive function.

Emerging studies link vascular risk factors and cerebrovascular health to the prevalence and rates of progression in Alzheimer’s disease (AD). The brain’s ability to maintain constant blood flow across a range of cerebral perfusion pressures, or autoregulation, may both promote and result from small vessel cerebrovascular disease and AD-related amyloid pathology. Here, we examined the relationship among cerebral autoregulation, small vessel cerebrovascular disease, and amyloid deposition in 14 non-demented older adults. Reduced cerebral autoregulation, was associated with increased amyloid deposition and increased white matter hyperintensity volume, which, in turn were positively associated with each other. For the first time in humans, we demonstrate an interrelationship among AD pathology, small vessel cerebrovascular disease, and cerebral autoregulation. Vascular factors and AD pathology are not independent but rather appear to interact.

Recent advances in neuroimaging have identified a large number of neural measures that could be involved in age-related declines in cognitive functioning. A popular method of investigating neural-cognition relations has been to determine the brain regions in which a particular neural measure is associated with the level of specific cognitive measures. Although this procedure has been informative, it ignores the strong interrelations that typically exist among the measures in each modality. An alternative approach involves investigating the number and identity of distinct dimensions within the set of neural measures and within the set of cognitive measures prior to examining relations between the two types of measures. The procedure is illustrated with data from 297 adults between 20 and 79 years of age with cortical thickness in different brain regions as the neural measures, and performance on 12 cognitive tests as the cognitive measures. The results revealed that most of the relations between cortical thickness and cognition occurred at a general level corresponding to variance shared among different brain regions and among different cognitive measures. In addition, the strength of the thickness-cognition relation was substantially reduced after controlling the variation in age, which suggests that at least some of the thickness-cognition relations in age-heterogeneous samples may be attributable to the influence of age on each type of measure.