Aging is typically related to changes in brain and cognition, but the aging process is heterogeneous and differs between individuals. Recent research has started investigating the influence of ...cognitive and physical training on cognitive performance, functional brain activity, and brain structure in old age. The functional relevance of neural changes and the interactions among these changes following interventions is still a matter of debate. Here we selectively review research on structural and functional brain correlates of training-induced performance changes in healthy older adults and present exemplary longitudinal intervention studies sorted by the type of training applied (i.e., strategy-based training, process-specific training, and physical exercise). Although many training studies have been conducted recently, within each task domain, the number of studies that used comparable methods and techniques to assess behavioral and neural changes is limited. We suggest that future studies should include a multimodal approach to enhance the understanding of the relation between different levels of brain changes in aging and those changes that result from training. Investigating inter-individual differences in intervention-induced behavioral and neuronal changes would provide more information about who would benefit from a specific intervention and why. In addition, a more systematic examination of the time course of training-related structural and functional changes would improve the current level of knowledge about how learning is implemented in the brain and facilitate our understanding of contradictory results.
Associative memory involves binding two or more items into a coherent memory episode. Relative to memory for single items, associative memory declines greatly in aging. However, older individuals ...vary substantially in their ability to memorize associative information. Although functional studies link associative memory to the medial temporal lobe (MTL) and prefrontal cortex (PFC), little is known about how volumetric differences in MTL and PFC might contribute to individual differences in associative memory. We investigated regional gray-matter volumes related to individual differences in associative memory in a sample of healthy older adults (n=54; age=60years). To differentiate item from associative memory, participants intentionally learned face–scene picture pairs before performing a recognition task that included single faces, scenes, and face–scene pairs. Gray-matter volumes were analyzed using voxel-based morphometry region-of-interest (ROI) analyses. To examine volumetric differences specifically for associative memory, item memory was controlled for in the analyses. Behavioral results revealed large variability in associative memory that mainly originated from differences in false-alarm rates. Moreover, associative memory was independent of individuals' ability to remember single items. Older adults with better associative memory showed larger gray-matter volumes primarily in regions of the left and right lateral PFC. These findings provide evidence for the importance of PFC in intentional learning of associations, likely because of its involvement in organizational and strategic processes that distinguish older adults with good from those with poor associative memory.
The integrity of the brain's white matter is important for neural processing and displays age-related differences, but the contribution of changes in white matter to cognitive aging is unclear. We ...used latent change modeling to investigate this issue in a sample of very old adults (aged 81–103years) assessed twice with a retest interval of 2.3years. Using diffusion-tensor imaging, we probed white matter microstructure by quantifying mean fractional anisotropy and mean diffusivity of six major white matter tracts. Measures of perceptual speed, episodic memory, letter fluency, category fluency, and semantic memory were collected. Across time, alterations of white matter microstructure in the corticospinal tract were associated with decreases of perceptual speed. This association remained significant after statistically controlling for changes in white matter microstructure in the entire brain, in the other demarcated tracts, and in the other cognitive abilities. Changes in brain volume also did not account for the association. We conclude that white matter microstructure is a potent correlate of changes in sensorimotor aspects of behavior in very old age, but that it is unclear whether its impact extends to higher-order cognition.
•Changes of white matter microstructure relate to perceptual speed in very old age.•This association was restricted to the cortico-spinal tract.•White matter is a potent correlate of late aging of sensorimotor performance.
Abstract Introduction The underlying pathological mechanisms linking cardiovascular burden to cognitive decline remain unclear. Methods We investigated the associations of the Framingham general ...cardiovascular risk score (FGCRS), APOE ε4, and brain structure with the Mini-Mental State Examination (MMSE) decline using the 9-year follow-up data from Swedish National Study on Aging and Care in Kungsholmen (n = 2189, age ≥60) and the embedded magnetic resonance imaging (MRI) (n = 448) studies. Volumes of white matter hyperintensities (WMHs), total gray matter, ventricles, and hippocampus were assessed in the MRI sample. Results A higher FGCRS was associated with faster MMSE decline in young-old people (60–72 years) but not in old-old (≥78 years). Larger volumes of cerebral WMHs and ventricles and smaller volumes of total gray matter and hippocampus were all associated with accelerated MMSE decline ( P < .01); these associations were stronger among APOE ε4 carriers than noncarriers. Simultaneously entering multiple brain lesion markers as mediators in the model substantially attenuated the association between FGCRS and MMSE decline. Discussion The effect of cardiovascular risk burden on cognitive deterioration in old age is largely mediated by mixed brain lesions.
Increasing age is associated with deficits in a wide range of cognitive domains as well as with structural brain changes. Recent studies using diffusion tensor imaging (DTI) have shown that ...microstructural integrity of white matter is associated with cognitive performance in elderly persons, especially on tests that rely on perceptual speed. We used structural equation modeling to investigate associations between white matter microstructure and cognitive functions in a population-based sample of elderly persons (age ≥ 60 years), free of dementia, stroke, and neurological disorders (n = 253). Participants underwent a magnetic resonance imaging scan, from which mean fractional anisotropy (FA) and mean diffusivity (MD) of seven white matter tracts were quantified. Cognitive functioning was analyzed according to performance in five task domains (perceptual speed, episodic memory, semantic memory, letter fluency, and category fluency). After controlling for age, FA and MD were exclusively related to perceptual speed. When further stratifying the sample into two age groups, the associations were reliable in the old-old (≥ 78 years) only. This relationship between white matter microstructure and perceptual speed remained significant after excluding persons in a preclinical dementia phase. The observed pattern of results suggests that microstructural white matter integrity may be especially important to perceptual speed among very old adults.
Reduced white matter integrity, as indicated by lower fractional anisotropy (FA) and higher mean diffusivity (MD), has been related to poorer perceptual speed (PS) performance. As the ε4 allele has ...been associated with lower white matter integrity in old age, this represents a potential mechanism through which APOE may affect PS.
To examine whether the association between APOE and PS is mediated by white matter microstructure in very old persons without dementia.
Participants were selected from the population-based SNAC-K study. After excluding persons with dementia, preclinical dementia, and other neurological disorders, 652 persons (age range 78-90) were included in the study, of which 89 had data on diffusion tensor imaging (DTI). We used structural equation modeling to form seven latent white matter factors (FA and MD) and one latent PS factor. Separate analyses were performed for FA and MD and mediational analyses were carried out for tracts where significant associations were observed to both APOE and PS.
APOE was associated with white matter microstructure in 2 out of 14 tracts; ε4 carriers had significantly lower FA in forceps major and higher MD in the cortico-spinal tract. Allowing the white matter microstructure indicators in these tracts to mediate the association between APOE and PS resulted in a markedly attenuated association between these variables. Bootstrapping statistics in the subsample with DTI data (n = 89) indicated that FA in forceps major significantly mediated the association between APOE and PS (indirect effect: -0.070, 95% bias corrected CIs -0.197 to -0.004).
Lower white matter integrity may represent one of several mechanisms through which APOE affects PS performance in elderly persons free of dementia and preclinical dementia.
Research has suggested that variations within the IDE/HHEX gene region may underlie the association of type 2 diabetes with Alzheimer disease (AD). We sought to explore whether IDE genes play a role ...in the association of diabetes with dementia, AD, and structural brain changes using data from two community-based cohorts of older adults and a subsample with structural MRI.
The first cohort, which included dementia-free adults aged ≥75 y (n = 970) at baseline, was followed for 9 y to detect incident dementia (n = 358) and AD (n = 271) cases. The second cohort (for replication), which included 2,060 dementia-free participants aged ≥60 y at baseline, was followed for 6 y to identify incident dementia (n = 166) and AD (n = 121) cases. A subsample (n = 338) of dementia-free participants from the second cohort underwent MRI. HHEX_23 and IDE_9 were genotyped, and diabetes (here including type 2 diabetes and prediabetes) was assessed. In the first cohort, diabetes led to an adjusted hazard ratio (HR) of 1.73 (95% CI 1.19-2.32) and 1.66 (95% CI 1.06-2.40) for dementia and AD, respectively, among all participants. Compared to people carrying the GG genotype without diabetes, AA genotype carriers with diabetes had an adjusted HR of 5.54 (95% CI 2.40-7.18) and 4.81 (95% CI 1.88-8.50) for dementia and AD, respectively. There was a significant interaction between HHEX_23-AA and diabetes on dementia (HR 4.79, 95% CI 1.63-8.90, p = 0.013) and AD (HR 3.55, 95% CI 1.45-9.91, p = 0.025) compared to the GG genotype without diabetes. In the second cohort, the HRs were 1.68 (95% CI 1.04-2.99) and 1.64 (1.02-2.33) for the diabetes-AD and dementia-AD associations, respectively, and 4.06 (95% CI 1.06-7.58, p = 0.039) and 3.29 (95% CI 1.02-8.33, p = 0.044) for the interactions, respectively. MRI data showed that HHEX_23-AA carriers with diabetes had significant structural brain changes compared to HHEX_23-GG carriers without diabetes. No joint effects of IDE_9 and diabetes on dementia were shown. As a limitation, the sample sizes were small for certain subgroups.
A variant in the HHEX_23 gene interacts with diabetes to be associated with a substantially increased risk of dementia and AD, and with structural brain changes among dementia-free elderly people.
Abstract Alterations in iron concentration in certain deep gray matter regions are known to occur in aging and several clinical conditions. In vivo measurements of R2∗ transverse relaxation rates and ...quantitative susceptibility mapping (QSM) have been shown to be strongly correlated with iron concentration in tissue, but their calculation requires the acquisition of a multi-echo gradient recalled echo sequence (MGRE). In the current study, we examined the feasibility of approximating R2∗ rates using metrics derived from fMRI-EPI and T2 -weighted FLAIR images, which are widely available. In a sample of 40 healthy subjects, we obtained these metrics ( v EPI and v FLAIR ), as well as R2∗ rates and QSM estimates, and found significant correlations between v EPI and v FLAIR and R2∗ rates in several subcortical gray matter regions known to accumulate iron, but not in a control corticospinal white matter region. These relationships were preserved after referencing v EPI and v FLAIR with respect to the values in the control region. Effect sizes (above 0.5 for some of the regions, particularly the largest ones) were calculated and put in relation to those of the correlation between QSM and R2∗ rates. We propose that the metrics described here may be applied, possibly in a retrospective fashion, to analyze datasets with available EPI or T2 -weighted FLAIR scans (and lacking a MGRE sequence), to devise new hypotheses regarding links between iron concentration in brain tissue and other variables of interest.
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