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Cognitive reserve (CR) explains differential susceptibility of cognitive performance to neuropathology. However, as brain pathologies progress, cognitive decline occurs even in individuals with initially high CR. The interplay between the structural brain health (= level of brain reserve) and CR‐related brain networks therefore requires further research. Our sample included 142 individuals aged 60–70 years. National Adult Reading Test intelligence quotient (NART‐IQ) was our CR proxy. On an in‐scanner Letter Sternberg task, we used ordinal trend (OrT) analysis to extract a task‐related brain activation pattern (OrT slope) for each participant that captures increased expression with task load (one, three, and six letters). We assessed whether OrT slope represents a neural mechanism underlying CR by associating it with task performance and NART‐IQ. Additionally, we investigated how the following brain reserve measures affect the association between NART‐IQ and OrT slope: mean cortical thickness, total gray matter volume, and brain volumes proximal to the areas contained in the OrT patterns. We found that higher OrT slope was associated with better task performance and higher NART‐IQ. Further, the brain reserve measures were not directly associated with OrT slope, but they affected the relationship between NART‐IQ and OrT slope: NART‐IQ was associated with OrT slope only in individuals with high brain reserve. The degree of brain reserve has an impact on how (and perhaps whether) CR can be implemented in brain networks in older individuals. [ABSTRACT FROM AUTHOR]

Financial decision‐making (FDM) and awareness of the integrity of one's FDM abilities (or financial awareness) are both critical for preventing financial mistakes. We examined the white matter correlates of these constructs and hypothesized that the tracts connecting the temporal–frontal regions would be most strongly correlated with both FDM and financial awareness. Overall, 49 healthy older adults were included in the FDM analysis and 44 in the financial awareness analyses. The Objective Financial Competency Assessment Inventory was used to measure FDM. Financial awareness was measured by integrating metacognitive ratings into this inventory and was calculated as the degree of overconfidence or underconfidence. Diffusion tensor imaging data were processed with Tracts Constrained by Underlying Anatomy distributed as part of the FreeSurfer analytic suite, which produced average measures of fractional anisotropy and mean diffusivity in 18 white matter tracts along with the overall tract average. As expected, FDM showed the strongest negative associations with average mean diffusivity measure of the superior longitudinal fasciculus ‐temporal (SLFT; r = −.360, p =.011) and ‐parietal (r = −.351, p =.014) tracts. After adjusting for FDM, only the association between financial awareness and average mean diffusivity measure of the right SLFT (r =.310, p =.046) was significant. Overlapping white matter tracts were involved in both FDM and financial awareness. More importantly, these preliminary findings reinforce emerging literature on a unique role of right hemisphere temporal connections in supporting financial awareness. [ABSTRACT FROM AUTHOR]

Background: A healthy dietary pattern, Mediterranean diet (MeDi), has been reported to be associated with better brain and cognition. White matter hyperintensities (WMHs), seen in brain magnetic resonance imaging, are considered to be due to cerebral small vessel diseases and have been shown to predict faster cognitive decline in older adults. However, current evidence on the association between MeDi and WMH is inconsistent and longitudinal data are scarce. This study aims to examine whether better adherence to MeDi is associated with less accumulation of WMH over time. Method: This longitudinal study was conducted among 183 cognitively intact adults aged 20‐80 years. MeDi was calculated from dietary data assessed by a self‐reported food frequency questionnaire, ranging from 0‐55, with a higher score indicating better adherence. WMH was assessed by 3T MRI, and log‐transformed prior to analyses. A one‐sample T‐test was used to examine if WMH burden increased from baseline to follow‐up over an average of five years. Multivariable linear regression was used to estimate the effect of MeDi on the change in WMH. Covariates included age, gender, race/ethnicity, education, IQ, follow‐up interval, caloric intake, baseline WMH, baseline total gray matter volume, and baseline mean cortical thickness. Moderation effects by age (young: <43, middle‐aged: 43‐65, and older: ≥65 years), sex, and race/ethnicity (non‐Hispanic White and other, non‐Hispanic Black, and Hispanic) were examined, followed by stratification analyses. Result: Among all participants, WMH increased from baseline to follow‐up (mean difference [follow‐up‐baseline][standard error(SE)] = 0.31[0.04], p<0.001). A higher MeDi was associated with less increase of WMH (β[SE] = ‐0.014[0.006], p = 0.034), adjusting by all covariates. The association between MeDi and WMH change was moderated by age group (young group as the reference, p‐interaction[middle‐aged*MeDi] = 0.024, p‐interaction[older*MeDi] = 0.017), adjusting by follow‐up interval: the association was observed among the young group (β[SE] = ‐0.038[0.010], p<0.001), but not among the middle‐aged ((β[SE] = ‐0.002[0.013, p = 0.872]) or the older group ((β[SE] = ‐0.002[0.009], p = 0.836). No significant moderation effects by sex or race/ethnicity were found, adjusting by age and follow‐up interval. Conclusion: Better adherence to MeDi was associated with reduced increase of WMH over time. Following a healthy diet, especially at an early age, may help maintain a healthy brain. [ABSTRACT FROM AUTHOR]

The deposition of amyloid-β (Aβ) protein in the human brain is a hallmark of Alzheimer's disease and is related to cognitive decline. However, the relationship between early Aβ deposition and future cognitive impairment remains poorly understood, particularly concerning its spatial distribution and network-level effects. Here, we employed a cross-validated machine learning approach and investigated whether integrating subject-specific brain connectome information with Aβ burden measures improves predictive validity for subsequent cognitive decline. Baseline regional Aβ pathology measures from positron emission tomography (PET) imaging predicted prospective cognitive decline. Incorporating structural connectome, but not functional connectome, information into the Aβ measures improved predictive performance. We further identified a neuropathological signature pattern linked to future cognitive decline, which was validated in an independent cohort. These findings advance our understanding of how Aβ pathology relates to brain networks and highlight the potential of network-based metrics for Aβ-PET imaging to identify individuals at higher risk of cognitive decline., Competing Interests: Competing interest statement The authors have declared no conflicts of interest for this manuscript.