Background: Varying treatment outcomes in transcranial electrical stimulation (tES) recipients may depend on the amount of current reaching the brain. Brain atrophy associated with normal aging may affect tES current delivery to the brain. Computational models have been employed to compute predicted tES current inside the brain. This study is the largest study that uses computational models to investigate tES field distribution in healthy older adults. Methods: Individualized head models from 587 healthy older adults (mean ¼ 73.9years, 51e95 years) were constructed to create field maps. Two electrode montages (F3-F4, M1-SO) with 2 mA input current were modeled using ROAST with modified codes. A customized template of healthy older adults, the UFAB-587, was created from the same dataset and used to warp individual brains into the same space. Warped models were analyzed to determine the relationship between computed field measures, brain atrophy and age. Main results: Computed field measures were inversely correlated with brain atrophy (R 2 ¼ 0.0829, p ¼ 1.14e-12). Field pattern showed negative correlation with age in brain sub-regions including part of DLPFC and precentral gyrus. Mediation analysis revealed that the negative correlation between age and current density is partially mediated by brain-to-CSF ratio. Conclusions: Computed field measures showed decreasing amount of tES current reaching the brain with increasing atrophy. Therefore, adjusting current dose by modifying tES stimulation parameters in older adults based on degree of atrophy may be necessary to achieve desired stimulation benefits. Results from this study may inform future tES application in healthy older adults.

Type 2 diabetes mellitus (T2DM) increases risk for dementia, including Alzheimer’s disease (AD). Many previous studies of brain changes underlying cognitive impairment in T2DM have applied conventional structural magnetic resonance imaging (MRI) to detect macrostructural changes associated with cerebrovascular disease such as white matter hyperintensities or infarcts. However, such pathology likely reflects end-stage manifestations of chronic decrements in cerebral blood flow (CBF). MRI techniques that measure CBF may (1) elucidate mechanisms that precede irreversible parenchymal damage and (2) serve as a marker of risk for cognitive decline. CBF measured with arterial spin labeling (ASL) MRI may be a useful marker of perfusion deficits in T2DM and related conditions. We examined associations among T2DM, CBF, and cognition in a sample of 49 well-characterized nondemented older adults. Along with a standard T1-weighted scan, a pseudocontinuous ASL sequence optimized for older adults (by increasing post-labeling delays to allow more time for the blood to reach brain tissue) was obtained on a 3T GE scanner to measure regional CBF in FreeSurfer derived regions of interest. Participants also completed a neuropsychological assessment. Results showed no significant differences between individuals with and without T2DM in terms of cortical thickness or regional brain volume. However, adjusting for age, sex, comorbid vascular risk factors, and reference CBF (postcentral gyrus) older adults with T2DM demonstrated reduced CBF in the hippocampus, and inferior temporal, inferior parietal, and frontal cortices. Lower CBF was associated with poorer memory and executive function/processing speed. When adjusting for diabetes, the significant associations between lower regional CBF and poorer executive function/processing speed remained. Results demonstrate that CBF is reduced in older adults with T2DM, and suggest that CBF alterations likely precede volumetric changes. Notably, relative to nondiabetic control participants, those with T2DM showed lower CBF in predilection sites for AD pathology (medial temporal lobe and inferior parietal regions). Findings augment recent research suggesting that perfusion deficits may underlie cognitive decrements frequently observed among older adults with T2DM. Results also suggest that CBF measured with ASL MRI may reflect an early and important marker of risk of cognitive impairment in T2DM and related conditions.

Aging is associated with disruptions in the resting-state functional architecture of the brain. Previous studies have primarily focused on age-related declines in the default mode network (DMN) and its implications in Alzheimer's disease. However, due to mixed findings, it is unclear if changes in resting-state network functional connectivity are linked to cognitive decline in healthy older adults. In the present study, we evaluated the influence of intra-network coherence for four higher-order cognitive resting-state networks on a sensitive measure of cognitive aging (i.e., NIH Toolbox Fluid Cognition Battery) in 154 healthy older adults with a mean age of 71 and education ranging between 12 years and 21 years (mean = 16). Only coherence within the cinguloopercular network (CON) was significantly related to Fluid Cognition Composite scores, explaining more variance in scores than age and education. Furthermore, we mapped CON connectivity onto fluid cognitive subdomains that typically decline in advanced age. Greater CON connectivity was associated with better performance on episodic memory, attention, and executive function tasks. Overall, the present study provides evidence to propose CON coherence as a potential novel neural marker for nonpathological cognitive aging.

Cerebral blood flow (CBF) alterations and amyloid-β (Aβ) accumulation have been independently linked to cognitive deficits in older adults at risk for dementia. Less is known about how CBF and Aβ may interact to affect cognition in cognitively normal older adults. Therefore, we examined potential statistical interactions between CBF and Aβ status in regions typically affected in Alzheimer’s disease (AD) within a sample of older adults from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. Sixty-two cognitively normal participants (mean age = 72 years) underwent neuroimaging and memory testing. Arterial spin labeling magnetic resonance imaging was used to quantify CBF and florbetapir PET amyloid imaging was used to measure Aβ deposition. Aβ status (i.e., positivity versus negativity) was determined based on established cutoffs (Landau et al., 2013). The Rey Auditory Verbal Learning Test was used to assess memory. Linear regression models adjusted for age, education, and sex, demonstrated significant interactions between CBF and Aβ status on memory performance. Among Aβ positive older adults, there were significant negative associations between higher CBF in hippocampus, posterior cingulate, and precuneus and poorer memory performance. In contrast, among Aβ negative older adults, there were no significant associations between CBF and cognition. Our findings extend previous CBF studies of dementia risk by reporting interactions between Aβ status and CBF on memory performance in a sample of well-characterized, cognitively normal older adults. Results suggest that differential CBF-cognition associations can be identified in healthy, asymptomatic Aβ positive older adults relative to Aβ negative individuals. Associations between higherCBF and poorer memory among Aβ positive older adults may reflect a cellular and/or vascular compensatory response to pathologic processes whereby higher CBF is needed to maintain normal memory abilities. Findings indicate that CBF and its associations with cognition may have utility as a reliable marker of brain function early in the AD process when interventions are likely to be beneficial.

We examined cortical amyloid-β (Aβ) levels and interactions with apolipoprotein (APOE) ε4 genotype status across empirically-derived mild cognitive impairment (MCI) subgroups and cognitively normal older adults. Participants were 583 ADNI participants (444 MCI, 139 normal controls [NC]) with baseline florbetapir positron emission tomography (PET) amyloid imaging and neuropsychological testing. Of those with ADNI-defined MCI, a previous cluster analysis [1] classified 51% (n = 227) of the current sample as amnestic MCI, 8% (n = 37) as dysexecutive/mixed MCI, and 41% (n = 180) as cluster-derived normal (cognitively normal). Results demonstrated that the dysexecutive/mixed and amnestic MCI groups showed significantly greater levels of amyloid relative to the cluster-derived normal and NC groups who did not differ from each other. Additionally, 78% of the dysexecutive/mixed, 63% of the amnestic MCI, 42% of the cluster-derived normal, and 34% of the NC group exceeded the amyloid positivity threshold. Finally, a group by APOE genotype interaction demonstrated that APOE ε4 carriers within the amnestic MCI, cluster-derived normal, and NC groups showed significantly greater amyloid accumulation compared to non-carriers of their respective group. Such an interaction was not revealed within the dysexecutive/mixed MCI group which was characterized by both greater cognitive impairment and amyloid accumulation compared to the other participant groups. Our results from the ADNI cohort show considerable heterogeneity in Aβ across all groups studied, even within a group of robust NC participants. Findings suggest that conventional criteria for MCI may be susceptible to false positive diagnostic errors, and that onset of Aβ accumulation may occur earlier in APOE ε4 carriers compared to non-carriers.