Childhood engagement in cognitively stimulating activities moderates relationships between brain structure and cognitive function in adulthood

Greater engagement in cognitively stimulating activities (CSA) during adulthood has been shown to protect against neurocognitive decline, but no studies have investigated whether CSA during childhood protects against effects of brain changes on cognition later in life. The current study tested the moderating role of childhood CSA in the relationships between brain structure and cognitive performance during adulthood. At baseline (N=250) and 5-year follow-up (N=204) healthy adults aged 20-80 underwent MRI to assess four structural brain measures and completed neuropsychological tests to measure three cognitive domains. Participants were categorized into low and high childhood CSA based on self-report questionnaires. Results of multivariable linear regressions analyzing interactions between CSA, brain structure, and cognition showed that higher childhood CSA was associated with a weaker relationship between cortical thickness and memory at baseline, and attenuated the effects of change in cortical thickness and brain volume on decline in processing speed over time. These findings suggest higher CSA during childhood may mitigate the effects of brain structure changes on cognitive function later in life.

Personality traits and cognitive reserve-High openness benefits cognition in the presence of age-related brain changes

Cognitive reserve explains differential susceptibility of cognitive performance to neuropathology. We investigated whether certain personality traits underlie cognitive reserve and are accordingly associated with better cognition and less cognitive decline in the presence of age-related brain changes. We included healthy adults aged 19-80 years for cross-sectional (N=399) and longitudinal (N=273, mean follow-up time=5 years, SD=0.7 years) analyses. Assessment of the BIG5 personality traits openness, conscientiousness, extraversion, agreeableness, and neuroticism was questionnaire-based. Each cognitive domain (perceptual speed, memory, fluid reasoning, vocabulary) was measured with up to six tasks. Cognitive domain-specific brain status variables were obtained by combining 77 structural brain measures into single scores using elastic net regularization. These brain status variables explained up to 43.1% of the variance in cognitive performance. We found that higher openness was associated with higher fluid reasoning and better vocabulary after controlling for brain status, age, and sex. Further, lower brain status was associated with a greater decline in perceptual speed only in individuals with low openness. We conclude that high openness benefits cognitive reserve.

Brain reserve affects the expression of cognitive reserve networks

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.

In vivo tau is associated with change in memory and processing speed, but not reasoning, in cognitively unimpaired older adults

The relationship between tau deposition and cognitive decline in cognitively healthy older adults is still unclear. The tau PET tracer 18F-MK-6240 has shown favorable imaging characteristics to identify early tau deposition in aging. We evaluated the relationship between in vivo tau levels (18F-MK-6240) and retrospective cognitive change over 5 years in episodic memory, processing speed, and reasoning. For tau quantification, a set of regions of interest (ROIs) was selected a priori based on previous literature: (1) total-ROI comprising selected areas, (2) medial temporal lobe-ROI, and (3) lateral temporal lobe-ROI and cingulate/parietal lobe-ROI. Higher tau burden in most ROIs was associated with a steeper decline in memory and speed. There were no associations between tau and reasoning change. The novelty of this finding is that tau burden may affect not only episodic memory, a well-established finding but also processing speed. Our finding reinforces the notion that early tau deposition in areas related to Alzheimer's disease is associated with cognitive decline in cognitively unimpaired individuals, even in a sample with low amyloid-β pathology.

Exploring the Association between Amyloid-β and Memory Markers for Alzheimer's Disease in Cognitively Unimpaired Older Adults

BACKGROUND

Memory tests vary in their sensitivity for detection of pre-symptomatic Alzheimer's disease (AD). The Visual Short-Term Memory Binding Test (VSTMBT) identifies AD-related performance deficits in older adults who are otherwise cognitively unimpaired.

OBJECTIVE

We investigated the association of this psychometric measure with brain amyloidosis and atrophy.

DESIGN

Cross-sectional mixed and correlational.

SETTING

Cognitive Reserve Study from Columbia University.

PARTICIPANTS

a sample of 39 cognitively unimpaired older adults (Age: M=65.3, SD=3.07) was obtained from the above study.

MEASUREMENTS

Extensive neuropsychological and neuroimaging (MRI and amyloid-β PET) assessments were carried out.

RESULTS

Performance on the VSTMBT allowed us to split the sample into Low Binding Cost (LBC, N=21) and High Binding Cost (HBC, N=18). Groups were matched according to age [p=0.702], years of education [0.071], and sex [p=0.291]. HBC's performance was comparable to that seen in symptomatic AD. Groups only differed in their amyloid-β deposition on PET in regions of the right ventral stream linked to visual cognition and affected early in AD pathogenesis (lateral-occipital cortex, p = 0.008; fusiform gyrus, p = 0.017; and entorhinal cortex, p = 0.046). Other regions known to be linked to low-level visual integration function also revealed increased amyloid-β deposition in HBC.

CONCLUSIONS

VSTMB deficits are associated with neuropathogenesis (i.e., amyloid-β deposition) in the earliest affected regions in pre-symptomatic AD. The VSTMB test holds potential for the identification of cognitively unimpaired older adults with very early AD pathogenesis and may thus be a useful tool for early intervention trials or other forms of clinical research.

Neurophysiological markers in community-dwelling older adults with mild cognitive impairment: an EEG study

BACKGROUND

Neurodegeneration and structural changes in the brain due to amyloid deposition have been observed even in individuals with mild cognitive impairment (MCI). EEG measurement is considered an effective tool because it is noninvasive, has few restrictions on the measurement environment, and is simple and easy to use. In this study, we investigated the neurophysiological characteristics of community-dwelling older adults with MCI using EEG.

METHODS

Demographic characteristics, cognitive function, physical function, resting-state MRI and electroencephalogram (rs-EEG), event-related potentials (ERPs) during Simon tasks, and task proportion of correct responses and reaction times (RTs) were obtained from 402 healthy controls (HC) and 47 MCI participants. We introduced exact low-resolution brain electromagnetic tomography-independent component analysis (eLORETA-ICA) to assess the rs-EEG network in community-dwelling older adults with MCI.

RESULTS

A lower proportion of correct responses to the Simon task and slower RTs were observed in the MCI group (p < 0.01). Despite no difference in brain volume between the HC and MCI groups, significant decreases in dorsal attention network (DAN) activity (p < 0.05) and N2 amplitude of ERP (p < 0.001) were observed in the MCI group. Moreover, DAN activity demonstrated a correlation with education (Rs = 0.32, p = 0.027), global cognitive function (Rs = 0.32, p = 0.030), and processing speed (Rs = 0.37, p = 0.010) in the MCI group. The discrimination accuracy for MCI with the addition of the eLORETA-ICA network ranged from 0.7817 to 0.7929, and the area under the curve ranged from 0.8492 to 0.8495.

CONCLUSIONS

The eLORETA-ICA approach of rs-EEG using noninvasive and relatively inexpensive EEG demonstrates specific changes in elders with MCI. It may provide a simple and valid assessment method with few restrictions on the measurement environment and may be useful for early detection of MCI in community-dwelling older adults.

Association of Cognitive Polygenic Index and Cognitive Performance with Age in Cognitively Healthy Adults

Genome-wide association studies have discovered common genetic variants associated with cognitive performance. Polygenic scores that summarize these discoveries explain up to 10% of the variance in cognitive test performance in samples of adults. However, the role these genetics play in cognitive aging is not well understood. We analyzed data from 168 cognitively healthy participants aged 23-77 years old, with data on genetics, neuropsychological assessment, and brain-imaging measurements from two large ongoing studies, the Reference Abilities Neural Networks, and the Cognitive Reserve study. We tested whether a polygenic index previously related to cognition (Cog PGI) would moderate the relationship between age and measurements of the cognitive domains extracted from a neuropsychological evaluation: fluid reasoning, memory, vocabulary, and speed of processing. We further explored the relationship of Cog PGI and age on cognition using Johnson-Neyman intervals for two-way interactions. Sex, education, and brain measures of cortical thickness, total gray matter volume, and white matter hyperintensity were considered covariates. The analysis controlled for population structure-ancestry. There was a significant interaction effect of Cog PGI on the association between age and the domains of memory (Standardized coefficient = -0.158, p-value = 0.022), fluid reasoning (Standardized coefficient = -0.146, p-value = 0.020), and vocabulary (Standardized coefficient = -0.191, p-value = 0.001). Higher PGI strengthened the negative relationship between age and the domains of memory and fluid reasoning while PGI weakened the positive relationship between age and vocabulary. Based on the Johnson-Neyman intervals, Cog PGI was significantly associated with domains of memory, reasoning, and vocabulary for younger adults. There is a significant moderation effect of genetic predisposition for cognition for the association between age and cognitive performance. Genetics discovered in genome-wide association studies of cognitive performance show a stronger association in young and midlife older adults.

Simple topological task-based functional connectivity features predict longitudinal behavioral change of fluid reasoning in the RANN cohort

Recent attention has been given to topological data analysis (TDA), and more specifically persistent homology (PH), to identify the underlying shape of brain network connectivity beyond simple edge pairings by computing connective components across different connectivity thresholds (see Sizemore et al., 2019). In the present study, we applied PH to task-based functional connectivity, computing 0-dimension Betti (B0) curves and calculating the area under these curves (AUC); AUC indicates how quickly a single connected component is formed across correlation filtration thresholds, with lower values interpreted as potentially analogous to lower whole-brain system segregation (e.g., Gracia-Tabuenca et al., 2020). One hundred sixty-three participants from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (age 20-80 years) were tested in-scanner at baseline and five-year follow-up on a battery of tests comprising four domains of cognition (i.e., Stern et al., 2014). We tested for 1.) age-related change in the AUC of the B0 curve over time, 2.) the predictive utility of AUC in accounting for longitudinal change in behavioral performance and 3.) compared system segregation to the PH approach. Results demonstrated longitudinal age-related decreases in AUC for Fluid Reasoning, with these decreases predicting longitudinal declines in cognition, even after controlling for demographic and brain integrity factors; moreover, change in AUC partially mediated the effect of age on change in cognitive performance. System segregation also significantly decreased with age in three of the four cognitive domains but did not predict change in cognition. These results argue for greater application of TDA to the study of aging.

Effects of Brain Maintenance and Cognitive Reserve on Age-Related Decline in Three Cognitive Abilities

OBJECTIVES

Age-related cognitive changes can be influenced by both brain maintenance (BM), which refers to the relative absence over time of changes in neural resources or neuropathologic changes, and cognitive reserve (CR), which encompasses brain processes that allow for better-than-expected behavioral performance given the degree of life-course-related brain changes. This study evaluated the effects of age, BM, and CR on longitudinal changes over 2 visits, 5 years apart, in 3 cognitive abilities that capture most of age-related variability.

METHODS

Participants included 254 healthy adults aged 20-80 years at recruitment. Potential BM was estimated using whole-brain cortical thickness and white matter mean diffusivity at both visits. Education and intelligence quotient (IQ; estimated with American National Adult Reading Test) were tested as moderating factors for cognitive changes in the 3 cognitive abilities.

RESULTS

Consistent with BM-after accounting for age, sex, and baseline performance-individual differences in the preservation of mean diffusivity and cortical thickness were independently associated with relative preservation in the 3 abilities. Consistent with CR-after accounting for age, sex, baseline performance, and structural brain changes-higher IQ, but not education, was associated with reduced 5-year decline in reasoning (β = 0.387, p = .002), and education was associated with reduced decline in speed (β = 0.237, p = .039).

DISCUSSION

These results demonstrate that both CR and BM can moderate cognitive changes in healthy aging and that the 2 mechanisms can make differential contributions to preserved cognition.

Persistent homology-based functional connectivity and its association with cognitive ability: Life-span study

Brain-segregation attributes in resting-state functional networks have been widely investigated to understand cognition and cognitive aging using various approaches [e.g., average connectivity within/between networks and brain system segregation (BSS)]. While these approaches have assumed that resting-state functional networks operate in a modular structure, a complementary perspective assumes that a core-periphery or rich club structure accounts for brain functions where the hubs are tightly interconnected to each other to allow for integrated processing. In this article, we apply a novel method, persistent homology (PH), to develop an alternative to standard functional connectivity by quantifying the pattern of information during the integrated processing. We also investigate whether PH-based functional connectivity explains cognitive performance and compare the amount of variability in explaining cognitive performance for three sets of independent variables: (1) PH-based functional connectivity, (2) graph theory-based measures, and (3) BSS. Resting-state functional connectivity data were extracted from 279 healthy participants, and cognitive ability scores were generated in four domains (fluid reasoning, episodic memory, vocabulary, and processing speed). The results first highlight the pattern of brain-information flow over whole brain regions (i.e., integrated processing) accounts for more variance of cognitive abilities than other methods. The results also show that fluid reasoning and vocabulary performance significantly decrease as the strength of the additional information flow on functional connectivity with the shortest path increases. While PH has been applied to functional connectivity analysis in recent studies, our results demonstrate potential utility of PH-based functional connectivity in understanding cognitive function.

Assessing Flexibility of Solution Strategy: Strategy Shifting as a Measure of Cognitive Reserve

OBJECTIVES

This series of experiments explores whether flexibility in strategy shifting might function as an expression of cognitive reserve (CR).

METHODS

A reasoning task was designed using matrix reasoning stimuli that each required 1 of 2 specific solution strategies: logicoanalytic and visuospatial. It was formatted as a task-switching paradigm, assessing the ability to switch between solution strategies as measured by switch costs. Study 1 was done on Amazon Mechanical Turk and included an assessment of CR proxies. Study 2 used participants who had been studied extensively with neuropsychological assessments and structural neuroimaging.

RESULTS

Study 1 found that switch costs increased with aging. In addition, a relationship between switch costs and CR proxies was noted, suggesting a relationship between the flexibility of strategy shifting and CR. The results of Study 2 again indicated that age negatively affected strategy-shifting flexibility, but that individuals with higher CR as measured with standard proxies performed better. The flexibility measure accounted for additional variance in cognitive performance over that explained by cortical thickness, suggesting that it may contribute to CR.

DISCUSSION

Overall, the results are consistent with the idea that flexibility in strategy shifting might be 1 cognitive process that underlies cognitive reserve.

Older adults compensate for switch, but not mixing costs, relative to younger adults on an intrinsically cued task switching experiment

Introduction

Aging negatively impacts the ability to rapidly and successfully switch between two or more tasks that have different rules or objectives. However, previous work has shown that the context impacts the extent of this age-related impairment: while there is relative age-related invariance when participants must rapidly switch back and forth between two simple tasks (often called "switch costs"), age-related differences emerge when the contexts changes from one in which only one task must be performed to one in which multiple tasks must be performed, but a trial-level switch is not required (e.g., task repeat trials within dual task blocks, often called "mixing costs"). Here, we explored these two kinds of costs behaviorally, and also investigated the neural correlates of these effects.

Methods

Seventy-one younger adults and 175 older adults completed a task-switching experiment while they underwent fMRI brain imaging. We investigated the impact of age on behavioral performance and neural activity considering two types of potential costs: switch costs (dual-task switch trials minus dual-task non-switch trials), and mixing costs (dual-task non-switch minus single-task trials).

Results

We replicated previous behavioral findings, with greater age associated with mixing, but not switch costs. Neurally, we found age-related compensatory activations for switch costs in the dorsal lateral prefrontal cortex, pars opercularis, superior temporal gyrus, and the posterior and anterior cingulate, but age-related under recruitment for mixing costs in fronto-parietal areas including the supramarginal gyrus and pre and supplemental motor areas.

Discussion

These results suggest an age-based dissociation between executive components that contribute to task switching.

Distinct and joint effects of low and high levels of Aβ and tau deposition on cortical thickness

Alzheimer's disease (AD) is defined by the presence of Amyloid-β (Aβ),tau, and neurodegeneration (ATN framework) in the human cerebral cortex. Yet, prior studies have suggested that Aβ deposition can be associated with both cortical thinning and thickening. These contradictory results are attributed to small sample sizes, the presence versus absence of tau, and limited detectability in the earliest phase of protein deposition, which may begin in young adulthood and cannot be captured in studies enrolling only older subjects. In this study, we aimed to find the distinct and joint effects of Aβ andtau on neurodegeneration during the progression from normal to abnormal stages of pathologies that remain elusive. We used18F-MK6240 and 18F-Florbetaben/18F-Florbetapir positron emission tomography (PET) and magnetic resonance imaging (MRI) to quantify tau, Aβ, and cortical thickness in 590 participants ranging in age from 20 to 90. We performed multiple regression analyses to assess the distinct and joint effects of Aβ and tau on cortical thickness using 590 healthy control (HC) and mild cognitive impairment (MCI) participants (141 young, 394 HC elderlies, 52 MCI). We showed thatin participants with normal levels of global Aβdeposition, Aβ uptakewassignificantly associated with increasedcortical thickness regardless of tau (e.g., left entorhinal cortex with t > 3.241, p < 0.0013). The relationship between tau deposition and neurodegeneration was more complex: in participants with abnormal levels of global tau, tau uptake was associated with cortical thinning in several regions of the brain (e.g., left entorhinal with t < -2.80, p < 0.0096 and left insula with t-value < -4.284, p < 0.0001), as reported on prior neuroimaging and neuropathological studies. Surprisingly, in participants with normal levels of global tau, tau was found to be associated with cortical thickening. Moreover, in participants with abnormal levels of global Aβandtau, theresonancebetween them, defined as their correlation throughout the cortex, wasassociated strongly with cortical thinning even when controlling for a direct linear effect. We confirm prior findings of an association between Aβ deposition and cortical thickening and suggest this may also be the case in the earliest stages of deposition in normal aging. We also illustrate that resonance between high levels of Aβ and tau uptake is strongly associated with cortical thinning, emphasizing the effects of Aβ/tau synergy inAD pathogenesis.

Brain connectomics: time for a molecular imaging perspective?

In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific community to take an integrative approach whereby MRI-based, electrophysiological techniques, and molecular imaging contribute to our understanding of the brain connectome.

Polygenic indices for cognition in healthy aging; the role of brain measures

Background

Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging.

Methods

We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20-80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH).

Results

Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age<65) as compared to older adults. For further validation, linear regression for Cog PGI and cognition in the fully adjusted model and adding the interaction between age group and Cog PGI, showed significant results (B = 0.892, SE: 0.325, p = 0.007) driven by young and middle-aged adults (B = -0.403, SE: 0.193, p = 0.039). In ancillary analysis, the Cognitive PGI was not associated with any of the brain measures.

Conclusions

Genetics discovered in GWAS of cognition are associated with cognitive performance in healthy adults across age, but most strongly in young and middle-aged adults. Associations were not explained by brain-structural markers of brain aging. Genetics uncovered in GWAS of cognitive performance may contribute to individual differences established relatively early in life and may not reflect genetic mechanisms of cognitive aging.

Disruption of early visual processing in amyloid-positive healthy individuals and mild cognitive impairment

BACKGROUND

Amyloid deposition is a primary predictor of Alzheimer's disease (AD) and related neurodegenerative disorders. Retinal changes involving the structure and function of the ganglion cell layer are increasingly documented in both established and prodromal AD. Visual event-related potentials (vERP) are sensitive to dysfunction in the magno- and parvocellular visual systems, which originate within the retinal ganglion cell layer. The present study evaluates vERP as a function of amyloid deposition in aging, and in mild cognitive impairment (MCI).

METHODS

vERP to stimulus-onset, motion-onset, and alpha-frequency steady-state (ssVEP) stimuli were obtained from 16 amyloid-positive and 41 amyloid-negative healthy elders and 15 MCI individuals and analyzed using time-frequency approaches. Social cognition was assessed in a subset of individuals using The Awareness of Social Inference Test (TASIT).

RESULTS

Neurocognitively intact but amyloid-positive participants and MCI individuals showed significant deficits in stimulus-onset (theta) and motion-onset (delta) vERP generation relative to amyloid-negative participants (all p < .01). Across healthy elders, a composite index of these measures correlated highly (r =  - .52, p < .001) with amyloid standardized uptake value ratios (SUVR) and TASIT performance. A composite index composed of vERP measures significant differentiated amyloid-positive and amyloid-negative groups with an overall classification accuracy of > 70%.

DISCUSSION

vERP may assist in the early detection of amyloid deposition among older individuals without observable neurocognitive impairments and in linking previously documented retinal deficits in both prodromal AD and MCI to behavioral impairments in social cognition.

Neural similarity across task load relates to cognitive reserve and brain maintenance measures on the Letter Sternberg task: a longitudinal study

The aging process is characterized by change across several measures that index cognitive status and brain integrity. In the present study, 54 cognitively-healthy younger and older adults, were analyzed, longitudinally, on a verbal working memory task to investigate the effect of brain maintenance (i.e., cortical thickness) and cognitive reserve (i.e., NART IQ as proxy) factors on a derived measure of neural efficiency. Participants were scanned using fMRI while presented with the Letter Sternberg task, a verbal working memory task consisting of encoding, maintenance and retrieval phases, where cognitive load is manipulated by varying the number of presented items (i.e., between one and six letters). Via correlation analysis, we looked at region-level and whole-brain relationships between load levels within each phase and then computed a global task measure, what we term phase specificity, to analyze how similar neural responses were across load levels within each phase compared to between each phase. We found that longitudinal change in phase specificity was positively related to longitudinal change in cortical thickness, at both the whole-brain and regional level. Additionally, baseline NART IQ was positively related to longitudinal change in phase specificity over time. Furthermore, we found a longitudinal effect of sex on change in phase specificity, such that females displayed higher phase specificity over time. Cross-sectional findings aligned with longitudinal findings, with the notable exception of behavioral performance being positively linked to phase specificity cross-sectionally at baseline. Taken together, our findings suggest that phase specificity positively relates to brain maintenance and reserve factors and should be better investigated as a measure of neural efficiency.

Longitudinal association between changes in resting-state network connectivity and cognition trajectories: The moderation role of a healthy diet

Introduction

Healthy diet has been shown to alter brain structure and function and improve cognitive performance, and prior work from our group showed that Mediterranean diet (MeDi) moderates the effect of between-network resting-state functional connectivity (rsFC) on cognitive function in a cross-sectional sample of healthy adults. The current study aimed to expand on this previous work by testing whether MeDi moderates the effects of changes in between- and within-network rsFC on changes in cognitive performance over an average of 5 years.

Methods

At baseline and 5-year follow up, 124 adults aged 20-80 years underwent resting state fMRI to measure connectivity within and between 10 pre-defined networks, and completed six cognitive tasks to measure each of four cognitive reference abilities (RAs): fluid reasoning (FLUID), episodic memory, processing speed and attention, and vocabulary. Participants were categorized into low, moderate, and high MeDi groups based on food frequency questionnaires (FFQs). Multivariable linear regressions were used to test relationships between MeDi, change in within- and between-network rsFC, and change in cognitive function.

Results

Results showed that MeDi group significantly moderated the effects of change in overall between-network and within-network rsFC on change in memory performance. Exploratory analyses on individual networks revealed that interactions between MeDi and between-network rsFC were significant for nearly all individual networks, whereas the moderating effect of MeDi on the relationship between within-network rsFC change and memory change was limited to a subset of specific functional networks.

Discussion

These findings suggest healthy diet may protect cognitive function by attenuating the negative effects of changes in connectivity over time. Further research is warranted to understand the mechanisms by which MeDi exerts its neuroprotective effects over the lifespan.

A randomized trial of blood donor iron repletion on red cell quality for transfusion and donor cognition and well-being

Although altruistic regular blood donors are vital for the blood supply, many become iron deficient from donation-induced iron loss. The effects of blood donation-induced iron deficiency on red cell transfusion quality or donor cognition are unknown. In this double-blind, randomized trial, adult iron-deficient blood donors (n = 79; ferritin < 15 μg/L and zinc protoporphyrin >60 μMol/mol heme) who met donation qualifications were enrolled. A first standard blood donation was followed by the gold-standard measure for red cell storage quality: a 51-chromium posttransfusion red cell recovery study. Donors were then randomized to intravenous iron repletion (1 g low-molecular-weight iron dextran) or placebo. A second donation ∼5 months later was followed by another recovery study. Primary outcome was the within-subject change in posttransfusion recovery. The primary outcome measure of an ancillary study reported here was the National Institutes of Health Toolbox-derived uncorrected standard Cognition Fluid Composite Score. Overall, 983 donors were screened; 110 were iron-deficient, and of these, 39 were randomized to iron repletion and 40 to placebo. Red cell storage quality was unchanged by iron repletion: mean change in posttransfusion recovery was 1.6% (95% confidence interval -0.5 to 3.8) and -0.4% (-2.0 to 1.2) with and without iron, respectively. Iron repletion did not affect any cognition or well-being measures. These data provide evidence that current criteria for blood donation preserve red cell transfusion quality for the recipient and protect adult donors from measurable effects of blood donation-induced iron deficiency on cognition. This trial was registered at www.clinicaltrials.gov as NCT02889133 and NCT02990559.

Physical activity moderates the association between white matter hyperintensity burden and cognitive change

Objective

Greater physical activity (PA) could delay cognitive decline, yet the underlying mechanisms remain unclear. White matter hyperintensity (WMH) burden is one of the key brain pathologies that have been shown to predict faster cognitive decline at a late age. One possible pathway is that PA may help maintain cognition by mitigating the detrimental effects of brain pathologies, like WMH, on cognitive change. This study aims to examine whether PA moderates the association between WMH burden and cognitive change.

Materials and methods

This population-based longitudinal study included 198 dementia-free adults aged 20-80 years. Leisure-time physical activity (LTPA) was assessed by a self-reported questionnaire. Occupational physical activity (OPA) was a factor score measuring the physical demands of each job. Total physical activity (TPA) was operationalized as the average of z-scores of LTPA and OPA. Outcome variables included 5-year changes in global cognition and in four reference abilities (fluid reasoning, processing speed, memory, and vocabulary). Multivariable linear regression models were used to estimate the moderation effect of PA on the association between white matter hyperintensities and cognitive change, adjusting for age, sex, education, and baseline cognition.

Results

Over approximately 5 years, global cognition (p < 0.001), reasoning (p < 0.001), speed (p < 0.001), and memory (p < 0.05) scores declined, and vocabulary (p < 0.001) increased. Higher WMH burden was correlated with more decline in global cognition (Spearman's rho = -0.229, p = 0.001), reasoning (rho = -0.402, p < 0.001), and speed (rho = -0.319, p < 0.001), and less increase in vocabulary (rho = -0.316, p < 0.001). Greater TPA attenuated the association between WMH burden and changes in reasoning (β_TPA^*WMH = 0.029, 95% CI = 0.006-0.052, p = 0.013), speed (β_TPA^*WMH = 0.035, 95% CI = -0.004-0.065, p = 0.028), and vocabulary (β_TPA^*WMH = 0.034, 95% CI = 0.004-0.065, p = 0.029). OPA seemed to be the factor that exerted a stronger moderation on the relationship between WMH burden and cognitive change.

Conclusion

Physical activity may help maintain reasoning, speed, and vocabulary abilities in face of WMH burden. The cognitive reserve potential of PA warrants further examination.

Effects of aging on cognitive and brain inter-network integration patterns underlying usual and dual-task gait performance

Introduction

Aging affects the interplay between cognition and gait performance. Neuroimaging studies reported associations between gait performance and structural measures; however, functional connectivity (FC) analysis of imaging data can help to identify dynamic neural mechanisms underlying optimal performance. Here, we investigated the effects on divergent cognitive and inter-network FC patterns underlying gait performance during usual (UW) and dual-task (DT) walking.

Methods

A total of 115 community-dwelling, healthy participants between 20 and 80 years were enrolled. All participants underwent comprehensive cognitive and gait assessments in two conditions and resting state functional MRI (fMRI) scans. Inter-network FC from motor-related to 6 primary cognitive networks were estimated. Step-wise regression models tested the relationships between gait parameters, inter-network FC, neuropsychological scores, and demographic variables. A threshold of p < 0.05 was adopted for all statistical analyses.

Results

UW was largely associated with FC levels between motor and sustained attention networks. DT performance was associated with inter-network FC between motor and divided attention, and processing speed in the overall group. In young adults, UW was associated with inter-network FC between motor and sustained attention networks. On the other hand, DT performance was associated with cognitive performance, as well as inter-network connectivity between motor and divided attention networks (VAN and SAL). In contrast, the older age group (> 65 years) showed increased integration between motor, dorsal, and ventral attention, as well as default-mode networks, which was negatively associated with UW gait performance. Inverse associations between motor and sustained attention inter-network connectivity and DT performance were observed.

Conclusion

While UW relies on inter-network FC between motor and sustained attention networks, DT performance relies on additional cognitive capacities, increased motor, and executive control network integration. FC analyses demonstrate that the decline in cognitive performance with aging leads to the reliance on additional neural resources to maintain routine walking tasks.

Diet moderates the effect of resting state functional connectivity on cognitive function

Past research suggests modifiable lifestyle factors impact structural and functional measures of brain health, as well as cognitive performance, but no study to date has tested the effect of diet on resting state functional connectivity (rsFC), and its relationship with cognition. The current study tested whether Mediterranean diet (MeDi) moderates the associations between internetwork rsFC and cognitive function. 201 cognitively intact adults 20-80 years old underwent resting state fMRI to measure rsFC among 10 networks, and completed 12 cognitive tasks assessing perceptual speed, fluid reasoning, episodic memory, and vocabulary. Food frequency questionnaires were used to categorize participants into low, moderate, and high MeDi adherence groups. Multivariable linear regressions were used to test associations between MeDi group, task performance, and internetwork rsFC. MeDi group moderated the relationship between rsFC and fluid reasoning for nine of the 10 functional networks' connectivity to all others: higher internetwork rsFC predicted lower fluid reasoning performance in the low MeDi adherence group, but not in moderate and high MeDi groups. Results suggest healthy diet may support cognitive ability despite differences in large-scale network connectivity at rest. Further research is warranted to understand how diet impacts neural processes underlying cognitive function over time.

Mediterranean Diet and White Matter Hyperintensity Change over Time in Cognitively Intact Adults

Current evidence on the impact of Mediterranean diet (MeDi) on white matter hyperintensity (WMH) trajectory is scarce. This study aims to examine whether greater adherence to MeDi is associated with less accumulation of WMH. This population-based longitudinal study included 183 cognitively intact adults aged 20−80 years. The MeDi score was obtained from a self-reported food frequency questionnaire; WMH was assessed by 3T MRI. Multivariable linear regression was used to estimate the effect of MeDi on WMH change. Covariates included socio-demographic factors and brain markers. Moderation effects by age, gender, and race/ethnicity were examined, followed by stratification analyses. Among all participants, WMH increased from baseline to follow-up (mean difference [follow-up-baseline] [standard deviation] = 0.31 [0.48], p < 0.001). MeDi adherence was negatively associated with the increase in WMH (β = −0.014, 95% CI = −0.026−−0.001, p = 0.034), adjusting for all covariates. The association between MeDi and WMH change was moderated by age (young group = reference, p-interaction[middle-aged × MeDi] = 0.075, p-interaction[older × MeDi] = 0.037). The association between MeDi and WMH change was observed among the young group (β = −0.035, 95% CI = −0.058−−0.013, p = 0.003), but not among other age groups. Moderation effects by gender and race/ethnicity did not reach significance. Greater adherence to MeDi was associated with a lesser increase in WMH over time. Following a healthy diet, especially at younger age, may help to maintain a healthy brain.

Age-Specific Activation Patterns and Inter-Subject Similarity During Verbal Working Memory Maintenance and Cognitive Reserve

Cognitive Reserve (CR), according to a recent consensus definition of the NIH-funded Reserve and Resilience collaboratory, is constituted by any mechanism contributing to cognitive performance beyond, or interacting with, brain structure in the widest sense. To identity multivariate activation patterns fulfilling this postulate, we investigated a verbal Sternberg fMRI task and imaged 181 people with age coverage in the ranges 20-30 (44 participants) and 55-70 (137 participants). Beyond task performance, participants were characterized in terms of demographics, and neuropsychological assessments of vocabulary, episodic memory, perceptual speed, and abstract fluid reasoning. Participants studied an array of either one, three, or six upper-case letters for 3 s (=encoding phase), then a blank fixation screen was presented for 7 s (=maintenance phase), to be probed with a lower-case letter to which they responded with a differential button press whether the letter was part of the studied array or not (=retrieval phase). We focused on identifying maintenance-related activation patterns showing memory load increases in pattern score on an individual participant level for both age groups. We found such a pattern that increased with memory load for all but one person in the young participants (p < 0.001), and such a pattern for all participants in the older group (p < 0.001). Both patterns showed broad topographic similarities; however, relationships to task performance and neuropsychological characteristics were markedly different and point to individual differences in Cognitive Reserve. Beyond the derivation of group-level activation patterns, we also investigated the inter-subject spatial similarity of individual working memory rehearsal patterns in the older participants' group as a function of neuropsychological and task performance, education, and mean cortical thickness. Higher task accuracy and neuropsychological function was reliably associated with higher inter-subject similarity of individual-level activation patterns in older participants.

Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment

White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition. Here, we parcellated WMH using a novel system that segments WMH based on both lobar regions and distance from the ventricles, dividing the brain into a coordinate system composed of 36 distinct parcels (‘bullseye’ parcellation), and then investigated the effect of distribution on cognition using two different analytic approaches. Data from a well characterized sample of healthy older adults (58 to 84 years) who were free of dementia were included. Cognition was evaluated using 12 computerized tasks, factored onto 4 indices representing episodic memory, speed of processing, fluid reasoning and vocabulary. We first assessed the distribution of WMH according to the bullseye parcellation and tested the relationship between WMH parcellations and performance across the four cognitive domains. Then, we used a data-driven approach to derive latent variables within the WMH distribution, and tested the relation between these latent components and cognitive function. We observed that different, well-defined cognitive constructs mapped to specific WMH distributions. Speed of processing was correlated with WMH in the frontal lobe, while in the case of episodic memory, the relationship was more ubiquitous, involving most of the parcellations. A principal components analysis revealed that the 36 bullseye regions factored onto 3 latent components representing the natural aggrupation of WMH: fronto-parietal periventricular (WMH principally in the frontal and parietal lobes and basal ganglia, especially in the periventricular region); occipital; and temporal and juxtacortical WMH (involving WMH in the temporal lobe, and at the juxtacortical region from frontal and parietal lobes). We found that fronto-parietal periventricular and temporal & juxtacortical WMH were independently associated with speed of processing and episodic memory, respectively. These results indicate that different cognitive impairment phenotypes might present with specific WMH distributions. Additionally, our study encourages future research to consider WMH classifications using parcellations systems other than periventricular and deep localizations.

Application of predictive models in boosting power of Alzheimer's disease clinical trials: A post hoc analysis of phase 3 solanezumab trials

Background

The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and would also respond to the therapeutic intervention.

Objective

To investigate if predictive models can be an effective tool for identifying and excluding people unlikely to show cognitive decline as an enrichment strategy in AD trials.

Method

We used data from the placebo arms of two phase 3, double-blind trials, EXPEDITION and EXPEDITION2. Patients had 18 months of follow-up. Based on the longitudinal data from the placebo arm, we classified participants into two groups: one showed cognitive decline (any negative slope) and the other showed no cognitive decline (slope is zero or positive) on the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-cog). We used baseline data for EXPEDITION to train regression-based classifiers and machine learning classifiers to estimate probability of cognitive decline. Models were applied to EXPEDITION2 data to assess predicted performance in an independent sample. Features used in predictive models included baseline demographics, apolipoprotein E ε4 genotype, neuropsychological scores, functional scores, and volumetric magnetic resonance imaging.

Result

In EXPEDITION, 46.3% of placebo-treated patients showed no cognitive decline and the proportion was similar in EXPEDITION2 (45.6%). Models had high sensitivity and modest specificity in both the training (EXPEDITION) and replication samples (EXPEDITION2) for detecting the stable group. Positive predictive value of models was higher than the base prevalence of cognitive decline, and negative predictive value of models were higher than the base rate of participants who had stable cognition.

Conclusion

Excluding persons with AD unlikely to decline from the active and placebo arms of clinical trials using predictive models may boost the power of AD trials through selective inclusion of participants expected to decline.

Self-awareness for financial decision making abilities is linked to right temporal cortical thickness in older adults

Everyday financial decision making and the awareness of the integrity of one's financial decision making abilities (or financial awareness) are both critical to study in older adults as they can help identify those at risk for making suboptimal financial decisions and prevent financial loss. In the current study, we examined the cognitive and cortical thickness correlates of financial decision making and financial awareness in 59 community-dwelling participants co-enrolled in a larger study (mean age=68.35 years (SD=5.5), mean education=15.91 (SD=2.36), 61% = women, 67% = White, 30% = Black participants). Data from standardized measures of financial decision making and cognition was investigated along with FreeSurfer (v. 5.3) derived thickness regions. Based on metacognitive frameworks, financial awareness was measured along with a well-validated measure of memory awareness. Results revealed that numeracy, executive functioning and vocabulary were associated with financial decision making, whereas in analysis adjusted for financial decision making, memory awareness relative to cognition was most strongly linked to financial awareness. No significant associations between thickness and financial decision making were found. However, both financial and memory awareness were associated with the same right-hemisphere temporal thickness regions underscoring the idea of a common substrate of awareness. Interestingly, our findings converge with the emerging work on financial exploitation in which the right sided temporal regions have been found to play a prominent role. Incorporating the contributing role of self-awareness in various models of financial exploitation will be an important consideration for future studies.

Tolcapone Treatment for Cognitive and Behavioral Symptoms in Behavioral Variant Frontotemporal Dementia: A Placebo-Controlled Crossover Study

BACKGROUND

There are currently no disease-targeted treatments for cognitive or behavioral symptoms in patients with behavioral variant frontotemporal dementia (bvFTD).

OBJECTIVE

To determine the effect of tolcapone, a specific inhibitor of Catechol-O-Methyltransferase (COMT), in patients with bvFTD.

METHODS

In this randomized, double-blind, placebo-controlled, cross-over study at two study sites, we examined the effect of tolcapone on 28 adult outpatients with bvFTD. The primary outcome was reaction time on the N-back cognitive test. As an imaging outcome, we examined differences in the resting blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal intensity between subjects on placebo versus tolcapone performing the N-back test. Secondary outcomes included measures of cognitive performance and behavioral disturbance using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Neuropsychiatric Inventory-Questionnaire (NPI-Q), and Clinical Global Impressions scale (CGI).

RESULTS

Tolcapone was well tolerated and no patients dropped out. The most frequent treatment-related adverse event during tolcapone treatment was elevated liver enzymes (21%). There were no significant differences between tolcapone treatment and placebo in the primary or imaging outcomes. However, there were significant differences between RBANS total scores (p < 0.01), NPI-Q total scores (p = 0.04), and CGI total scores (p = 0.035) between treatment conditions which were driven by differences between baseline and tolcapone conditions. Further, there was a trend toward significance between tolcapone and placebo on the CGI (p = 0.078).

CONCLUSIONS

Further study of COMT inhibition and related approaches with longer duration of treatment and larger sample sizes in frontotemporal lobar degeneration-spectrum disorders may be warranted.

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques

BACKGROUND

Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease (AD), particularly in trials for amyloid-targeted therapy. Predicting Aβ positivity prior to PET imaging can decrease unnecessary patient burden and costs of running these trials.

OBJECTIVE

The aim of this study was to evaluate the performance of a machine learning model in estimating the individual risk of Aβ+ based on gold-standard of PET imaging.

METHODS

We used data from an amnestic mild cognitive impairment (aMCI) subset of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to develop and validate the models. The predictors of Aβ status included demographic and ApoE4 status in all models plus a combination of neuropsychological tests (NP), MRI volumetrics, and cerebrospinal fluid (CSF) biomarkers.

RESULTS

The models that included NP and MRI measures separately showed an area under the receiver operating characteristics (AUC) of 0.74 and 0.72, respectively. However, using NP and MRI measures jointly in the model did not improve prediction. The models including CSF biomarkers significantly outperformed other models with AUCs between 0.89 to 0.92.

CONCLUSIONS

Predictive models can be effectively used to identify persons with aMCI likely to be amyloid positive on a subsequent PET scan.

Age-related disintegration in functional connectivity: Evidence from Reference Ability Neural Network (RANN) cohort

Aging is typically marked by a decline in some domains of cognition. Some theories have linked this decline to a reduction in distinctiveness of processing at the neural level that in turn leads to cognitive decline. Increasing correlations with age among tasks formerly considered independent have been posited, supporting dedifferentiation, although results have been mixed. An alternative view is that tasks become more, and not less, independent of one another with increasing age, suggesting age-related differentiation, or what has also been termed disintegration. In the current study, we investigated if the aging process leads to a loss of behavioral and neural specificity within latent cognitive abilities. To this end, we tested 287 participants (20-80 years) on a battery of 12 in-scanner tests, three each tapping one of four reference abilities. We performed between-task correlations within domain (pertaining to convergent validity), and between domain (pertaining to discriminant validity) at both the behavioral and neural level and found that neural convergent validity was positively associated with behavioral convergent validity. In examining neural validity across the lifespan, we found significant reductions in both within- and between-domain task correlations, with a significant decrease in construct validity (convergent or discriminant) with age. Furthermore, the effect of age on total cognition was significantly mediated by neural construct validity. Taken together, contrary to a hypothesis of dedifferentiation, these correlation reductions suggest that tasks indeed become more independent with advancing age, favoring a differentiation/disintegration hypothesis of aging.

Detecting biological heterogeneity patterns in ADNI amnestic mild cognitive impairment based on volumetric MRI

There is substantial biological heterogeneity among older adults with amnestic mild cognitive impairment (aMCI). We hypothesized that this heterogeneity can be detected solely based on volumetric MRI measures, which potentially have clinical implications and can improve our ability to predict clinical outcomes. We used latent class analysis (LCA) to identify subgroups among persons with aMCI (n = 696) enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI), based on baseline volumetric MRI measures. We used volumetric measures of 10 different brain regions. The subgroups were validated with respect to demographics, cognitive performance, and other AD biomarkers. The subgroups were compared with each other and with normal and Alzheimer's disease (AD) groups with respect to baseline cognitive function and longitudinal rate of conversion. Four aMCI subgroups emerged with distinct MRI patterns: The first subgroup (n = 404), most similar to normal controls in volumetric characteristics and cognitive function, had the lowest incidence of AD. The second subgroup (n = 230) had the most similar MRI profile to early AD, along with poor performance in memory and executive function domains. The third subgroup (n = 36) had the highest global atrophy, very small hippocampus and worst overall cognitive performance. The fourth subgroup (n = 26) had the least amount of atrophy, however still had poor cognitive function specifically in in the executive function domain. Individuals with aMCI who were clinically categorized within one group other showed substantial heterogeneity based on MRI volumetric measures.

Predictive utility of task-related functional connectivity vs. voxel activation

Functional connectivity, both in resting state and task performance, has steadily increased its share of neuroimaging research effort in the last 1.5 decades. In the current study, we investigated the predictive utility regarding behavioral performance and task information for 240 participants, aged 20–77, for both voxel activation and functional connectivity in 12 cognitive tasks, belonging to 4 cognitive reference domains (Episodic Memory, Fluid Reasoning, Perceptual Speed, and Vocabulary). We also added a model only comprising brain-structure information not specifically acquired during performance of a cognitive task. We used a simple brain-behavioral prediction technique based on Principal Component Analysis (PCA) and regression and studied the utility of both modalities in quasi out-of-sample predictions, using split-sample simulations (= 5-fold Monte Carlo cross validation) with 1,000 iterations for which a regression model predicting a cognitive outcome was estimated in a training sample, with a subsequent assessment of prediction success in a non-overlapping test sample. The sample assignments were identical for functional connectivity, voxel activation, and brain structure, enabling apples-to-apples comparisons of predictive utility. All 3 models that were investigated included the demographic covariates age, gender, and years of education. A minimal reference model using simple linear regression with just these 3 covariates was included for comparison as well and was evaluated with the same resampling scheme as described above. Results of the comparison between voxel activation and functional connectivity were mixed and showed some dependency on cognitive outcome; however, mean differences in predictive utility between voxel activation and functional connectivity were rather small in terms of within-modality variability or predictive success. More notably, only in the case of Fluid Reasoning did concurrent functional neuroimaging provided compelling about cognitive performance beyond structural brain imaging or the minimal reference model.

Segregation of functional networks is associated with cognitive resilience in Alzheimer's disease

Cognitive resilience is an important modulating factor of cognitive decline in Alzheimer's disease, but the functional brain mechanisms that support cognitive resilience remain elusive. Given previous findings in normal ageing, we tested the hypothesis that higher segregation of the brain's connectome into distinct functional networks represents a functional mechanism underlying cognitive resilience in Alzheimer's disease. Using resting-state functional MRI, we assessed both resting-state functional MRI global system segregation, i.e. the balance of between-network to within-network connectivity, and the alternate index of modularity Q as predictors of cognitive resilience. We performed all analyses in two independent samples for validation: (i) 108 individuals with autosomal dominantly inherited Alzheimer's disease and 71 non-carrier controls; and (ii) 156 amyloid-PET-positive subjects across the spectrum of sporadic Alzheimer's disease and 184 amyloid-negative controls. In the autosomal dominant Alzheimer's disease sample, disease severity was assessed by estimated years from symptom onset. In the sporadic Alzheimer's sample, disease stage was assessed by temporal lobe tau-PET (i.e. composite across Braak stage I and III regions). In both samples, we tested whether the effect of disease severity on cognition was attenuated at higher levels of functional network segregation. For autosomal dominant Alzheimer's disease, we found higher functional MRI-assessed system segregation to be associated with an attenuated effect of estimated years from symptom onset on global cognition (P = 0.007). Similarly, for patients with sporadic Alzheimer's disease, higher functional MRI-assessed system segregation was associated with less decrement in global cognition (P = 0.001) and episodic memory (P = 0.004) per unit increase of temporal lobe tau-PET. Confirmatory analyses using the alternate index of modularity Q revealed consistent results. In conclusion, higher segregation of functional connections into distinct large-scale networks supports cognitive resilience in Alzheimer's disease.

A framework for identification of a resting-bold connectome associated with cognitive reserve

The concept of cognitive reserve proposes that specific life experiences result in more flexible or resilient cognitive processing allowing some people to cope better with age- or disease-related brain changes than others. Imaging studies seeking to understand the neural implementation of cognitive reserve have most often used task-related fMRI studies. Using that approach, we recently described a task-invariant cognitive-reserve network whose expression correlated with IQ and that moderated between cortical thickness and cognitive performance. Here we sought to identify a pattern of resting BOLD connectivity related to cognitive reserve. We identified a connectome pattern whose connectivity correlated with IQ in both the derivation sample and a separate replication sample. The majority of the edges showing positive relationships with IQ implicate frontal regions. In the derivation sample, connectivity either moderated the relationship between mean cortical thickness and a set of cognitive outcomes or accounted for unique variance in cognitive performance after accounting for cortical thickness. In a replication sample we found that expression of this connectome correlated significantly with the primary endpoint of IQ, and also accounted for unique variance in cognitive performance beyond cortical thickness. Our findings represent an intermediate level of replication and are unlikely to have arisen purely by type-I error. This connectivity pattern therefore meets some of our theoretical criteria for a cognitive reserve-related network and provides insight into the neural implementation of cognitive reserve. Further, expression of this connectome could potentially be used as a direct measure of cognitive reserve, and as an outcome measure for intervention studies that seek to influence cognitive reserve. Future validation of and re-derivation of the pattern in expanded data sets by our and other groups will lead to further improved estimates of cognitive reserve in resting functional connectivity.

Classifying multiple sclerosis patients on the basis of SDMT performance using machine learning

Objective:

To build a model to predict cognitive status reflecting structural, functional, and white matter integrity changes in early multiple sclerosis (MS).

Methods:

Based on Symbol Digit Modalities Test (SDMT) performance, 183 early MS patients were assigned “lower” or “higher” performance groups. Three-dimensional (3D)-T2, T1, diffusion weighted, and resting-state magnetic resonance imaging (MRI) data were acquired in 3T. Using Random Forest, five models were trained to classify patients into two groups based on 1—demographic/clinical, 2—lesion volume/location, 3—local/global tissue volume, 4—local/global diffusion tensor imaging, and 5—whole-brain resting-state-functional-connectivity measures. In a final model, all important features from previous models were concatenated. Area under the receiver operating characteristic curve (AUC) values were calculated to evaluate classifier performance.

Results:

The highest AUC value (0.90) was achieved by concatenating all important features from neuroimaging models. The top 10 contributing variables included volumes of bilateral nucleus accumbens and right thalamus, mean diffusivity of left cingulum-angular bundle, and functional connectivity among hubs of seven large-scale networks.

Conclusion:

These results provide an indication of a non-random brain pattern mostly compromising areas involved in attentional processes specific to patients who perform worse in SDMT. High accuracy of the final model supports this pattern as a potential neuroimaging biomarker of subtle cognitive changes in early MS.

Reference Ability Neural Network-selective functional connectivity across the lifespan

Previous studies have demonstrated that four latent variables, or reference abilities (RAs), can account for the majority of age-related changes in cognition: these being episodic memory, fluid reasoning, speed of processing, and vocabulary. In the current study, we focused on RA-selective functional connectivity patterns that vary with both age and behavior. We analyzed fMRI data from 287 community-dwelling adults (20-80 years) on a battery of tests relating to the four RAs (three tests per RA = 12 tests). Functional connectivity values were calculated between a pre-defined set of 264 ROIs (nodes). Across all participants, we (a) identified connections (edges) that correlated with an RA-specific indicator variable and, indexing only these edges; (b) performed linear regression analysis per edge, regressing indicator correlations (Model 1) and connectivity values (Model 2) on Age, Behavioral Performance, and the Interaction term; and (c) took the conjunction of significant edges between models. Results revealed a different subset of edges for each RA whose connectivity strength and domain-selectivity varied with age and behavior. Strikingly, the fluid reasoning RA was particularly vulnerable to the effects of age and displayed the most extensive connectivity and selectivity "footprint" for behavior. These findings indicate that different functional networks are recruited across RA, with fluid reasoning displaying a special status among them.

fMRI-guided white matter connectivity in fluid and crystallized cognitive abilities in healthy adults

This study examined within-subject differences among three fluid abilities that decline with age: reasoning, episodic memory and processing speed, compared with vocabulary, a crystallized ability that is maintained with age. The data were obtained from the Reference Ability Neural Network (RANN) study from which 221 participants had complete behavioral data for all 12 cognitive tasks, three per ability, along with fMRI and diffusion weighted imaging data. We used fMRI task activation to guide white matter tractography, and generated mean percent signal change in the regions associated with the processing of each ability along with diffusion tensor imaging measures, fractional anisotropy (FA) and mean diffusivity (MD), for each cognitive ability. Qualitatively brain regions associated with vocabulary were more localized and lateralized to the left hemisphere whereas the fluid abilities were associated with brain activations that were more distributed across the brain and bilaterally situated. Using continuous age, we observed smaller correlations between MD and age for white matter tracts connecting brain regions associated with the vocabulary ability than that for the fluid abilities, suggesting that vocabulary white matter tracts were better maintained with age. Furthermore, after multiple comparisons correction and accounting for age, education, and sex, the mean percent signal change for episodic memory showed positive associations with behavioral performance. Overall, the vocabulary ability may be better maintained with age due to the more localized brain regions involved, which places smaller reliance on long distance white matter tracts for signal transduction. These results support the hypothesis that functional activation and white matter structures underlying the vocabulary ability contribute to the ability's greater resistance against aging.

Optimized prediction of cognition based on brain morphometry across the adult life span

We mapped out the combined and unique contributions of 5 different biomarkers for 2 cognitive outcomes in cognitively healthy adults. Beside associations of biomarkers with cognition in the full experimental sample, we focused on how well any such associations would persist in held-out data. Three hundred thirty-five cognitively normal participants, 20-80 years older, were included in the study. Z-scores were computed for fluid reasoning and vocabulary. The following imaging data were included: regional brain volume, regional thickness, fractional anisotropy of white-matter tracts, volumes of select deep gray-matter regions, and global white-matter hyperintensity. Volume accounted for most of the variance in both cognitive domains. In out-of-sample data, fluid reasoning was best predicted by volumes, but vocabulary by the combination of all modalities. Although the predictive utility was better overall for older participants, the information gleaned relative to null models was less for older participants. An optimized set of brain biomarkers can thus predict cognition in out-of-sample data, to various degrees, for both fluid and crystallized intelligence.

Identifying a task-invariant cognitive reserve network using task potency

Cognitive reserve (CR) is thought to protect against the consequence of age- or disease-related structural brain changes across multiple cognitive domains. The neural basis of CR may therefore comprise a functional network that is actively involved in many different cognitive processes. To investigate the existence of such a "task-invariant" CR network, we measured functional connectivity in a cognitively normal sample between 20 and 80 years old (N ​= ​265), both at rest and during the performance of 11 separate tasks that aim to capture four latent cognitive abilities (i.e. vocabulary, episodic memory, processing speed, and fluid reasoning). For each individual, we determined the change in functional connectivity from the resting state to each task state, which is referred to as "task potency" (Chauvin et al., 2018, 2019). Task potency was calculated for each pair among 264 nodes (Power et al., 2012) and then summarized across tasks reflecting the same cognitive ability. Subsequently, we established the correlation between task potency and IQ or education (i.e. CR factors). We identified a set of 57 pairs in which task potency showed significant correlations with IQ, but not education, across all four cognitive abilities. These pairs were included in a principal component analysis, from which we extracted the first component to obtain a latent variable reflecting task potency in this task-invariant CR network. This task potency variable was associated with better episodic memory (β ​= ​0.19, p ​< ​.01) and fluid reasoning performance (β ​= ​0.17, p ​< ​.01) above and beyond the effects of cortical thickness (range [absolute] β ​= ​0.28-0.32, p ​< ​.001). Our identification of this task-invariant network contributes to a better understanding of the mechanism underlying CR, which may facilitate the development of CR-enhancing treatments. Our work also offers a useful alternative operational measure of CR for future studies.

Cortical thickness and its associations with age, total cognition and education across the adult lifespan

Early-life education (years of schooling) has been investigated in regards to cognition, health outcomes and mortality. It has been shown to confer cognitive reserve that might lessen the impact of brain pathology and its impact on cognitive and motor functioning in a variety of neurodegenerative diseases and, for instance, to influence electrical activity [Begum, T., Reza, F., Ahmed, I., & Abdullah, J. M. (2014). Influence of education level on design-induced N170 and P300 components of event related potentials in the human brain. J Integr Neurosci, 13(1), 71–88. doi:10.1142/S0219635214500058]. On the other hand, demonstrations of a direct association between education and brain-structural measures have been more equivocal and scant. The current study sought to identify univariate cortical-thickness patterns underlying education and general intelligence after adjusting for age, gender and possible in-scanner movement in 353 individuals aged 40 to 80. We followed up this idea with multivariate analyses as well. For univariate analyses, our analyses yielded no robust associations between education and general intelligence beyond confounding effects of gender, age and extraneous in-scanner movement. A subsequent multivariate analyses showed a relationship between education and regional cortical thickness with a robust pattern of negative as well as positive loadings in several right-sided brain areas, speaking to a subtle but robust distributed effect of education on cortical thickness. Cortical thickness variance that is the residual of this education-related pattern was shown to be positively associated with age and extraneous in-scanner movement. Our study thus presents a complex picture of the association of education with regional cortical thickness: education was associated with a distributed brain-wide pattern of positive as well as negative loadings with unaccounted residuals being larger for older participants. Focal regional associations beyond demographic and age covariates were not identified.

Benfotiamine and Cognitive Decline in Alzheimer's Disease: Results of a Randomized Placebo-Controlled Phase IIa Clinical Trial

BACKGROUND

In preclinical models, benfotiamine efficiently ameliorates the clinical and biological pathologies that define Alzheimer's disease (AD) including impaired cognition, amyloid-β plaques, neurofibrillary tangles, diminished glucose metabolism, oxidative stress, increased advanced glycation end products (AGE), and inflammation.

OBJECTIVE

To collect preliminary data on feasibility, safety, and efficacy in individuals with amnestic mild cognitive impairment (aMCI) or mild dementia due to AD in a placebo-controlled trial of benfotiamine.

METHODS

A twelve-month treatment with benfotiamine tested whether clinical decline would be delayed in the benfotiamine group compared to the placebo group. The primary clinical outcome was the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog). Secondary outcomes were the clinical dementia rating (CDR) score and fluorodeoxyglucose (FDG) uptake, measured with brain positron emission tomography (PET). Blood AGE were examined as an exploratory outcome.

RESULTS

Participants were treated with benfotiamine (34) or placebo (36). Benfotiamine treatment was safe. The increase in ADAS-Cog was 43% lower in the benfotiamine group than in the placebo group, indicating less cognitive decline, and this effect was nearly statistically significant (p = 0.125). Worsening in CDR was 77% lower (p = 0.034) in the benfotiamine group compared to the placebo group, and this effect was stronger in the APOEɛ4 non-carriers. Benfotiamine significantly reduced increases in AGE (p = 0.044), and this effect was stronger in the APOEɛ4 non-carriers. Exploratory analysis derivation of an FDG PET pattern score showed a treatment effect at one year (p = 0.002).

CONCLUSION

Oral benfotiamine is safe and potentially efficacious in improving cognitive outcomes among persons with MCI and mild AD.

Occupational Patterns of Structural Brain Health: Independent Contributions Beyond Education, Gender, Intelligence, and Age

Occupational activity represents a large percentage of people's daily activity and thus likely is as impactful for people's general and cognitive health as other lifestyle components such as leisure activity, sleep, diet, and exercise. Different occupations, however, require different skills, abilities, activities, credentials, work styles, etc., constituting a rich multidimensional formative exposure with likely consequences for brain development over the lifespan. In the current study, we were interested in how different occupations with their different attributes relate to five variables: structural brain health, duration of early-life education, gender, IQ, and age, although the main focus was the relationship to brain health. To this end, we used the Occupation Information Network (O∗NET), which provides quantification of occupations along 246 items. Occupational patterns with different loadings for these 246 items were derived from 277 community-dwelling adults, ranging in age from 40 to 80, based upon the five subject measures. We found significant patterns underlying four of our variables of interest, with gender and education predictably showing the most numerous and strongest associations, while brain health and intelligence showed weaker associations, and age did not manifest any associations. For the occupational pattern associated with brain health, we found mainly positive associations on items pertaining to rigorous problem-solving, leadership, responsibility, and information processing. We emphasize that the findings are correlational and cannot establish causation. Future extensions of this work will assess the influence of occupation on future cognitive brain status and cognitive performance.