Development of a machine learning algorithm to predict the residual cognitive reserve index.

Elucidating the mechanisms by which late-life neurodegeneration causes cognitive decline requires understanding why some individuals are more resilient than others to the effects of brain change on cognition (cognitive reserve). Currently, there is no way of measuring cognitive reserve that is valid (e.g. capable of moderating brain-cognition associations), widely accessible (e.g. does not require neuroimaging and large sample sizes), and able to provide insight into resilience-promoting mechanisms. To address these limitations, this study sought to determine whether a machine learning approach to combining standard clinical variables could (i) predict a residual-based cognitive reserve criterion standard and (ii) prospectively moderate brain-cognition associations. In a training sample combining data from the University of California (UC) Davis and the Alzheimer's Disease Neuroimaging Initiative-2 (ADNI-2) cohort (N = 1665), we operationalized cognitive reserve using an MRI-based residual approach. An eXtreme Gradient Boosting machine learning algorithm was trained to predict this residual reserve index (RRI) using three models: Minimal (basic clinical data, such as age, education, anthropometrics, and blood pressure), Extended (Minimal model plus cognitive screening, word reading, and depression measures), and Full [Extended model plus Clinical Dementia Rating (CDR) and Everyday Cognition (ECog) scale]. External validation was performed in an independent sample of ADNI 1/3/GO participants (N = 1640), which examined whether the effects of brain change on cognitive change were moderated by the machine learning models' cognitive reserve estimates. The three machine learning models differed in their accuracy and validity. The Minimal model did not correlate strongly with the criterion standard (r = 0.23) and did not moderate the effects of brain change on cognitive change. In contrast, the Extended and Full models were modestly correlated with the criterion standard (r = 0.49 and 0.54, respectively) and prospectively moderated longitudinal brain-cognition associations, outperforming other cognitive reserve proxies (education, word reading). The primary difference between the Minimal model-which did not perform well as a measure of cognitive reserve-and the Extended and Full models-which demonstrated good accuracy and validity-is the lack of cognitive performance and informant-report data in the Minimal model. This suggests that basic clinical variables like anthropometrics, vital signs, and demographics are not sufficient for estimating cognitive reserve. Rather, the most accurate and valid estimates of cognitive reserve were obtained when cognitive performance data-ideally augmented by informant-reported functioning-was used. These results indicate that a dynamic and accessible proxy for cognitive reserve can be generated for individuals without neuroimaging data and gives some insight into factors that may promote resilience.

Vietnamese Insights into Cognitive Aging Program (VIP): Objectives, study design, and cohort description.

Introduction: There is a dearth of research on cognitive aging and dementia in Asian Americans, particularly in Vietnamese Americans, the fourth largest Asian subgroup in the United States. Methods: The Vietnamese Insights into Cognitive Aging Program (VIP) investigates early life adversity and war-related trauma and their associations with cognitive health in a community-based sample of older Vietnamese Americans in Northern California (i.e., Sacramento and Santa Clara counties). Baseline measurements include a comprehensive neuropsychological battery, including measures of global cognition along with executive function, semantic memory, and episodic memory. Data also include measures of functioning, early life adversity and trauma exposure, and psychosocial and traditional cardiovascular disease risk factors. Cognitive assessments will be repeated twice over the course of the data collection period, approximately 12- and 24- months post-baseline. Blood samples collected during Wave 2 will be assayed for biochemical risk factors. Results: Baseline assessments were conducted from January 2022 to November 2023, with N = 548 Vietnamese Americans; mean age ± SD was 73 ± 5.31 years and 55% of participants were women. There were significant differences in social factors by site, with Santa Clara participants having higher education (some college or higher: Sacramento, ≈25%; Santa Clara: ≈48%) and marginally higher incomes compared to Sacramento participants. A higher percentage of Santa Clara participants reported speaking English well or very well (24%) compared to Sacramento participants (13%), although the majority of the entire sample (81%) reported speaking some to no English (response options: not at all; some/a little bit; well/very well). Discussion: This longitudinal study providea a unique opportunity to more fully delineate psychosocial factors that contribute to dementia disparities in diverse and under-engaged populations. Future work will examine cognition, the prevalence of mild cognitive impairment and dementia, and other health outcomes, while controlling for site differences in all analyses. Highlights: Vietnamese Insights into Cognitive Aging Program (VIP) is a new study.VIP has detailed early life and health data on 548 older Vietnamese Americans.History of war and trauma may contribute to Alzheimer's disease and related dementias (ADRD)-related burden.VIP may provide insight into ADRD burden in other understudied groups.

The McCusker Subjective Cognitive Impairment Inventory (McSCI): a novel measure of perceived cognitive decline.

BACKGROUND: Subjective cognitive decline (SCD), i.e. self/other-reported concerns on one's cognitive functioning without objective evidence of significant decline, is an indicator of dementia risk. There is little consensus on reliability and validity of the available SCD measures. Therefore, introducing a novel and psychometrically sound measure of SCD is timely. OBJECTIVE: The psychometric properties of a new SCD measure, the McCusker Subjective Cognitive Impairment Inventory-Self-Report (McSCI-S), are reported. METHODS: Through review of previously published measures as well as our clinical and research data on people with SCD, we developed a 46-item self-report questionnaire to assess concerns on six cognitive domains, namely, memory, language, orientation, attention and concentration, visuoconstruction abilities and executive function. The McSCI-S was examined in a cohort of 526 participants using factor analysis, item response theory analysis and receiver operating characteristic (ROC) curve. RESULTS: A unidimensional model provided acceptable fit (CFI = 0.94, TLI = 0.94, RMSEA [90% CI] = 0.052 [.049, 0.055], WRMR = 1.45). The McSCI-S internal consistency was excellent (.96). A cut-off score of ≥24 is proposed to identify participants with SCDs. Higher McSCI-S scores were associated with poorer general cognition, episodic verbal memory, executive function and greater memory complaints and depressive scores (P < .001), controlling for age, sex and education. CONCLUSIONS: Excellent reliability and construct validity suggest the McSCI-S estimates SCDs with acceptable accuracy while capturing self-reported concerns for various cognitive domains. The psychometric analysis indicated that this measure can be used in cohort studies as well as on individual, clinical settings to assess SCDs.

The Neuropsychological Assessment Battery Driving Scenes Test in a Dementia Clinic.

OBJECTIVE: In dementia research, the Driving Scenes test from the Neuropsychological Assessment Battery has been shown to relate to memory, dementia diagnosis, and functional impairment. The aim of the current study was to examine Driving Scenes and its component scores, and their relationships with cognition and daily functioning, in a mixed dementia clinic sample. METHOD: One hundred U.S. military veterans between the ages of 55 and 88 were administered a full neuropsychological protocol that included Driving Scenes. RESULTS: The Driving Scenes score and its subscores were strongly related to memory skills, and there were additional subscore associations with language and visuospatial functions. Driving Scenes uniquely predicted reported bill payment difficulties and tendency to get lost while driving, which were not predicted by other performances across cognitive domains. CONCLUSION: Driving Scenes is a clinically and functionally relevant measure of memory. Although the Driving Scenes total score remains useful in dementia evaluations, component scores and error scores contribute additional practical information.

Associations between personality and psychological characteristics and cognitive outcomes among older adults.

Prior research has shown that some personality traits are associated with cognitive outcomes and may confirm risk or protection against cognitive decline. The present study expands on previous work to examine the association between a more comprehensive set of psychological characteristics and cognitive performance in a diverse cohort of older adults. We also examine whether controlling for brain atrophy influences the association between psychological characteristics and cognitive function. A total of 157 older adults completed a battery of psychological questionnaires (Openness to Experience, Conscientiousness, Agreeableness, Neuroticism, Extraversion, positive affect, negative affect-sadness, negative affect-anger, sense of purpose, loneliness, grit, and self-efficacy). Cognitive outcomes were measured across multiple domains: episodic memory, semantic memory, executive function, and spatial ability. Baseline brain (MRI) variables included gray matter, hippocampus, and total white matter hyperintensity volume. Parallel process, multilevel models yielded intercept (individual cognitive domain scores) and linear slope (global cognitive change) random effects for the cognitive outcomes. Positive affect (ß = 0.013, SE = 0.005, p = .004) and Openness (ß = 0.018, SE = 0.007, p = .009) were associated with less cognitive change, independent of baseline brain variables and covariates. Greater sadness predicted more cognitive decline when controlling for covariates, but not brain atrophy. A variety of psychological characteristics were associated with the cross-sectional measures of cognition. This study highlights the important impact of positive and negative affect on reducing or enhancing the risk of longitudinal cognitive decline. Such findings are especially important, given the available efficacious interventions that can improve affect. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Self-reported mid- to late-life physical and recreational activities: Associations with late-life cognition.

OBJECTIVE: Physical and recreational activities are behaviors that may modify risk of late-life cognitive decline. We sought to examine the role of retrospectively self-reported midlife (age 40) physical and recreational activity engagement - and self-reported change in these activities from age 40 to initial study visit - in predicting late-life cognition. METHOD: Data were obtained from 898 participants in a longitudinal study of cognitive aging in demographically and cognitively diverse older adults (Age: range = 49-93 years, M = 75, SD = 7.19). Self-reported physical and recreational activity participation at age 40 and at the initial study visit were quantified using the Life Experiences Assessment Form. Change in activities was modeled using latent change scores. Cognitive outcomes were obtained annually (range = 2-17 years) using the Spanish and English Neuropsychological Assessment Scales, which measure verbal episodic memory, semantic memory, visuospatial processing, and executive functioning. RESULTS: Physical activity engagement at age 40 was strongly associated with cognitive performance in all four domains at the initial visit and with global cognitive slope. However, change in physical activities after age 40 was not associated with cognitive outcomes. In contrast, recreational activity engagement - both at age 40 and change after 40 - was predictive of cognitive intercepts and slope. CONCLUSIONS: Retrospectively self-reported midlife physical and recreational activity engagement were strongly associated with late-life cognition - both level of performance and rate of future decline. However, the data suggest that maintenance of recreational activity engagement (e.g., writing, taking classes, reading) after age 40 is more strongly associated with late-life cognition than continued maintenance of physical activity levels.

Modeling the development of cognitive reserve in children: A residual index approach.

OBJECTIVE: To model cognitive reserve (CR) longitudinally in a neurodiverse pediatric sample using a residual index approach, and to test the criterion and construct validity of this index. METHOD: Participants were N = 115 children aged 9.5-13 years at baseline (MAge = 10.48 years, SDAge = 0.61), and n = 43 (37.4%) met criteria for ADHD. The CR index represented variance in Matrix Reasoning scores from the WASI that was unexplained by MRI-based brain variables (bilateral hippocampal volumes, total gray matter volumes, and total white matter hypointensity volumes) or demographics (age and sex). RESULTS: At baseline, the CR index predicted math computation ability (estimate = 0.50, SE = 0.07, p < .001), and word reading ability (estimate = 0.26, SE = 0.10, p = .012). Longitudinally, change in CR over time was not associated with change in math computation ability (estimate = -0.02, SE = 0.03, p < .513), but did predict change in word reading ability (estimate = 0.10, SE = 0.03, p < .001). Change in CR was also found to moderate the relationship between change in word reading ability and white matter hypointensity volume (estimate = 0.10, SE = 0.05, p = .045). CONCLUSIONS: Evidence for the criterion validity of this CR index is encouraging, but somewhat mixed, while construct validity was evidenced through interaction between CR, brain, and word reading ability. Future research would benefit from optimization of the CR index through careful selection of brain variables for a pediatric sample.

Harmonization of cognitive screening tools for dementia across diverse samples: A simulation study.

Introduction: Research focusing on cognitive aging and dementia is a global endeavor. However, cross-national differences in cognition are embedded in other sociocultural differences, precluding direct comparisons of test scores. Such comparisons can be facilitated by co-calibration using item response theory (IRT). The goal of this study was to explore, using simulation, the necessary conditions for accurate harmonization of cognitive data. Method: Neuropsychological test scores from the US Health and Retirement Study (HRS) and the Mexican Health and Aging Study (MHAS) were subjected to IRT analysis to estimate item parameters and sample means and standard deviations. These estimates were used to generate simulated item response patterns under 10 scenarios that adjusted the quality and quantity of linking items used in harmonization. IRT-derived factor scores were compared to the known population values to assess bias, efficiency, accuracy, and reliability of the harmonized data. Results: The current configuration of HRS and MHAS data was not suitable for harmonization, as poor linking item quality led to large bias in both cohorts. Scenarios with more numerous and higher quality linking items led to less biased and more accurate harmonization. Discussion: Linking items must possess low measurement error across the range of latent ability for co-calibration to be successful. HIGHLIGHTS: We developed a statistical simulation platform to evaluate the degree to which cross-sample harmonization accuracy varies as a function of the quality and quantity of linking items.Two large studies of aging-one in Mexico and one in the United States-use three common items to measure cognition.These three common items have weak correspondence with the ability being measured and are all low in difficulty.Harmonized scores derived from the three common linking items will provide biased and inaccurate estimates of cognitive ability.Harmonization accuracy is greatest when linking items vary in difficulty and are strongly related to the ability being measured.

Toward a statistical validation of brain signatures as robust measures of behavioral substrates.

The "brain signature of cognition" concept has garnered interest as a data-driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of behavioral outcomes. Previously we presented a method for computing signatures of episodic memory. However, to be a robust brain measure, the signature approach requires a rigorous validation of model performance across a variety of cohorts. Here we report validation results and provide an example of extending it to a second behavioral domain. In each of two discovery data cohorts, we derived regional brain gray matter thickness associations for two domains: neuropsychological and everyday cognition memory. We computed regional association to outcome in 40 randomly selected discovery subsets of size 400 in each cohort. We generated spatial overlap frequency maps and defined high-frequency regions as "consensus" signature masks. Using separate validation datasets, we evaluated replicability of cohort-based consensus model fits and explanatory power by comparing signature model fits with each other and with competing theory-based models. Spatial replications produced convergent consensus signature regions. Consensus signature model fits were highly correlated in 50 random subsets of each validation cohort, indicating high replicability. In comparisons over each full cohort, signature models outperformed other models. In this validation study, we produced signature models that replicated model fits to outcome and outperformed other commonly used measures. Signatures in two memory domains suggested strongly shared brain substrates. Robust brain signatures may therefore be achievable, yielding reliable and useful measures for modeling substrates of behavioral domains.

Effects of early-life environment and adulthood SES on cognitive change in a multiethnic cohort.

OBJECTIVES: Early-life socioeconomic status (SES) and adversity are associated with late-life cognition and risk of dementia. We examined the association between early-life SES and adversity and late-life cross-sectional cognitive outcomes as well as global cognitive decline, hypothesizing that adulthood SES would mediate these associations. METHODS: Our sample (N = 837) was a racially and ethnically diverse cohort of non-Hispanic/Latino White (48%), Black (27%), and Hispanic/Latino (19%) participants from Northern California. Participant addresses were geocoded to the level of the census tract, and US Census Tract 2010 variables (e.g., percent with high school diploma) were extracted and combined to create a neighborhood SES composite. We used multilevel latent variable models to estimate early-life (e.g., parental education, whether participant ever went hungry) and adult (participant's education, main occupation) SES factors and their associations with cross-sectional and longitudinal cognitive outcomes of episodic memory, semantic memory, executive function, and spatial ability. RESULTS: Child and adult factors were strongly related to domain-specific cognitive intercepts (0.20-0.48 SD per SD of SES factor); in contrast, SES factors were not related to global cognitive change (0.001-0.01 SD per year per SD of SES factor). Adulthood SES mediated a large percentage (68-75%) of the total early-life effect on cognition. CONCLUSIONS: Early-life sociocontextual factors are more strongly associated with cross-sectional late-life cognitive performance compared to cognitive change; this effect is largely mediated through associations with adulthood SES.

Neighborhood socioeconomic status and segregation linked to cognitive decline.

Introduction: Few longitudinal studies have examined the joint impact of neighborhood segregation and neighborhood socioeconomic status (NSES) in cognitive decline over time. Methods: This study included non-Hispanic White (NHW, n = 209) and Black participants (n = 118) whose cognition was evaluated as part of an ongoing longitudinal study. Four distinct categories of segregation and NSES were evaluated for their association with cognitive outcomes (episodic memory, semantic memory, executive function, and spatial ability) using race-specific mixed-effects models. Results: Compared to Black participants living in higher segregation-lower NSES areas, Black participants living in lower segregation-lower NSES areas or higher segregation-higher NSES areas experienced slower decline in episodic memory over time. Compared to NHW participants living in higher segregation-lower NSES areas, NHWs living in lower segregation-higher NSES areas experienced faster decline in spatial ability. Discussion: Segregation and NSES are differentially associated with cognition depending on participant race. Further research is needed to replicate study results.

Tau and amyloid biomarkers modify the degree to which cognitive reserve and brain reserve predict cognitive decline.

OBJECTIVE: Brain reserve, cognitive reserve, and education are thought to protect against late-life cognitive decline, but these variables have not been directly compared to one another in the same model, using future cognitive and functional decline as outcomes. We sought to determine whether the influence of these protective factors on executive function (EF) and daily function decline was dependent upon Alzheimer's disease (AD) pathology severity, as measured by the total tau to beta-amyloid (T-τ/Aß1-42) ratio in cerebrospinal fluid (CSF). METHOD: Participants were 1201 older adult volunteers in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Brain reserve was defined using a composite index of structural brain volumes (total brain matter, hippocampus, and white matter hyperintensity). Cognitive reserve was defined as the variance in episodic memory performance not explained by brain integrity and demographics. RESULTS: At higher levels of T-τ/Aß1-42, brain and cognitive reserve predicted slower decline in EF. Only brain reserve attenuated decline at lower levels of T-τ/Aß1-42. Education had no independent association with cognitive decline. CONCLUSIONS: These results point to a hierarchy of protection against aging- and disease-associated cognitive decline. When pathology is low, only structural brain integrity predicts rate of future EF decline. The ability of cognitive reserve to predict future EF decline becomes stronger as CSF biomarker evidence of AD increases. Although education is typically thought of as a proxy for cognitive reserve, it did not show any protective effects on cognition after accounting for brain integrity and the residual cognitive reserve index.

Residual reserve index modifies the effect of amyloid pathology on fluorodeoxyglucose metabolism: Implications for efficiency and capacity in cognitive reserve.

Background: The residual approach to measuring cognitive reserve (using the residual reserve index) aims to capture cognitive resilience conferred by cognitive reserve, but may be confounded by factors representing brain resilience. We sought to distinguish between brain and cognitive resilience by comparing interactions between the residual reserve index and amyloid, tau, and neurodegeneration ["AT(N)"] biomarkers when predicting executive function. We hypothesized that the residual reserve index would moderate at least one path from an AT(N) biomarker to executive function (consistent with cognitive resilience), as opposed to moderating a path between two AT(N) biomarkers (suggestive of brain resilience). Methods: Participants (N = 332) were from the Alzheimer's Disease Neuroimaging Initiative. The residual reserve index represented the difference between observed and predicted memory performance (a positive residual reserve index suggests higher cognitive reserve). AT(N) biomarkers were: CSF ß-amyloid1-42/ß-amyloid1-40 (A), plasma phosphorylated tau-181 (T), and FDG metabolism in AD-specific regions ([N]). AT(N) biomarkers (measured at consecutive time points) were entered in a sequential mediation model testing the indirect effects from baseline amyloid to executive function intercept (third annual follow-up) and slope (baseline to seventh follow-up), via tau and/or FDG metabolism. The baseline residual reserve index was entered as a moderator of paths between AT(N) biomarkers (e.g., amyloid-tau), and paths between AT(N) biomarkers and executive function. Results: The residual reserve index interacted with amyloid pathology when predicting FDG metabolism: the indirect effect of amyloid → FDG metabolism → executive function intercept and slope varied as a function of the residual reserve index. With lower amyloid pathology, executive function performance was comparable at different levels of the residual reserve index, but a higher residual reserve index was associated with lower FDG metabolism. With higher amyloid pathology, a higher residual reserve index predicted better executive function via higher FDG metabolism. Conclusion: The effect of the residual reserve index on executive function performance via FDG metabolism was consistent with cognitive resilience. This suggests the residual reserve index captures variation in cognitive reserve; specifically, neural efficiency, and neural capacity to upregulate metabolism to enhance cognitive resilience in the face of greater amyloid pathology. Implications for future research include the potential bidirectionality between neural efficiency and amyloid accumulation.

The Western Australia Olfactory Memory Test: Reliability and Validity in a Sample of Older Adults.

OBJECTIVE: The Western Australia Olfactory Memory Test (WAOMT) is a newly developed test designed to meet a need for a comprehensive measure of olfactory episodic memory (OEM) for clinical and research applications. METHOD: This study aimed to establish the psychometric properties of the WAOMT in a sample of 209 community-dwelling older adults. An independent sample of 27 test-naïve participants were recruited to assess test retest reliability (between 7 and 28 days). Scale psychometric properties were examined using item response theory methods, combined samples (final N = 241). Convergent validity was assessed by comparing performance on the WAOMT with a comprehensive neuropsychological battery of domains (verbal and visual episodic memory, and odor identification), as well as other neuropsychological skills. Based on previous literature, it was predicted that the WAOMT would be positively correlated with conceptually similar cognitive domains. RESULTS: The WAOMT is a psychometrically sound test with adequate reliability properties and demonstrated convergent validity with tests of verbal and episodic memory and smell identification. Patterns of performance highlight learning and memory characteristics unique to OEM (e.g., learning curves, cued and free recall). CONCLUSION: Clinical and research implications include streamlining future versions of the WAOMT to ease patient and administrative burden, and the potential to reliably detect early neuropathological changes in healthy older adults with nonimpaired OEM abilities.

When is it appropriate to infer cognitive impairment on the basis of premorbid IQ estimates? A simulation study.

Whether an individual meets psychometric criteria for cognitive impairment is dictated by the comparison criterion, which is typically either a normative mean or a known or estimated previous level of ability. This study investigated the conditions under which adjusting normative expectations based on estimated premorbid intelligence would be appropriate. A simulated data set was derived and several parameters were systematically varied: the correlation between premorbid intelligence and the cognitive test score, the cutoff used to classify a score as "normal" or "abnormal", and the population base rate of cognitive impairment. Simulation results demonstrated that the correlation between premorbid intelligence and the cognitive score was the only parameter to substantially influence the trade-off between the two normative approaches, with correlations above ρ = .35 signifying greater advantage to adjusting normative expectations by premorbid intelligence. These findings inform common neuropsychological practices regarding the application of premorbid intelligence estimates to the detection of cognitive impairment. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Episodic Memory Profile in Autism Spectrum Disorder: A Bayesian Meta-Analysis.

Although autism spectrum disorders (ASD) are commonly characterized by diminished episodic memory, the literature in this area is mixed. We address these inconsistent findings by employing multilevel Bayesian meta-analysis to quantify episodic memory differences between individuals with ASD and typically developing (TD) controls. We used meta-regression to evaluate the effects of test modality (e.g., word list, story recall), delay interval (immediate vs. delayed), retrieval demands (recognition vs. recall), and sensory modality (auditory vs. visual) on episodic memory in ASD. A total of 338 effect sizes from 113 empirical articles, including 5,632 unique participants (ASD = 2,777, TD = 2,855), were included. Results show that the memory deficits associated with ASD were larger for recall (g = -0.52, se = 0.04, 95% CrI [-0.60, -0.43]) compared to recognition (g = -0.25, se = 0.05, 95% CrI [-0.35, -0.14]) and differed based on the testing modality. For example, effect sizes were smallest for words (g = -0.28, se = 0.05, 95% CrI [-0.38, -0.18]), pictures (g = -0.38, se = 0.07, 95% CrI [-0.52, -0.24]), and figure reproduction (g = -0.49, se = 0.11, 95% CrI [-0.70, -0.27]). However, effect sizes for sentences (g = -0.59, se = 0.20, 95% CrI [-1.00, -0.21]), stories (Hedges' g = -0.54, se = 0.08, 95% CrI [-0.69, -0.38]) and staged events (g = -0.75, se = 0.10, 95% CrI [-0.95, -0.55]) were much larger. These findings suggest that ASD is associated with a small to medium reduction in scores on episodic memory tests relative to TD controls.

Longitudinal declines in event-based, but not time-based, prospective memory among community-dwelling older adults.

Age-related deficits in prospective memory (PM) are well established, but it is not known whether PM is stable over time among older adults. In this study, 271 community-dwelling older adults underwent abaseline neuropsychological evaluation and up to three follow-up visits, approximately 2.4 years apart. Mixed effects linear longitudinal models revealed small, but significant linear declines and between-subjects variability in event-based PM performance. There were no changes in performance on measures of time-based PM, retrospective memory, or executive functions. Changes in event-based PM were not associated with age, retrospective memory, executive functions, or everyday functioning. Among older adults, event-based PM appears to be more susceptible to linear declines than does time-based PM, which future research might examine with regard to the possible underlying cognitive mechanisms of cue encoding, monitoring, detection, and retrieval processes.

The latent factor structure underlying regional brain volume change and its relation to cognitive change in older adults.

OBJECTIVE: Late-life changes in cognition and brain integrity are both highly multivariate, time-dependent processes that are essential for understanding cognitive aging and neurodegenerative disease outcomes. The present study seeks to identify a latent variable model capable of efficiently reducing a multitude of structural brain change magnetic resonance imaging (MRI) measurements into a smaller number of dimensions. We further seek to demonstrate the validity of this model by evaluating its ability to reproduce patterns of coordinated brain volume change and to explain the rate of cognitive decline over time. METHOD: We used longitudinal cognitive data and structural MRI scans, obtained from a diverse sample of 358 participants (Mage = 74.81, SD = 7.17), to implement latent variable models for measuring brain change and to estimate the effects of these brain change factors on cognitive decline. RESULTS: Results supported a bifactor model for brain change with four group factors (prefrontal, temporolimbic, medial temporal, and posterior association) and one general change factor (global atrophy). Atrophy in the global (ß = 0.434, SE = 0.070), temporolimbic (ß = 0.275, SE = 0.085), and medial temporal (ß = 0.240, SE = 0.085) factors were the strongest predictors of global cognitive decline. Overall, the brain change model explained 59% of the variance in global cognitive slope. CONCLUSIONS: The current results suggest that brain change across 27 bilateral regions of interest can be grouped into five change factors, three of which (global gray matter, temporolimbic, and medial temporal lobe atrophy) are strongly associated with cognitive decline. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A robust brain signature region approach for episodic memory performance in older adults.

The brain signature concept aims to characterize brain regions most strongly associated with an outcome of interest. Brain signatures derive their power from data-driven searches that select features based solely on performance metrics of prediction or classification. This approach has important potential to delineate biologically relevant brain substrates for prediction or classification of future trajectories. Recent work has used exploratory voxel-wise or atlas-based searches, with some using machine learning techniques to define salient features. These have shown undoubted usefulness, but two issues remain. The preponderance of recent work has been aimed at categorical rather than continuous outcomes, and it is rare for non-atlas reliant voxel-based signatures to be reported that would be useful for modelling and hypothesis testing. We describe a cross-validated signature region model for structural brain components associated with baseline and longitudinal episodic memory across cognitively heterogeneous populations including normal, mild impairment and dementia. We used three non-overlapping cohorts of older participants: from the UC Davis Aging and Diversity cohort (n = 255; mean age 75.3 ± 7.1 years; 128 cognitively normal, 97 mild cognitive impairment, 30 demented and seven unclassified); from Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 (n = 379; mean age 75.1 ± 7.2; 82 cognitively normal, 176 mild cognitive impairment, 121 Alzheimer's dementia); and from ADNI2/GO (n = 680; mean age 72.5 ± 7.1; 220 cognitively normal, 381 mild cognitive impairment and 79 Alzheimer's dementia). We used voxel-wise regression analysis, correcting for multiple comparisons, to generate an array of regional masks corresponding to different association strength levels of cortical grey matter with baseline memory and brain atrophy with memory change. Cognitive measures were episodic memory using Spanish and English Neuropsychological Assessment Scales instruments for UC Davis and ADNI-Mem for ADNI 1 and ADNI2/GO. Performance metric was the adjusted R2 coefficient of determination of each model explaining outcomes in two cohorts other than where it was computed. We compared within-cohort performances of signature models against each other and against other recent signature models of episodic memory. Findings were: (i) two independently generated signature region of interest models performed similarly in a third separate cohort; (ii) a signature region of interest generated in one imaging cohort replicated its performance level when explaining cognitive outcomes in each of other, separate cohorts; and (iii) this approach better explained baseline and longitudinal memory than other recent theory-driven and data-driven models. This suggests our approach can generate signatures that may be easily and robustly applied for modelling and hypothesis testing in mixed cognition cohorts.

Comparison of Education and Episodic Memory as Modifiers of Brain Atrophy Effects on Cognitive Decline: Implications for Measuring Cognitive Reserve.

OBJECTIVE: This study compared the level of education and tests from multiple cognitive domains as proxies for cognitive reserve. METHOD: The participants were educationally, ethnically, and cognitively diverse older adults enrolled in a longitudinal aging study. We examined independent and interactive effects of education, baseline cognitive scores, and MRI measures of cortical gray matter change on longitudinal cognitive change. RESULTS: Baseline episodic memory was related to cognitive decline independent of brain and demographic variables and moderated (weakened) the impact of gray matter change. Education moderated (strengthened) the gray matter change effect. Non-memory cognitive measures did not incrementally explain cognitive decline or moderate gray matter change effects. CONCLUSIONS: Episodic memory showed strong construct validity as a measure of cognitive reserve. Education effects on cognitive decline were dependent upon the rate of atrophy, indicating education effectively measures cognitive reserve only when atrophy rate is low. Results indicate that episodic memory has clinical utility as a predictor of future cognitive decline and better represents the neural basis of cognitive reserve than other cognitive abilities or static proxies like education.