Conventional methods of functional assessment include subjective self- or informant report, which may be biased by personal characteristics, cognitive abilities, and lack of standardization (eg, influence of idiosyncratic task demands). Traditional performance-based assessments offer some advantages over self- or informant reports but are time-consuming to administer and score. This study aims to evaluate the validity and reliability of the Virtual Kitchen Challenge-Version 2 (VKC-2), an objective, standardized, and highly efficient alternative to current functional assessments for older adults across the spectrum of cognitive aging, from preclinical to mild dementia. A total of 236 community-dwelling, diverse older adults completed a comprehensive neuropsychological evaluation to classify cognitive status as healthy, mild cognitive impairment, or mild dementia, after adjustment for demographic variables (age, education, sex, and estimated IQ). Participants completed 2 everyday tasks (breakfast and lunch) in a virtual kitchen (VKC-2) using a touchscreen interface to select objects and sequence steps. Automated scoring reflected completion time and performance efficiency (eg, number of screen interactions, percentage of time spent off-screen, interactions with distractor objects). Participants also completed the VKC-2 tasks using real objects (Real Kitchen). All participants and informants for 219 participants completed questionnaires regarding everyday function. A subsample of participants (n=143) performed the VKC-2 again in a second session, 4-6 weeks after the baseline, for retest analyses. Analyses evaluated construct and convergent validity, as well as retest and internal reliability, of VKC-2 automated scores. A principal component analysis showed that the primary VKC-2 automated scores captured a single dimension and could be combined into a composite score reflecting task efficiency. Construct validity was supported by analyses of covariance results showing that participants with healthy cognition obtained significantly better VKC-2 scores than participants with cognitive impairment (all Ps<.001), even after controlling for demographics and general computer visuomotor dexterity. Convergent validity was supported by significant correlations between VKC-2 scores and performance on the Real Kitchen (r=-0.58 to 0.64, Ps<.001), conventional cognitive test scores (r=-0.50 to -0.22, Ps<.001), and self- and informant report questionnaires evaluating everyday function (r=0.25 to 0.43, Ps<.001). Intraclass correlation coefficients (ICCs) indicated moderate to excellent retest reliability (ICC=0.70-0.90) for VKC-2 scores after 4-6 weeks. Reliability improved in analyses including only participants who reported no change in cognitive status between time 1 and time 2 (n=123). Spearman-Brown correlations showed acceptable to good internal consistency between the VKC-2 tasks (breakfast and lunch) for all scores (0.77-0.84), supporting the use of total scores. The VKC-2 is an efficient, valid, and sensitive measure of everyday function for diverse older adults and holds promise to improve the status quo of functional assessment in aging, particularly when informants are unavailable or unreliable.

Cognitive co-ageing with inequitable political ecologies: Deconditioning & urban public transport.

A systematic review of multivariate studies in cognitive aging: Introducing the concept of cognitive organization.

Sex-specific factors and APOEε4 genotype alter functional connectivity at middle age.

Cognitive ageing: sex and life course social class differences in England.

Genistein ameliorates glucose-induced β-amyloid toxicity, oxidative stress, and aging in the C. elegans model of Alzheimer's disease.

The relationship between co-use of tobacco and alcohol and cognitive decline in middle-aged and older Chinese males: A cross-lagged panel network analysis.

Absolute and relative handgrip strength as indicators of cognitive impairment: Evidence from the Mexican cognitive aging study

Eye-tracking technology is one of the fundamental tools in scientific research. Eye-tracking data can provide detailed insights into visual attention, perception, and other cognitive processes. This bibliometric analysis aims to systematically review the state-of-the-art of eye-tracking studies in the behavioural sciences, identify emerging research trends and thematic areas, and uncover future research directions. A comprehensive analysis was conducted using the SCOPUS database. The search strategy included keywords related to eye-tracking. The retrieved articles were analysed for publication trends, co-authorship networks, keyword co-occurrences, and thematic evolution over time. The analysis identified 5,825 relevant articles published between 2015 and 2024. The state-of-the-art of this area of study in behavioural sciences reveals a substantial increase in publications over the past decade. Research trends and thematic analysis highlight seven key areas of study, in particular: (1) driving behaviour; (2) social cognition; (3) cognitive ageing; (4) language processing; (5) visual cognition; (6) cognitive processes; and (7) electroencephalography (EEG). For future work, the analysis suggests promising research avenues, including the application of eye-tracking in virtual reality environments, longitudinal studies of attentional development, and interdisciplinary approaches combining eye-tracking with machine learning techniques. This study provides a comprehensive overview of the current landscape of eye-tracking research in behavioural sciences. The findings emphasise the versatility of eye-tracking as a methodological tool and highlight key areas for future investigation. By identifying emerging trends and suggesting new research directions, this study contributes to the ongoing development of eye-tracking methodologies in behavioural research.

BackgroundOlder Hispanic/LatinX populations are at increased risk compared with older White adults to develop dementia, yet few studies have characterized their performance on standardized neuropsychological batteries such as the NIH Toolbox Cognition Battery (NIHTB‐CB). We investigated the differences of NIHTB‐CB tests and composites in a 100% Spanish‐speaking and Hispanic sample of healthy agers, compared to those diagnosed with amnestic Mild Cognitive Impairment (aMCI) and mild dementia of the Alzheimer's Type (mDAT).MethodAs part of the larger Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA) Study, we assessed 125 healthy agers (87.2% female; Mage = 73.2, SDage = 4.99), 123 with an aMCI diagnosis (63.4% female; Mage = 76.50, SDage = 6.30), and 28 with mild DAT (64.3% female; Mage = 75.60, SDage = 7.62). The NIHTB‐CB was administered by trained examiners included Oral Reading Recognition (ORR), Picture Vocabulary (PV), List Sort Working Memory (LSWM) Picture Sequence Memory (PSM), Pattern Comparison Processing Speed (PC), Dimensional Change Card Sort (DCCS), Flanker Inhibitory Control and Attention (Flanker) tests. In a series of ANOVAs, we investigated the differences in unadjusted scale scores, adjusting for age, education, sex as a biological variable, and study site.ResultCompared to healthy agers, those with aMCI scored significantly lower on all NIHTB‐CB measures and composites, with high standardized mean differences for LSWM (Diff = ‐11.73, 95% CI=[‐14.88, ‐8.57]), PCPS (Diff = ‐8.62, 95% CI=[‐12.44, ‐4.8]), DCCS (Diff = ‐8.19, 95% CI=[‐10.95, ‐5.43]), and PV (Diff = ‐8.02, 95% CI=[‐10.64, ‐5.39]). Observed differences between the healthy ager and mild DAT group were even higher, as expected: LSWM (Diff = ‐14.29, 95% CI=[‐20.55, ‐8.02]), PCPS (Diff = ‐17.71, 95% CI=[‐24.25, ‐11.17]), DCCS (Diff = ‐11.34, 95% CI=[‐16.27, ‐6.41]), and PV (Diff = ‐12.57, 95% CI=[‐16.93, ‐8.22]). The NIHTB‐CB differentiated between aMCI and mild DAT only on PCPS and PV. These differences were independent of sex or age effects, except for PCPS, where an increase in age predicted lower performance.ConclusionNearly all measures within the NIHTB‐CB significantly differentiate between healthy controls and individuals with aMCI, and healthy agers and individuals with mDAT among older Spanish‐speaking adults.

Background“Quality of life” is defined as an individual's perception of their position in life according to cultural contexts and values. This concept represents one of the main priorities in the management of people living with dementia, modifying the perceived status of the disease, duration of care, neuropsychiatric symptoms, etc. Different questionnaires, applicable to patients and their caregivers, have been developed to assess quality of life. However, few studies compare the scores obtained between both of these subjects.MethodA cross‐sectional, observational, and comparative study was conducted on patients from the Cognitive Aging and Dementia Clinic diagnosed with Alzheimer's, Vascular, or Mixed dementia in mild or moderate stages and their caregivers. The study describes demographic variables and compares the scores obtained in the quality of life scales.ResultWe obtained 21 responses from patients (61.9% and 38.1% with mild and moderate stage dementia) and their caregivers. The group with mild dementia had a mean age of 77 years (62‐90, p = 0.332), mostly female (47.6%, p = 0.410), and had mixed pathology (33.3%, p = 0.023). In the moderate dementia group, the mean age was 73 years (64‐85, p = 0.332), also primarily female (23.8%, p = 0.410), and the most frequent diagnosis was Alzheimer's (28.5%, p = 28.5%). The caregivers were mainly women, children, or spouses (42.8% and 52.5%, p = 0.676) and didn't have depression (p = 0.590). There were no significant differences in the total QoL‐AD score (34.1 in patients vs. 33.8 in caregivers, p = 0.880), except for self‐perception (p = 0.029) and economic status (p = 0.015), which were both higher for patients. Neither were there differences in the WHOQOL‐Bref questionnaire (81.19 in patients vs. 78.2 in caregivers, p = 0.502).ConclusionUnlike previous studies, no significant differences were observed between the responses obtained from patients and caregivers when assessing quality of life. However, the scores for items related to self‐perception and economic status differed. Extending the study to other dementia syndromes or other care centers could strengthen and broaden the present study's analysis.

BackgroundAdvanced dementia represents a challenge marked by significant cognitive deterioration that impacts an individual's ability to recognize family, communicate effectively, and maintain independence. In this context, it's essential to identify the unresolved needs of the caregiver to optimize functionality and care and improve the quality of life for both the patient and the caregiver.MethodA cross‐sectional study was conducted with 30 caregivers of patients with advanced dementia who attended the Cognitive Aging and Dementia clinic at the National Institute of Neurology and Neurosurgery, between February and April 2024. Participants completed a sociodemographic questionnaire and a care needs assessment questionnaire, in addition to some questions specifically developed for this population by the research team.ResultWe obtained 30 responses from primary caregivers of patients with advanced dementia, mostly women and children (80% and 60%, respectively). Regarding the characteristics of patients with advanced dementia, the majority were female (60%) and over 80 years old (40%). When analyzing caregivers' needs based on the patient's sex, a slight significance was observed in the incorrect administration of medications (10%, p = 0.054) and in the need for information on managing behavioral changes (36.7%, p = 0.008). In relation to the patient's age, a statistically significant association was found between caregiver needs, particularly in managing behavioral changes in patients aged 71‐80 years (75%, p = 0.017), as well as the need for information on how to perform activities of daily living (87.5%, p = 0.057). Regarding the relationship between caregiver needs and behavioral problems, these needs were more frequent among female caregivers (45.8%), with a significant result (p = 0.046). Concerning primary caregivers' needs related to behavioral changes and assistance with activities of daily living, no significance was found. However, the need for information about end‐of‐life care showed a significant result (p = 0.001), with 100% of children reporting this need.ConclusionThe implementation of programs that provide specific support for the caregiver's needs is required, particularly regarding the management of behavioral changes, activities of daily living, dementia progression, and end‐of‐life care.

BackgroundGlobal cognitive metrics are useful for tracking cognitive aging, yet there is no consensus on how to best define and measure global cognition. The aim of this study was to compare scoring methods for global cognition against validity indicators.MethodUsing harmonized factor scores of four cognitive domains (memory, executive function, language, visuospatial) in the United States and Korea (Table 1), we compared scoring methods for global cognition with validity indicators of cognition, functioning, and structural neuroimaging at baseline. Scoring approaches included combining cognitive domains with mean z‐scoring, congeneric confirmatory factor analysis (CFA; maximum likelihood robust estimation), principal component analysis (PCA), and weighting domains based on the Mini‐Mental Status Examination (MMSEComposite). Correlations (r) were used to compare composites against continuous validity indicators. The Clinical Dementia Rating Scale Sum of Boxes (CDR‐SB) and MMSE were used to measure cognition and functioning. Neuroimaging measures included brain volume relative to cerebrospinal fluid (BV/CSF) and intracranial volume‐normalized measures of brain volume (BV/ICV), ventricular volume (VV), frontal lobe volume (FL), and medial temporal lobe volume (MTL). Receiver operating characteristic (ROC) curves assessed the ability to detect cognitive impairment (CDR‐Global≥0.5).ResultCognitive composites were highly intercorrelated (Figure; r range:0.94,1.00), correlated with CDR‐SB (r range:‐0.72,‐0.65) and MMSE (r range:0.75,0.77), and detected cognitive impairment in the good range (AUCs=0.84‐0.88). Cognitive composites were similarly correlated with neuroimaging metrics, with differences of at most r = 0.02 across comparisons, except for FL, where MMSEComposite had an r 0.04 lower than the others. Composites yielded stronger correlations with most neuroimaging metrics compared to standalone measures except for BV/ICV with CDR‐SB (r = ‐0.27). MTL and VV demonstrated the strongest associations with cognitive composites and other indicators of cognition/functioning.ConclusionRegardless of scoring method, global cognitive composites were similarly related to validity indicators of cognition/functioning and structural neuroimaging in a harmonized sample. MMSEComposite showed the strongest relationships with CDR but was less strongly associated with frontal lobe volume. Composites demonstrated stronger relationships with structural neuroimaging compared to standalone measures. Future work aims to evaluate similarities and differences between cohorts and evaluate relationships longitudinally.

BackgroundDespite evidence for sex differences in cognitive performance and risk of developing Alzheimer's disease and related dementias, few studies have explored sex differences in rates of cognitive decline. Examining rates of decline using longitudinal data can critically further our understanding of healthy versus abnormal cognitive aging; however, these studies are often complicated by practice effects. Smartphone‐based ecological momentary assessments (EMA) may provide a unique opportunity to address this concern by facilitating short‐term intensive measures of cognitive performance, multiple times/day over multiple days in real‐world settings.MethodThe Einstein Aging Study assessed processing speed in diverse community‐dwelling older adults over 6 years using the WAIS‐III Digit Symbol Substitution Test (DSST) and a smartphone‐based EMA Symbol Match (SM) test. DSST was assessed once annually during in‐person clinic visits, and EMA SM was assessed via a burst protocol (i.e., 6 times/day over two weeks), repeated annually. Multi‐level linear mixed effects models were used to evaluate sex differences in age‐related cognitive decline while accounting for practice effects from exposure to repeat testing. Models were adjusted for covariates including age at baseline, years of education, and race/ethnicity.ResultAmong 322 non‐demented older adults (77.6±5.0 years; 67.1% Female; 46.3% non‐Hispanic White, 40.1% non‐Hispanic Black), up to 6 annual bursts of EMA (mean 3.2±1.7) were obtained during a mean of 2.8±1.9 years of follow‐up. Consistent with prior literature, women performed better at baseline on both DSST number completed correctly within a set time (Table 2) and EMA SM response time (Table 3) measures. There were significant rates of decline among men in DSST and EMA SM during follow‐up. For EMA SM median completion time, mean performance at baseline was not significantly different between men and women; although, women showed faster decline during follow‐up (difference 216±88 milliseconds/year, p = 0.014) and slower improvement from burst assessment exposure (p = 0.002).ConclusionWe observed significantly faster decline in processing speed among women compared with men for EMA‐based but not a conventional, paper‐and‐pencil test. After accounting for practice effects, smartphone‐based digital EMA may be more sensitive to cognitive change and offer novel opportunities to identify possible sex differences at early disease stages.

BackgroundMild cognitive impairment (MCI) is a transitional state between normal cognitive aging and dementia and presents clinical challenges due to its heterogeneous causes and variable progression. Accurate early diagnosis and subtype classification of MCI are critical for guiding emerging targeted treatments and supporting patients and their families.MethodThis six‐year observational study examined cases of cognitive impairment referred to the regional tertiary memory clinic at Queen's Medical Centre, Nottingham, primarily the Young‐Onset Dementia Clinic. The study, conducted from December 2018 to November 2024, included referrals from Nottinghamshire, Leicestershire, Lincolnshire, and Derbyshire. Data were collected as part of the Cognition and NeuroImaging in Neurodegenerative Disorders (CogNID, IRAS 250525, NCT03861884) study and encompassed demographic, clinical, cognitive, cerebrospinal fluid (CSF) biomarker, and neuroimaging data.ResultOver six years, 630 individuals were seen at the neurology‐led clinics, and 429 (68.10%) took part in the study. The mean age of participants was 60.08 years, with 71.10% below 65 yr, 54.55% male, and 63.86% Caucasian. The average Addenbrooke's Cognitive Examination (ACE‐III) score was 70.29, with domain sub scores indicating deficits in Attention (13.91/18), Memory (15.05/26), Fluency (7.58/14), Language (21.62/26), and Visuospatial skills (12.45/16). Brain MRI was the most common mode of investigations. Each individual had 1.2 MRI scans and 0.421 FDG‐PET scans on average. CSF analysis was performed in 31.00% of participants. Alzheimer's disease (AD) was the most common diagnosis (n = 107, 24.94%). Other significant diagnoses included functional cognitive decline with non‐Alzheimer's pathology (12.59%), frontotemporal dementia (6.99%), COVID‐related cognitive impairment (6.06%), vascular cognitive impairment (4.20%) and dementia with Lewy bodies (2.78%) along with various neurodegenerative, vascular, autoimmune, infectious, metabolic, psychiatric, and movement disorders. 12.82% of participants were considered to have a mixed pathology, while the most common co‐pathology was AD and FTD. Over 6 years of this prospective longitudinal study, mortality rate was 5.13%, with 1.86% of participants transitioning to care homes.ConclusionThis observational and longitudinal study provides valuable insights into heterogeneous aetiology of MCI including co‐pathologies from real‐world Young‐Onset Dementia Memory Clinics.

BackgroundThe SPARE‐AD (Spatial Pattern of Abnormalities for Recognition of Early Alzheimer's Disease [AD]) index effectively captures the level of AD‐association patterns of brain atrophy present in elderly individuals. APOE ε4, the strongest genetic risk factor for AD, demonstrates sex‐dependent effects with greater risk in females compared to males. Given SPARE‐AD's sensitivity to AD‐related brain changes, we investigated whether APOE‐ε4 carrier status influences brain atrophy patterns measured by SPARE‐AD and if these effects are modified by sex.MethodThis study included 3,289 non‐Hispanic White participants (mean SPARE‐AD=‐0.79; mean age=72.3; 55.2% cognitive normal; 33.1% MCI; 11.1% AD; 54.1% female) from 4 AD and cognitive aging cohorts (ADNI, NACC, ROS/MAP, WRAP). The SPARE‐AD index was calculated using a high‐dimensional, non‐linear pattern classification method with positive values indicating AD‐like brain atrophy and negative values indicating normal brain structure. In cross‐sectional analyses at baseline, we evaluated the dominant effects of APOE‐ε4 carrier status on SPARE‐AD using multiple linear regression, adjusting for age, sex, and education levels. Sex‐stratified analyses were conducted to examine effect modification. In longitudinal analyses, we applied linear mixed‐effects models with time (years from baseline) and the intercept as fixed and random effects. We first evaluate the longitudinal progression of SPARE‐AD among cognitively unimpaired participants versus participants with MCI at baseline. We then assessed the effects of APOE‐ε4 carrier status on SPARE‐AD progression rates and their modification by sex. All analyses were meta‐analyzed across cohorts.ResultAPOE‐ε4 carriers showed significantly higher SPARE‐AD indices at baseline versus non‐carriers (β=0.34; SE=0.16; p = 0.029), with this effect being significant only among females (β‐females=0.37; p‐females=0.0021; Figure 1). The utility of SPARE‐AD as a prodromal biomarker was validated in longitudinal analyses, where cognitively unimpaired individuals demonstrated significantly slower SPARE‐AD progression compared to those with MCI (β=‐0.11; SE=0.04; p = 0.0052). APOE‐ε4 carriers exhibited accelerated SPARE‐AD progression (β=0.05; SE=0.025; p = 0.047; Figure 2), with no sex differences observed.ConclusionOur multi‐cohort study demonstrates that APOE‐ε4 carrier status influences both brain atrophy patterns and their progression. While baseline APOE‐ε4 effects were female‐specific, progression rates were sex‐independent. These findings advance our understanding of sex‐specific genetic influences on AD‐related brain changes.

BackgroundIndividual differences have been observed in the association between neurodegenerative brain changes and rates of cognitive decline. People who experience less rapid decline than expected based on neurodegeneration are described as being cognitively resilient to brain aging. We hypothesized that patterns of cognitive strengths and weaknesses (certain cognitive profiles) can provide a valid phenotype of prospective resilience.MethodParticipants (N = 2432) were from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study (1/2/3/GO). There were three analytic phases: 1) generate an estimate of prospective resilience; 2) use that resilience estimate to develop a baseline cognitive resilience phenotype; 3) validate the phenotype longitudinally. In the first phase, prospective resilience was defined as the discrepancy between rates of future cognitive and brain change (cognitive slope minus brain slope). In the second phase, a bifactor confirmatory factor analysis model defined the cognitive resilience phenotype as a latent variable representing the variance that the observed cognitive test scores shared with the prospective resilience estimate from phase 1. In the third phase, we used regression in a held‐out sample to test the hypothesized interaction between the resilience phenotype and brain volume change when predicting longitudinal cognitive decline (i.e., does the phenotype modify the association between brain atrophy and rate of cognitive decline?).ResultThe cognitive performance indicators that most strongly contributed to the resilience phenotype were Trail Making Test B (loading = .73), animal fluency (loading = .67), and Boston Naming Test (loading = .67; Table 1). The cognitive resilience phenotype moderated the regression of cognitive slope on brain slope in the held‐out sample (B=‐0.043, SE=0.016; Table 2, Figure 1).ConclusionA cross‐sectional estimate of prospective cognitive resilience against brain atrophy can be constructed from the ADNI neuropsychological test battery. This phenotype, which draws heavily upon measures of processing speed/executive functioning, category fluency, verbal naming, and immediate recall, can predict the extent to which future brain atrophy will impact rates of cognitive decline. Examining cognitive phenotypes associated with more resilient cognitive aging may help to understand neural systems that underpin resilience, potentially leading to resilience‐promoting interventions and new opportunities to efficiently monitor changes in resilience over time.

BackgroundThe Healthier Black Elders (HBE) program in Flint, MI established to advance health research engagement among Black older adults. Black adults are twice as likely to develop Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD) than their White counterparts. The HBE Community advisory board partnered with local research and aging services stakeholders to ascertain whether Black older adults in Flint, MI identify a need for tailored AD/ADRD educational programming, access to cognitive assessments and research studies on cognitive health.MethodSixty (60) community‐dwelling participants (Mean age 67, 68% women) were recruited from the existing participant research pool of Black of older adults (N = 400, age 55+) overseen by the community advisory board of HBE Flint program. Six focus groups were conducted in a local senior center and facilitated by a trained community outreach specialist and research assistant. Focus groups were audio recorded and transcribed without identifying information. Participants were provided lunch but no incentives. A semi‐structured interview protocol focused on participants’ familiarity with AD/ADRD, stigma and concerns, interest in education, interest in and experience with cognitive assessments and research participation; as well as desired program components. Two study staff uninvolved with data collection conducted multi‐stage qualitative coding using a grounded theory approach; identifying key themes.ResultKey themes revealed a lack of health literacy about cognitive aging and perceptions of social stigma surrounding cognitive impairment. Participants were specifically interested in both resources for caregiving as well as how to prepare themselves for impacts to financial, health, and daily living should they be diagnosed with AD/ADRD. Participants expressed that any community‐focused curriculum should address skills for voicing concerns about cognitive changes to a healthcare provider and among family members. Finally, participants were broadly interested in and open to participating in free AD/ADRD cognitive assessments that provided actionable information; many participants were familiar with aging research and enthusiastic about participating in studies vetted by HBE or other trusted community entities.ConclusionBlack older adults in Flint welcome knowledge, programming, and research engagement on AD/ADRD; stakeholders should work with the community to address cognitive aging needs.

BackgroundCurrent cognitive analysis methods in neurodegenerative disease rely on the use of individual neuropsychological assessments, which can be subject to variation and bias. A potentially more robust way to represent cognitive status is to use a cognitive age model to predict an individual's age from their cognitive assessment scores and demographics. This modeling allows for identification of individuals exhibiting resilience or vulnerability to normal aging processes across diverse datasets.MethodPsychometric and demographic data from cognitively unimpaired individuals from NACC UDS 3 (n = 11,752) were obtained. Neuropsychological assessment and demographic data were used to build a random forest model to predict a “cognitive” age. The distributions of predicted cognitive ages for each biological age were used to calculate a percentile rank for individuals in an independent dataset, with higher and lower percentile rank indicating vulnerability (cognitive > chronologic age) and resilience (cognitive < chronologic age), respectively. We assessed this model both with and without self‐identified race (white, black) as a predictor variable and related percentile rank to Area of Deprivation Index (ADI).ResultWe applied the model to cognitively unimpaired individuals in the Penn Aging Brain Cohort (n = 424). The model without race as a predictive feature resulted in a stronger relationship between “cognitive” age centile rank and ADI, suggesting that covarying for race may partially mask the effects of ADI. Removing race from the model also resulted in higher percentile ranks for Black participants, indicating a higher level of vulnerability in these individuals. Percentile rank can also be used to place individuals into resilient, normal, and vulnerable groups to understand what factors contribute to resilience and vulnerability. Preliminary analyses of structural MRI data comparing resilient and vulnerable groups yielded moderately higher thickness in the anterior cingulate cortex and medial frontal cortex of resilient individuals, necessitating further research in a larger population.ConclusionThis machine learning model is a valuable tool for analyzing cognition and identifying abnormal aging patterns in large‐scale datasets, including identification of vulnerable and resilient individuals. Understanding the influence of demographic variables in generating these predictions allows us to better understand their role in vulnerable and resilient aging.

BackgroundAssociative memory is a pivotal component of social cognition. The loss of this ability, frequently reported in the initial stages of Alzheimer's Disease (AD), is among the earliest indications of cognitive impairment. Recent studies have demonstrated that brain oscillations in the gamma band (γ, 30‐120 Hz) play a pivotal role in higher‐order cognitive functions, including multisensory integration (Senkowski et al., 2009) and memory consolidation (Fernandez‐Ruiz et al., 2021). This study aims to establish whether resting‐state EEG (rsEEG) spectral power can serve as a predictive biomarker of associative memory ability, possibly identifying early signs of memory challenges that may also be observed in AD patients.MethodForty‐eight healthy adults underwent rsEEG recording, followed by a face‐name association task (FNAT; Manippa et al., 2025), assessing immediate (IR) and delayed recall (DR).ResultResults showed that endogenous slow‐gamma (s‐γ, 30–49 Hz) power significantly predicted DR, accounting for 22% of the variance (p = 0.024). Increased s‐γ power in temporal regions was positively associated with memory performance (p = 0.038). Fast‐gamma (f‐γ, 51–100 Hz) power significantly predicted DR, accounting for 27% of the variance (p = 0.006), with increased frontal (p = 0.045) and reduced posterior (p <0.001) f‐γ power predicting better performance. Lastly, a trend was observed where increased temporal f‐γ power and reduced posterior f‐γ power were associated with better IR performance.ConclusionThe correlation between increased temporal s‐γ and improved accuracy confirms temporal lobe involvement in the consolidation and retrieval of associative memories (Mayes et al., 2007), consistent with reports of reduced gamma power in the medial temporal lobe in AD patients (Babiloni et al., 2020). Moreover, increased frontal f‐γ activity suggests greater reliance on executive control processes, typically located in the prefrontal cortex, facilitating retrieval (Wang et al., 2018). Reduced posterior f‐γ activity may indicate a shift from sensory integration to higher‐order cognitive processing, with disruptions potentially reflecting imbalanced network dynamics, as observed in AD (Verret et al., 2012). These findings offer novel insights into the neurophysiological mechanisms underlying associative memory, possibly facilitating monitoring and prevention of cognitive decline in populations at risk for AD.