Within-Individual Variability: An Index for Subtle Change in Neurocognition in Mild Cognitive Impairment

Cognitive dispersion and its functional relevance in behavioral variant frontotemporal dementia and prodromal behavioral variant frontotemporal dementia

OBJECTIVE

Executive dysfunction is characteristic of behavioral variant frontotemporal dementia (bvFTD) but can be challenging to detect. Dispersion-based intraindividual variability (IIV-d) is hypothesized to reflect a sensitive index of executive dysfunction and has demonstrated relevance to functional decline but has not been evaluated in bvFTD.

METHOD

We report on 477 demographically matched participants (159 cognitively healthy [CH], 159 clinical Alzheimer's disease [AD], 159 clinical bvFTD/prodromal bvFTD) who completed the Uniform Data Set 3.0 Neuropsychological Battery. IIV-d was measured using the coefficient of variance (CoV; raw and demographically adjusted) across 12 Uniform Data Set 3.0 Neuropsychological Battery indicators and the informant-rated Functional Activities Questionnaire assessed daily functioning.

RESULTS

Analysis of covariance showed that participants in the bvFTD/prodromal bvFTD group exhibited higher raw and demographically adjusted CoV compared to CH participants, at a very large effect size (d = 1.28-1.47). Demographically adjusted (but not raw) CoV was lower in the bvFTD/prodromal bvFTD group than the AD group, though the effect size was small (d = .38). Both CoV metrics accurately differentiated the bvFTD/prodromal bvFTD and CH groups (areas under the curve = .84), but not bvFTD/prodromal bvFTD and AD groups (areas under the curve = .59). Regression analyses in the bvFTD/prodromal bvFTD group indicated that higher IIV-d on both metrics was associated with greater daily functioning impairment, over and above covariates.

CONCLUSIONS

Compared to healthy adults, individuals with bvFTD/prodromal bvFTD show greater levels of performance variability across a battery of neuropsychological measures, which interferes with everyday functioning. These data demonstrate the clinical utility and ecological validity of IIV-d in bvFTD/prodromal bvFTD, though these findings should be replicated in more diverse samples. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Intraindividual variability in post-stroke cognition and its relationship with activities of daily living and social functioning: an ecological momentary assessment approach

INTRODUCTION

Ecological momentary assessment (EMA) is a methodological approach to studying intraindividual variation over time. This study aimed to use EMA to determine the variability of cognition in individuals with chronic stroke, identify the latent classes of cognitive variability, and examine any differences in daily activities, social functioning, and neuropsychological performance between these latent classes.

METHODS

Participants (N = 202) with mild-to-moderate stroke and over 3-month post-stroke completed a study protocol, including smartphone-based EMA and two lab visits. Participants responded to five EMA surveys daily for 14 days to assess cognition. They completed patient-reported measures and neuropsychological assessments during lab visits. Using latent class analysis, we derived four indicators to quantify cognitive variability and identified latent classes among participants. We used ANOVA and Chi-square to test differences between these latent classes in daily activities, social functioning, and neuropsychological performance.

RESULTS

The latent class analysis converged on a three-class model. The moderate and high variability classes demonstrated significantly greater problems in daily activities and social functioning than the low class. They had significantly higher proportions of participants with problems in daily activities and social functioning than the low class. Neuropsychological performance was not statistically different between the three classes, although a trend approaching statistically significant difference was observed in working memory and executive function domains.

DISCUSSION

EMA could capture intraindividual cognitive variability in stroke survivors. It offers a new approach to understanding the impact and mechanism of post-stroke cognitive problems in daily life and identifying individuals benefiting from self-regulation interventions.

Development and Validity of Norms for Cognitive Dispersion on the Uniform Data Set 3.0 Neuropsychological Battery

OBJECTIVE

Cognitive dispersion indexes intraindividual variability in performance across a battery of neuropsychological tests. Measures of dispersion show promise as markers of cognitive dyscontrol and everyday functioning difficulties; however, they have limited practical applicability due to a lack of normative data. This study aimed to develop and evaluate normed scores for cognitive dispersion among older adults.

METHOD

We analyzed data from 4,283 cognitively normal participants aged ≥50 years from the Uniform Data Set (UDS) 3.0. We describe methods for calculating intraindividual standard deviation (ISD) and coefficient of variation (CoV), as well as associated unadjusted scaled scores and demographically adjusted z-scores. We also examined the ability of ISD and CoV scores to differentiate between cognitively normal individuals (n = 4,283) and those with cognitive impairment due to Lewy body disease (n = 282).

RESULTS

We generated normative tables to map raw ISD and CoV scores onto a normal distribution of scaled scores. Cognitive dispersion indices were associated with age, education, and race/ethnicity but not sex. Regression equations were used to develop a freely accessible Excel calculator for deriving demographically adjusted normed scores for ISD and CoV. All measures of dispersion demonstrated excellent diagnostic utility when evaluated by the area under the curve produced from receiver operating characteristic curves.

CONCLUSIONS

Results of this study provide evidence for the clinical utility of sample-based and demographically adjusted normative standards for cognitive dispersion on the UDS 3.0. These standards can be used to guide interpretation of intraindividual variability among older adults in clinical and research settings.

Examining the Stability and Predictive Utility of Across- and Within-Domain Intra-Individual Variability in Mild Cognitive Impairment

OBJECTIVE

Dispersion is a form of intra-individual variability across neuropsychological tests that has been shown to predict cognitive decline. However, few studies have investigated the stability and predictive utility of both across- and within-domain dispersion. The current study aims to fill these gaps in the literature by examining multiple indices of dispersion in a longitudinal clinical sample of individuals diagnosed with mild cognitive impairment (MCI) at baseline.

METHOD

Two hundred thirty-eight MCI patients from a cognitive disorders clinic underwent testing at baseline and after approximately 1.5 years. Linear regression was used to examine whether baseline across- and within-domain dispersion predicted cognitive decline in individuals whose diagnostic classification progressed to dementia (i.e., MCI-Decline) and those who retained an MCI diagnosis at follow-up (i.e., MCI-Stable). Cognitive decline was operationalized dichotomously using group status and continuously using standardized regression-based (SRB) z-scores.

RESULTS

Dispersion variables at baseline and follow-up were positively correlated in both groups, with the exception of within-domain executive functioning and language dispersion in the MCI-Decline group. None of the dispersion variables predicted diagnostic conversion to MCI. Using SRB z-scores, greater across-domain dispersion predicted greater overall cognitive decline at follow-up, but this was not the case for within-domain variables with the exception of visuospatial skills.

CONCLUSIONS

Results suggest that across- and within-domain dispersion are relatively stable across time, and that across-domain dispersion is predictive of subtle cognitive decline in patients with MCI. However, these results also highlight that findings may differ based on the tests included in dispersion calculations.

Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers

BACKGROUND

Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure.

METHODS

Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference.

RESULTS

For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness.

CONCLUSIONS

We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

Cognitive intraindividual variability, cognitive impairment and psychosocial functioning in first-episode psychosis patients

Cognitive intraindividual variability (IIV) refers to fluctuations in performance across tasks (i.e. dispersion) or in a single task on multiple occasions (i.e. inconsistency). Little is known about IIV in patients with first-episode psychosis (FEP). We aimed to explore the association between IIV and both global cognitive performance and psychosocial functioning in a sample of 103 FEP patients. Patients were recruited at discharge from the PEPsNa program, a FEP follow-up intervention program lasting 24 months. The Social and Occupational Functioning Scale (SOFAS) and the Cognitive Assessment Interview (CAI-Sp) were employed for assessing psychosocial functioning. Cognitive assessments were performed using the MATRICS Cognitive Assessment Battery (MCCB), and the variability in the cognitive functions assessed with the MCCB was used to calculate the IIV. Significant correlations were obtained between IIV and global MCCB scores, the CAI-Sp and the SOFAS. We found significant differences in psychosocial functioning and cognitive performance between patients with high and low IIV. A higher IIV in FEP patients was related both to worse psychosocial functioning and worse global cognitive performance. Unlike global cognitive performance, IIV was not related to clinical characteristics, suggesting that it could be an indicator of cognitive impairment even in the absence of global impairment.

Adherence type impacts completion rates of frequent mobile cognitive assessments among older adults with and without cognitive impairment

Background

Prior to a diagnosis of Alzheimer's disease, many individuals experience cognitive and behavioral fluctuations that are not detected during a single session of traditional neuropsychological assessment. Mobile applications now enable high-frequency cognitive data to be collected remotely, introducing new opportunities and challenges. Emerging evidence suggests cognitively impaired older adults are capable of completing mobile assessments frequently, but no study has observed whether completion rates vary by assessment frequency or adherence type.

Methods

Thirty-three older adults were recruited from the Boston University Alzheimer's Disease Research Center (mean age = 73.5 years; 27.3% cognitively impaired; 57.6% female; 81.8% White, 18.2% Black). Participants remotely downloaded and completed the DANA Brain Vital application on their own mobile devices throughout the study. The study schedule included seventeen assessments to be completed over the course of a year. Specific periods during which assessments were expected to be completed were defined as subsegments, while segments consisted of multiple subsegments. The first segment included three subsegments to be completed within one week, the second segment included weekly subsegments and spanned three weeks, and the third and fourth segments included monthly subsegments spanning five and six months, respectively. Three distinct adherence types - subsegment adherence, segment adherence, and cumulative adherence - were examined to determine how completion rates varied depending on assessment frequency and adherence type.

Results

Adherence type significantly impacted whether the completion rates declined. When utilizing subsegment adherence, the completion rate significantly declined (p = 0.05) during the fourth segment. However, when considering completion rates from the perspective of segment adherence, a decline in completion rate was not observed. Overall adherence rates increased as adherence parameters were broadened from subsegment adherence (60.6%) to segment adherence (78.8%), to cumulative adherence (90.9%).

Conclusions

Older adults, including those with cognitive impairment, are able to complete remote cognitive assessments at a high-frequency, but may not necessarily adhere to prescribed schedules.

Reliability and Validity of Noncognitive Ecological Momentary Assessment Survey Response Times as an Indicator of Cognitive Processing Speed in People's Natural Environment: Intensive Longitudinal Study

BACKGROUND

Various populations with chronic conditions are at risk for decreased cognitive performance, making assessment of their cognition important. Formal mobile cognitive assessments measure cognitive performance with greater ecological validity than traditional laboratory-based testing but add to participant task demands. Given that responding to a survey is considered a cognitively demanding task itself, information that is passively collected as a by-product of ecological momentary assessment (EMA) may be a means through which people's cognitive performance in their natural environment can be estimated when formal ambulatory cognitive assessment is not feasible. We specifically examined whether the item response times (RTs) to EMA questions (eg, mood) can serve as approximations of cognitive processing speed.

OBJECTIVE

This study aims to investigate whether the RTs from noncognitive EMA surveys can serve as approximate indicators of between-person (BP) differences and momentary within-person (WP) variability in cognitive processing speed.

METHODS

Data from a 2-week EMA study investigating the relationships among glucose, emotion, and functioning in adults with type 1 diabetes were analyzed. Validated mobile cognitive tests assessing processing speed (Symbol Search task) and sustained attention (Go-No Go task) were administered together with noncognitive EMA surveys 5 to 6 times per day via smartphones. Multilevel modeling was used to examine the reliability of EMA RTs, their convergent validity with the Symbol Search task, and their divergent validity with the Go-No Go task. Other tests of the validity of EMA RTs included the examination of their associations with age, depression, fatigue, and the time of day.

RESULTS

Overall, in BP analyses, evidence was found supporting the reliability and convergent validity of EMA question RTs from even a single repeatedly administered EMA item as a measure of average processing speed. BP correlations between the Symbol Search task and EMA RTs ranged from 0.43 to 0.58 (P<.001). EMA RTs had significant BP associations with age (P<.001), as expected, but not with depression (P=.20) or average fatigue (P=.18). In WP analyses, the RTs to 16 slider items and all 22 EMA items (including the 16 slider items) had acceptable (>0.70) WP reliability. After correcting for unreliability in multilevel models, EMA RTs from most combinations of items showed moderate WP correlations with the Symbol Search task (ranged from 0.29 to 0.58; P<.001) and demonstrated theoretically expected relationships with momentary fatigue and the time of day. The associations between EMA RTs and the Symbol Search task were greater than those between EMA RTs and the Go-No Go task at both the BP and WP levels, providing evidence of divergent validity.

CONCLUSIONS

Assessing the RTs to EMA items (eg, mood) may be a method of approximating people's average levels of and momentary fluctuations in processing speed without adding tasks beyond the survey questions.

Subtle impairments of perceptual-motor function and well-being are detectable among military cadets and college athletes with self-reported history of concussion

Introduction

A lack of obvious long-term effects of concussion on standard clinical measures of behavioral performance capabilities does not preclude the existence of subtle neural processing impairments that appear to be linked to elevated risk for subsequent concussion occurrence, and which may be associated with greater susceptibility to progressive neurodegenerative processes. The purpose of this observational cohort study was to assess virtual reality motor response variability and survey responses as possible indicators of suboptimal brain function among military cadets and college athletes with self-reported history of concussion (HxC).

Methods

The cohort comprised 75 college students (20.7 ± 2.1 years): 39 Reserve Officer Training Corp (ROTC) military cadets (10 female), 16 football players, and 20 wrestlers; HxC self-reported by 20 (29.2 ± 27.1 months prior, range: 3-96). A virtual reality (VR) test involving 40 lunging/reaching responses to horizontally moving dots (filled/congruent: same direction; open/incongruent: opposite direction) was administered, along with the Sport Fitness and Wellness Index (SFWI) survey. VR Dispersion (standard deviation of 12 T-scores for neck, upper extremity, and lower extremity responses to congruent vs. incongruent stimuli originating from central vs. peripheral locations) and SFWI response patterns were the primary outcomes of interest.

Results

Logistic regression modeling of VR Dispersion (range: 1.5-21.8), SFWI (range: 44-100), and an interaction between them provided 81% HxC classification accuracy (Model χ ²[2] = 26.03, p < .001; Hosmer & Lemeshow χ ²[8] = 1.86, p = .967; Nagelkerke R ²= .427; Area Under Curve = .841, 95% CI: .734, .948). Binary modeling that included VR Dispersion ≥3.2 and SFWI ≤86 demonstrated 75% sensitivity and 86% specificity with both factors positive (Odds Ratio = 17.6, 95% CI: 5.0, 62.1).

Discussion/Conclusion

Detection of subtle indicators of altered brain processes that might otherwise remain unrecognized is clearly important for both short-term and long-term clinical management of concussion. Inconsistency among neck, upper extremity, and lower extremity responses to different types of moving visual stimuli, along with survey responses suggesting suboptimal well-being, merit further investigation as possible clinical indicators of persisting effects of concussion that might prove to be modifiable.

Dispersion-based cognitive intra-individual variability in dementia with Lewy bodies

OBJECTIVE

Cognitive fluctuations are characteristic of dementia with Lewy bodies (DLB) but challenging to measure. Dispersion-based intra-individual variability (IIV-d) captures neurocognitive performance fluctuations across a test battery and may be sensitive to cognitive fluctuations but has not been studied in DLB.

METHOD

We report on 5,976 participants that completed the uniform data set 3.0 neuropsychological battery (UDS3NB). IIV-d was calculated via the intra-individual standard deviation across 12 primary UDS3NB indicators. Separate models using mean USD3NB score and the Montreal cognitive assessment (MoCA) total score tested the reproducibility of the incremental value of IIV-d over-and-above global cognition. Binary logistic regressions tested whether IIV-d could classify individuals with and without clinician-rated cognitive fluctuations. Multinomial logistic regressions tested whether IIV-d could differentiate participants with DLB, participants with Alzheimer's disease (AD), and participants with healthy cognition (CH), as well as the incremental diagnostic utility of IIV-d over-and-above clinician-rated cognitive fluctuations.

RESULTS

IIV-d exhibited large univariate associations with clinician-rated and non-clinician-informant reported cognitive fluctuations, which persisted when adjusting for MoCA but not the full battery mean. Of diagnostic relevance, greater IIV-d was consistently associated with DLB and AD relative to CH over-and-above global cognition and clinician-rated cognitive fluctuations. Greater IIV-d was less consistently associated with an increased probability of DLB relative to AD when controlling for global cognition.

CONCLUSIONS

IIV-d accurately differentiates DLB from CH over-and-above global cognition and clinician-rated cognitive fluctuations. IIV-d may supplement a thorough clinical interview of cognitive fluctuations and serve as a standardized performance-based indicator of this transdiagnostic phenomenon. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Capturing Cognitive Aging in Vivo: Application of a Neuropsychological Framework for Emerging Digital Tools

As the global burden of dementia continues to plague our healthcare systems, efficient, objective, and sensitive tools to detect neurodegenerative disease and capture meaningful changes in everyday cognition are increasingly needed. Emerging digital tools present a promising option to address many drawbacks of current approaches, with contexts of use that include early detection, risk stratification, prognosis, and outcome measurement. However, conceptual models to guide hypotheses and interpretation of results from digital tools are lacking and are needed to sort and organize the large amount of continuous data from a variety of sensors. In this viewpoint, we propose a neuropsychological framework for use alongside a key emerging approach-digital phenotyping. The Variability in Everyday Behavior (VIBE) model is rooted in established trends from the neuropsychology, neurology, rehabilitation psychology, cognitive neuroscience, and computer science literature and links patterns of intraindividual variability, cognitive abilities, and everyday functioning across clinical stages from healthy to dementia. Based on the VIBE model, we present testable hypotheses to guide the design and interpretation of digital phenotyping studies that capture everyday cognition in vivo. We conclude with methodological considerations and future directions regarding the application of the digital phenotyping approach to improve the efficiency, accessibility, accuracy, and ecological validity of cognitive assessment in older adults.

A Novel Approach to Assessment of Perceptual-Motor Efficiency and Training-Induced Improvement in the Performance Capabilities of Elite Athletes

Standard clinical assessments of mild traumatic brain injury are inadequate to detect subtle abnormalities that can be revealed by sophisticated diagnostic technology. An association has been observed between sport-related concussion (SRC) and subsequent musculoskeletal injury, but the underlying neurophysiological mechanism is not currently understood. A cohort of 16 elite athletes (10 male, 6 female), which included nine individuals who reported a history of SRC (5 male, 4 female) that occurred between 4 months and 8 years earlier, volunteered to participate in a 12-session program for assessment and training of perceptual-motor efficiency. Performance metrics derived from single- and dual-task whole-body lateral and diagonal reactive movements to virtual reality targets in left and right directions were analyzed separately and combined in various ways to create composite representations of global function. Intra-individual variability across performance domains demonstrated very good SRC history classification accuracy for the earliest 3-session phase of the program (Reaction Time Dispersion AUC = 0.841; Deceleration Dispersion AUC = 0.810; Reaction Time Discrepancy AUC = 0.825, Deceleration Discrepancy AUC = 0.794). Good earliest phase discrimination was also found for Composite Asymmetry between left and right movement directions (AUC = 0.778) and Excursion Average distance beyond the minimal body displacement necessary for virtual target deactivation (AUC = 0.730). Sensitivity derived from Youden's Index for the 6 global factors ranged from 67 to 89% and an identical specificity value of 86% for all of them. Median values demonstrated substantial improvement from the first 3-session phase to the last 3-session phase for Composite Asymmetry and Excursion Average. The results suggest that a Composite Asymmetry value ≥ 0.15 and an Excursion Average value ≥ 7 m, provide reasonable qualitative approximations for clinical identification of suboptimal perceptual-motor performance. Despite acknowledged study limitations, the findings support a hypothesized relationship between whole-body reactive agility performance and functional connectivity among brain networks subserving sensory perception, cognitive decision-making, and motor execution. A complex systems approach appears to perform better than traditional data analysis methods for detection of subtle perceptual-motor impairment, which has the potential to advance both clinical management of SRC and training for performance enhancement.

Interindividual and intraindividual variability in amnestic mild cognitive impairment (aMCI) measured with an online cognitive assessment

INTRODUCTION

Mean cognitive performance is worse in amnestic mild cognitive impairment (aMCI) compared to control groups. However, studies on variability of cognitive performance in aMCI have yielded inconclusive results, with many differences in variability measures and samples from one study to another.

METHODS

We examined variability in aMCI using an existing older adult sample (n = 91; 51 with aMCI, 40 with normal cognition for age), measured with an online self-administered computerized cognitive assessment (Cogniciti's Brain Health Assessment). Our methodology extended past findings by using pure measures of variability (controlling for confounding effects of group performance or practice), and a clinically representative aMCI sample (reflecting the continuum of cognitive performance between normal cognition and aMCI).

RESULTS

Between-group t-tests showed significantly greater between-person variability (interindividual variability or diversity) in overall cognitive performance in aMCI than controls, although the effect size was with a small to moderate effect size, d = 0.44. No significant group differences were found in within-person variability (intraindividual variability) across cognitive tasks (dispersion) or across trials of a response time task (inconsistency), which may be because we used a sample measuring the continuum of cognitive performance. Exploratory correlation analyses showed that a worse overall score was associated with greater inter- and intraindividual variability, and that variability measures were correlated with each other, indicating people with worse cognitive performance were more variable.

DISCUSSION

The current study demonstrates that self-administered online tests can be used to remotely assess different types of variability in people at risk of Alzheimer`s. Our findings show small but significantly more interindividual differences in people with aMCI. This diversity is considered as "noise" in standard assessments of mean performance, but offers an interesting and cognitively informative "signal" in itself.

Cognitive Dispersion Predicts Grip Strength Trajectories in Men but not Women in a Sample of the Oldest Old Without Dementia

Background and Objectives

Grip strength is a reliable marker of biological vitality and it typically demonstrates an expected decline in older adults. According to the common-cause hypothesis, there is also a significant association between cognitive and physical function in older adults. Some specific cognitive functions have been shown to be associated with grip strength trajectories with most research solely focused on cutoff points or mean cognitive performance. In the present study, we examine whether a measure of cognitive dispersion might be more informative. We therefore used an index that quantifies dispersion in cognitive scores across multiple cognitive tests, shown to be associated with detrimental outcomes in older adults.

Research Design and Methods

Using repeated grip strength measures from men and women aged 80 and older, free of dementia in the OCTO-Twin study, we estimated aging-related grip strength trajectories. We examined the association of cognitive dispersion and mean cognitive function with grip strength level and aging-related rate of change, accounting for known risk factors.

Results

Cognitive dispersion was associated with grip strength trajectories in men and the association varied by mean cognitive performance, whereas we found no association in women.

Discussion and Implications

Our results provide evidence of a sex-specific vitality association between cognitive dispersion and aging-related trajectories of grip strength. Our results support the call for integration of sex and gender in health promotion and intervention research.

Using Mixture Modeling to Construct Subgroups of Cognitive Aging in the Wisconsin Longitudinal Study

OBJECTIVES

Longitudinal surveys of older adults increasingly incorporate assessments of cognitive performance. However, very few studies have used mixture modeling techniques to describe cognitive aging, identifying subgroups of people who display similar patterns of performance across discrete cognitive functions. We employ this approach to advance empirical evidence concerning interindividual variability and intraindividual change in patterns of cognitive aging.

METHOD

We drew upon data from 3,713 participants in the Wisconsin Longitudinal Study (WLS). We used latent class analysis to generate subgroups of cognitive aging based on assessments of verbal fluency and episodic memory at ages 65 and 72. We also employed latent transition analysis to identify how individual participants moved between subgroups over the 7-year period.

RESULTS

There were 4 subgroups at each point in time. Approximately 3 quarters of the sample demonstrated continuity in the qualitative type of profile between ages 65 and 72, with 17.9% of the sample in a profile with sustained overall low performance at both ages 65 and 72. An additional 18.7% of participants made subgroup transitions indicating marked decline in episodic memory.

DISCUSSION

Results demonstrate the utility of using mixture modeling to identify qualitatively and quantitatively distinct subgroups of cognitive aging among older adults. We discuss the implications of these results for the continued use of population health data to advance research on cognitive aging.

The marmoset as an important primate model for longitudinal studies of neurocognitive aging

Age-related cognitive decline has been extensively studied in humans, but the majority of research designs are cross-sectional and compare across younger and older adults. Longitudinal studies are necessary to capture variability in cognitive aging trajectories but are difficult to carry out in humans and long-lived nonhuman primates. Marmosets are an ideal primate model for neurocognitive aging as their naturally short lifespan facilitates longitudinal designs. In a longitudinal study of marmosets tested on reversal learning starting in middle-age, we found that, on average, the group of marmosets declined in cognitive performance around 8 years of age. However, we found highly variable patterns of cognitive aging trajectories across individuals. Preliminary analyses of brain tissues from this cohort also show highly variable degrees of neuropathology. Future work will tie together behavioral trajectories with brain pathology and provide a window into the factors that predict age-related cognitive decline.

Cognitive variability, brain aging, and cognitive decline in late-life major depression

OBJECTIVES

Older adults with late-life major depression (LLMD) are at increased risk of dementia. Dispersion, or within-person performance variability across cognitive tests, is a potential marker of cognitive decline. This study examined group differences in dispersion between LLMD and nondepressed healthy controls (HC) and investigated whether dispersion was a predictor of cognitive performance 1 year later in LLMD. We also explored demographic, clinical, and structural imaging correlates of dispersion in LLMD and HC. We hypothesized that dispersion would be greater in LLMD compared with HC and would be associated with worse cognitive performance 1 year later in LLMD.

DESIGN

Participants were enrolled in the Neurobiology of Late-Life Depression, a naturalistic longitudinal investigation of the predictors of poor illness course in LLMD.

PARTICIPANTS

The baseline sample consisted of 121 older adults with LLMD and 39 HC; of these subjects, 94 LLMD and 35 HC underwent magnetic resonance imaging (MRI). One-year cognitive data were available for 107 LLMD patients.

MEASUREMENTS

All participants underwent detailed clinical and structural MRI at baseline. LLMD participants also completed a comprehensive cognitive evaluation 1 year later.

RESULTS

Higher test dispersion was evident in LLMD when compared with nondepressed controls. Greater baseline dispersion predicted 1-year cognitive decline in LLMD patients even when controlling for baseline cognitive functioning and demographic and clinical confounders. Dispersion was correlated with white matter lesions in LLMD but not HC. Dispersion was also correlated with anxiety in both LLMD and HC.

CONCLUSIONS

Dispersion is a marker of neurocognitive integrity that requires further exploration in LLMD.

Clinical Utility of a Reaction-Time Attention Task in the Evaluation of Cognitive Impairment in Elderly with High Educational Disparity

BACKGROUND

The Clinical Dementia Rating (CDR) scale is commonly used to stage cognitive impairment, despite having educational limitations. In elderly with low education, a previous study has shown that intraindividual variability of reaction time (CV) and commission errors (CE), measured using a culture-free Go/No-Go task, can reliably distinguish early Alzheimer's disease (AD) from mild cognitive impairment (MCI) and healthy controls.

OBJECTIVE

We aimed to extend the clinical utility of this culture-free Go/No-Go task in a sample with high educational disparity.

METHODS

One hundred and ten participants with a wide range of years of formal education (0-14 years) were randomly selected from a geriatric unit and divided based on their CDR scores into cognitively unimpaired (CDR = 0), MCI (CDR = 0.5), and early AD (CDR = 1). All underwent a 90-s reaction-time test that measured the variables previously found to predict CDR in low educated elderly. Here we added years of formal education (educational level) to the model. Multivariate analyses compared differences in group means using educational level as confounding factor. A confirmatory discriminant analyses was performed, to assess if CDR scores could be predicted by the two Go/No-Go variables in a sample with high educational disparity.

RESULTS

Over all three groups, differences in both CE and CV reached statistical significance (p < 0.05). The discriminant analysis demonstrated that CV and CE discriminated cognitively impaired from cognitively normal elderly. These results remained similar when discriminating MCI from cognitively unimpaired elderly.

CONCLUSION

The Go/No-Go task reliably discriminates elderly with MCI from elderly without cognitive impairment independent of educational disparity.

Detection of Cognitive Dysfunction in Elderly with a Low Educational Level Using a Reaction-Time Attention Task

Background: Scales for cognitive deterioration usually depend on education level. Objective: We aimed to study the clinical utility of a culture-free Go/No-Go task in a multi-ethnic cohort with low education level. Methods: Sixty-four participants with less than 4 years of formal education were included and divided on the basis of their Clinical-Dementia-Rate scores (CDR) into cognitively unimpaired (CDR = 0), mild cognitive impairment (MCI; CDR = 0.5), and early Alzheimer’s disease (AD, CDR = 1). All underwent a 90-s Continuous Visual Attention Test. This test consisted of a 90-s Go/No-go task with 72 (80%) targets and 18 (20%) non-targets. For each participant, reaction times and intraindividual variability of reaction times of all correct target responses, as well as the number of omission and commission errors were evaluated. Coefficient of variability was calculated for each participant by dividing the standard deviation of the reaction times by the mean reaction time. A MANCOVA was performed to examine between-group differences using age and sex as covariates. Discriminate analysis was performed to find the most reliable test-variable to discriminate the three groups. Results: Commission error, intraindividual variability of reaction time, and coefficient of variability progressively worsened with increasing CDR level. Discriminant analysis demonstrated that coefficient of variability was the best discriminant factor, followed by intraindividual variability of reaction time and commission error. Conclusion: The Go/No-Go task was able to discriminate people with MCI or early AD from controls in the setting of illiteracy.

Cognitive Dispersion Is Not Associated with Cerebrospinal Fluid Biomarkers of Alzheimer's Disease: Results from the European Prevention of Alzheimer's Dementia (EPAD) v500.0 Cohort

BACKGROUND

Cognitive dispersion, variation in performance across cognitive domains, is posited as a non-invasive and cost-effective marker of early neurodegeneration. Little work has explored associations between cognitive dispersion and Alzheimer's disease (AD) biomarkers in healthy older adults. Even less is known about the influence or interaction of biomarkers reflecting brain pathophysiology or other risk factors on cognitive dispersion scores.

OBJECTIVE

The main aim of this study was to examine whether higher cognitive dispersion was associated with cerebrospinal fluid (CSF) levels of amyloid-β (Aβ42), total tau (t-tau), phosphorylated tau (p-tau), and amyloid positivity in a cohort of older adults at various severities of AD. A secondary aim was to explore which AD risk factors were associated with cognitive dispersion scores.

METHODS

Linear and logistic regression analyses explored the associations between dispersion and CSF levels of Aβ42, t-tau, and p-tau and amyloid positivity (Aβ42 < 1000 pg/ml). Relationships between sociodemographics, APOEɛ4 status, family history of dementia, and levels of depression and dispersion were also assessed.

RESULTS

Dispersion did not emerge as associated with any of the analytes nor amyloid positivity. Older (β= -0.007, SE = 0.002, p = 0.001) and less educated (β= -0.009, SE = 0.003, p = 0.009) individuals showed greater dispersion.

CONCLUSION

Dispersion was not associated with AD pathology, but was associated with age and years of education, highlighting individual differences in cognitive aging. The use of this metric as a screening tool for existing AD pathology is not supported by our analyses. Follow-up work will determine if dispersion scores can predict changes in biomarker levels and/or positivity status longitudinally.

Cognition in Context: Understanding the Everyday Predictors of Cognitive Performance in a New Era of Measurement

Background

Research suggests that variability in attention and working memory scores, as seen across time points, may be a sensitive indicator of impairment compared with a singular score at one point in time. Given that fluctuation in cognitive performance is a meaningful metric of real-world function and trajectory, it is valuable to understand the internal state-based and environmental factors that could be driving these fluctuations in performance.

Objective

In this viewpoint, we argue for the use of repeated mobile assessment as a way to better understand how context shapes moment-to-moment cognitive performance. To elucidate potential factors that give rise to intraindividual variability, we highlight existing literature that has linked both internal and external modifying variables to a number of cognitive domains. We identify ways in which these variables could be measured using mobile assessment to capture them in ecologically meaningful settings (ie, in daily life). Finally, we describe a number of studies that have already begun to use mobile assessment to measure changes in real time cognitive performance in people’s daily environments and the ways in which this burgeoning methodology may continue to advance the field.

Methods

This paper describes selected literature on contextual factors that examined how experimentally induced or self-reported contextual variables (ie, affect, motivation, time of day, environmental noise, physical activity, and social activity) related to tests of cognitive performance. We also selected papers that used mobile assessment of cognition; these papers were chosen for their use of high-frequency time-series measurement of cognition using a mobile device.

Results

Upon review of the relevant literature, it is evident that contextual factors have the potential to meaningfully impact cognitive performance when measured in laboratory and daily life environments. Although this research has shed light on the question of what gives rise to real-life variability in cognitive function (eg, affect and activity), many of the studies were limited by traditional methods of data collection (eg, involving retrospective recall). Furthermore, cognition has often been measured in one domain or in one age group, which does not allow us to extrapolate results to other cognitive domains and across the life span. On the basis of the literature reviewed, mobile assessment of cognition shows high levels of feasibility and validity and could be a useful method for capturing individual cognitive variability in real-world contexts via passive and active measures.

Conclusions

We propose that, through the use of mobile assessment, there is an opportunity to combine multiple sources of contextual and cognitive data. These data have the potential to provide individualized digital signatures that could improve diagnostic precision and lead to meaningful clinical outcomes in a wide range of psychiatric and neurological disorders.

Going beyond the mean: Intraindividual variability of cognitive performance in prodromal and early neurodegenerative disorders

OBJECTIVE

Intraindividual variability (IIV), generally defined as short-term variations in behavior, has been proposed as a sign of subtle early impairment in neurodegenerative disorders, presumably associated with the disintegration of neuronal network connectivity. We aim to provide a review of IIV as a sensitive cognitive marker in prodromal neurodegenerative disorders.

METHOD

A narrative review focusing not only on theoretical and methodological definitions, including an overview on the neural correlates of IIV, but mainly on results from population-based and clinical-based studies on the role of IIV as a reliable predictor of mild cognitive impairment (MCI) and conversion to dementia in neurodegenerative disorders, mostly Alzheimer's and Parkinson's disease.

RESULTS

Most studies focus on MCI and Alzheimer's disease and demonstrate that IIV is a reliable cognitive marker. IIV is partly more sensitive than mean performance in the prediction of cognitive impairment or progressive deterioration and is independent of socio-demographic variables and disease mediators (e.g., genetic susceptibility). Neuroimaging data, mostly from healthy subjects, suggest a relationship between IIV and dysfunction of the default mode network, presumably mediated by white matter disintegration in frontal and parietal areas.

CONCLUSIONS

IIV measures may provide valuable information about diagnosis and progression in prodromal stages of neurodegenerative disorders. Thus, further conceptual and methodological clarifications are needed to justify the inclusion of IIV as a sensible cognitive marker in routine clinical neuropsychological assessment.