Age impairs mnemonic discrimination of objects more than scenes: A web-based, large-scale approach across the lifespan

A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices

Remote monitoring of cognition holds the promise to facilitate case-finding in clinical care and the individual detection of cognitive impairment in clinical and research settings. In the context of Alzheimer's disease, this is particularly relevant for patients who seek medical advice due to memory problems. Here, we develop a remote digital memory composite (RDMC) score from an unsupervised remote cognitive assessment battery focused on episodic memory and long-term recall and assess its construct validity, retest reliability, and diagnostic accuracy when predicting MCI-grade impairment in a memory clinic sample and healthy controls. A total of 199 participants were recruited from three cohorts and included as healthy controls (n = 97), individuals with subjective cognitive decline (n = 59), or patients with mild cognitive impairment (n = 43). Participants performed cognitive assessments in a fully remote and unsupervised setting via a smartphone app. The derived RDMC score is significantly correlated with the PACC5 score across participants and demonstrates good retest reliability. Diagnostic accuracy for discriminating memory impairment from no impairment is high (cross-validated AUC = 0.83, 95% CI [0.66, 0.99]) with a sensitivity of 0.82 and a specificity of 0.72. Thus, unsupervised remote cognitive assessments implemented in the neotiv digital platform show good discrimination between cognitively impaired and unimpaired individuals, further demonstrating that it is feasible to complement the neuropsychological assessment of episodic memory with unsupervised and remote assessments on mobile devices. This contributes to recent efforts to implement remote assessment of episodic memory for case-finding and monitoring in large research studies and clinical care.

Getting LOST: A conceptual framework for supporting and enhancing spatial navigation in aging

Spatial navigation is more difficult and effortful for older than younger individuals, a shift which occurs for a variety of neurological, physical, and cognitive reasons associated with aging. Despite a large body of evidence documenting age-related deficits in spatial navigation, comparatively less research addresses how to facilitate more effective navigation behavior for older adults. Since navigation challenges arise for a variety of reasons in old age, a one-size-fits-all solution is unlikely to work. Here, we introduce a framework for the variety of spatial navigation challenges faced in aging, which we call LOST-Location, Orientation, Spatial mapping, and Transit. The LOST framework builds on evidence from the cognitive neuroscience of spatial navigation, which reveals distinct components underpinning human wayfinding. We evaluate research on navigational aids-devices and depictions-which help people find their way around; and we reflect on how navigation aids solve (or fail to solve) specific wayfinding difficulties faced by older adults. In summary, we emphasize a bespoke approach to improving spatial navigation in aging, which focuses on tailoring navigation solutions to specific navigation challenges. Our hope is that by providing precise support to older navigators, navigation opportunities can facilitate independence and exploration, while minimizing the danger of becoming lost. We conclude by delineating critical knowledge gaps in how to improve older adults' spatial navigation capacities that the novel LOST framework could guide to address. This article is categorized under: Psychology > Development and Aging Neuroscience > Cognition Neuroscience > Behavior.

Executive Function Predicts Older Adults' Lure Discrimination Difficulties on the Mnemonic Similarity Task

OBJECTIVES

Older adults often have difficulty remembering the details of recently encountered objects. We previously found this with the Mnemonic Similarity Task (MST). Surprisingly, the older adults' MST Lure Discrimination Index (LDI) was significantly correlated with visual acuity but not with memory or executive function. Here we ran a replication with new, larger samples of young (N = 45) and older adults (N = 70). We then combined the original and replication older adult samples (N = 108) to critically examine the relative contributions of visual acuity, memory, and executive function composite scores to LDI performance using dominance analysis. This provided, to our knowledge, the first direct statistical comparison of all 3 of these factors and their interactions on LDI.

METHODS

Participants completed the MST and a battery assessing visual acuity, memory, and executive function. We examined age group differences on MST performance in the new (i.e., replication) young and older adult samples and performed multiple regression and dominance analysis on the combined older adult sample.

RESULTS

Consistent with previous findings, the older adults showed significantly poorer LDI but preserved item recognition. LDI was significantly correlated with both memory and executive function but not with visual acuity. In the combined older adult sample, all 3 composites predicted LDI, but dominance analysis indicated that executive function was the most important predictor.

DISCUSSION

Older adults' MST LDI difficulty may be predicted by their executive function and visual acuity. These factors should be considered when interpreting older adults' MST performance.

Memory precision and age differentially predict the use of decision-making strategies across the lifespan

Memory function declines in normal aging, in a relatively continuous fashion following middle-age. The effect of aging on decision-making is less well-understood, with seemingly conflicting results on both the nature and direction of these age effects. One route for clarifying these mixed findings is to understand how age-related differences in memory affect decisions. Recent work has proposed memory sampling as a specific computational role for memory in decision-making, alongside well-studied mechanisms of reinforcement learning (RL). Here, we tested the hypothesis that age-related declines in episodic memory alter memory sampling. Participants (total N = 361; ages 18-77) performed one of two variants of a standard reward-guided decision experiment with additional trial-unique mnemonic content and a separately-administered task for assessing memory precision. When we fit participants' choices with a hybrid computational model implementing both memory-based and RL-driven valuation side-by-side, we found that memory precision tracked the contribution of memory sampling to choice. At the same time, age corresponded to decreasing influence of RL and increasing perseveration. A second experiment confirmed these results and further revealed that memory precision tracked the specificity of memories selected for sampling. Together, these findings suggest that differences in decision-making across the lifespan may be related to memory function, and that interventions which aim to improve the former may benefit from targeting the latter.

Entorhinal-Hippocampal Circuit Integrity Is Related to Mnemonic Discrimination and Amyloid-β Pathology in Older Adults

Mnemonic discrimination, a cognitive process that relies on hippocampal pattern separation, is one of the first memory domains to decline in aging and preclinical Alzheimer's disease. We tested whether functional connectivity (FC) within the entorhinal-hippocampal circuit, measured with high-resolution resting state fMRI, is associated with mnemonic discrimination and amyloid-β (Aβ) pathology in a sample of 64 cognitively normal human older adults (mean age, 71.3 ± 6.4 years; 67% female). FC was measured between entorhinal-hippocampal circuit nodes with known anatomical connectivity, as well as within cortical memory networks. Aβ pathology was measured with 18F-florbetapir-PET, and neurodegeneration was assessed with subregional volume from structural MRI. Participants performed both object and spatial versions of a mnemonic discrimination task outside of the scanner and were classified into low-performing and high-performing groups on each task using a median split. Low object mnemonic discrimination performance was specifically associated with increased FC between anterolateral entorhinal cortex (alEC) and dentate gyrus (DG)/CA3, supporting the importance of this connection to object memory. This hyperconnectivity between alEC and DG/CA3 was related to Aβ pathology and decreased entorhinal cortex volume. In contrast, spatial mnemonic discrimination was not associated with altered FC. Aβ was further associated with dysfunction within hippocampal subfields, particularly with decreased FC between CA1 and subiculum as well as reduced volume in these regions. Our findings suggest that Aβ may indirectly lead to memory impairment through entorhinal-hippocampal circuit dysfunction and neurodegeneration and provide a mechanism for increased vulnerability of object mnemonic discrimination.SIGNIFICANCE STATEMENT Mnemonic discrimination is a critical episodic memory process that is performed in the dentate gyrus (DG) and CA3 subfield of the hippocampus, relying on input from entorhinal cortex. Mnemonic discrimination is particularly vulnerable to decline in older adults; however, the mechanisms behind this vulnerability are still unknown. We demonstrate that object mnemonic discrimination impairment is related to hyperconnectivity between the anterolateral entorhinal cortex and DG/CA3. This hyperconnectivity was associated with amyloid-β pathology and neurodegeneration in entorhinal cortex, suggesting aberrantly increased network activity is a pathological process. Our findings provide a mechanistic explanation of the vulnerability of object compared to spatial mnemonic discrimination in older adults and has translational implications for choice of outcome measures in clinical trials for Alzheimer's disease.

Unsupervised mobile app-based cognitive testing in a population-based study of older adults born 1944

BACKGROUND

Mobile app-based tools have the potential to yield rapid, cost-effective, and sensitive measures for detecting dementia-related cognitive impairment in clinical and research settings. At the same time, there is a substantial need to validate these tools in real-life settings. The primary aim of this study was thus to evaluate the feasibility, validity, and reliability of mobile app-based tasks for assessing cognitive function in a population-based sample of older adults.

METHOD

A total of 172 non-demented (Clinical Dementia Rating 0 and 0.5) older participants (aged 76-77) completed two mobile app-based memory tasks-the Mnemonic Discrimination Task for Objects and Scenes (MDT-OS) and the long-term (24 h) delayed Object-In-Room Recall Task (ORR-LDR). To determine the validity of the tasks for measuring relevant cognitive functions in this population, we assessed relationships with conventional cognitive tests. In addition, psychometric properties, including test-retest reliability, and the participants' self-rated experience with mobile app-based cognitive tasks were assessed.

RESULT

MDT-OS and ORR-LDR were weakly-to-moderately correlated with the Preclinical Alzheimer's Cognitive Composite (PACC5) (r = 0.3-0.44, p < .001) and with several other measures of episodic memory, processing speed, and executive function. Test-retest reliability was poor-to-moderate for one single session but improved to moderate-to-good when using the average of two sessions. We observed no significant floor or ceiling effects nor effects of education or gender on task performance. Contextual factors such as distractions and screen size did not significantly affect task performance. Most participants deemed the tasks interesting, but many rated them as highly challenging. While several participants reported distractions during tasks, most could concentrate well. However, there were difficulties in completing delayed recall tasks on time in this unsupervised and remote setting.

CONCLUSION

Our study proves the feasibility of mobile app-based cognitive assessments in a community sample of older adults, demonstrating its validity in relation to conventional cognitive measures and its reliability for repeated measurements over time. To further strengthen study adherence, future studies should implement additional measures to improve task completion on time.

Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer's disease

OBJECTIVE

Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer's disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants' personal devices in their everyday environments.

METHODS

We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65-97 years) and 22 individuals with very mild dementia (ages 61-88 years). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau positron emission tomography, and structural magnetic resonance imaging studies.

RESULTS

First, ARC tasks were reliable as between-person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants.

CONCLUSIONS

Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.

Feasibility of Digital Memory Assessments in an Unsupervised and Remote Study Setting

Sensitive and frequent digital remote memory assessments via mobile devices hold the promise to facilitate the detection of cognitive impairment and decline. However, in order to be successful at scale, cognitive tests need to be applicable in unsupervised settings and confounding factors need to be understood. This study explored the feasibility of completely unsupervised digital cognitive assessments using three novel memory tasks in a Citizen Science project across Germany. To that end, the study aimed to identify factors associated with stronger participant retention, to examine test-retest reliability and the extent of practice effects, as well as to investigate the influence of uncontrolled settings such as time of day, delay between sessions or screen size on memory performance. A total of 1,407 adults (aged 18–89) participated in the study for up to 12 weeks, completing weekly memory tasks in addition to short questionnaires regarding sleep duration, subjective cognitive complaints as well as cold symptoms. Participation across memory tasks was pseudorandomized such that individuals were assigned to one of three memory paradigms resulting in three otherwise identical sub-studies. One hundred thirty-eight participants contributed to two of the three paradigms. Critically, for each memory task 12 independent parallel test sets were used to minimize effects of repeated testing. First, we observed a mean participant retention time of 44 days, or 4 active test sessions, and 77.5% compliance to the study protocol in an unsupervised setting with no contact between participants and study personnel, payment or feedback. We identified subject-level factors that contributed to higher retention times. Second, we found minor practice effects associated with repeated cognitive testing, and reveal evidence for acceptable-to-good retest reliability of mobile testing. Third, we show that memory performance assessed through repeated digital assessments was strongly associated with age in all paradigms, and individuals with subjectively reported cognitive decline presented lower mnemonic discrimination accuracy compared to non-complaining participants. Finally, we identified design-related factors that need to be incorporated in future studies such as the time delay between test sessions. Our results demonstrate the feasibility of fully unsupervised digital remote memory assessments and identify critical factors to account for in future studies.

Healthy Middle-Aged Adults Have Preserved Mnemonic Discrimination and Integration, While Showing No Detectable Memory Benefits

Declarative memory abilities change across adulthood. Semantic memory and autobiographic episodic knowledge can remain stable or even increase from mid- to late adulthood, while episodic memory abilities decline in later adulthood. Although it is well known that prior knowledge influences new learning, it is unclear whether the experiential growth of knowledge and memory traces across the lifespan may drive favorable adaptations in some basic memory processes. We hypothesized that an increased reliance on memory integration may be an adaptive mechanism to handle increased interference from accumulating memory traces and knowledge across adulthood. In turn, this may confer an improved ability for integration, observable in middle-age, before the onset of major aging-related declines. We further tested whether the hypothesized increase would be associated with previously observed reductions in memory discrimination performance in midlife. Data from a sample of healthy middle-aged (40-50 years, n = 40) and younger adults (20-28 years, n = 41) did not support the hypothesis of improved integration, as assessed by an associative inference paradigm. Instead, age-equivalent performance on both integration and discrimination measures were observed [Bayes factors (BFs)10 = 0.19-0.25], along with expected higher verbal knowledge and slower perceptual speed for middle-aged [(BFs)10 = 8.52-73.52]. The results contribute to an increased understanding of memory processing in midlife, an understudied portion of the lifespan, and suggest that two core episodic memory processes, integration and discrimination, can be maintained in healthy middle-aged adults.

Bayesian modeling of item heterogeneity in dichotomous recognition memory data and prospects for computerized adaptive testing

Most current models of recognition memory fail to separately model item and person heterogeneity which makes it difficult to assess ability at the latent construct level and prevents the administration of adaptive tests. Here we propose to employ a General Condorcet Model for Recognition (GCMR) in order to estimate ability, response bias and item difficulty in dichotomous recognition memory tasks. Using a Bayesian modeling framework and MCMC inference, we perform 3 separate validation studies comparing GCMR to the Rasch model from IRT and the 2-High-Threshold (2HT) recognition model. First, two simulations demonstrate that recovery of GCMR ability estimates with varying sparsity and test difficulty is more robust and that estimates improve from the two other models under common test scenarios. Then, using a real dataset, face validity is confirmed by replicating previous findings of general and domain-specific age effects (Güsten et al. in Cortex 137:138-148, https://doi.org/10.1016/j.cortex.2020.12.017 , 2021). Using cross-validation we show better out-of-sample prediction for the GCMR as compared to Rasch and 2HT model. In addition, we present a hierarchical extension of the model that is able to estimate age- and domain-specific effects directly, without recurring to a two-stage procedure. Finally, an adaptive test using the GCMR is simulated, showing that the test length necessary to obtain reliable ability estimates can be significantly reduced compared to a non-adaptive procedure. The GCMR allows to model trial-by-trial performance and to increase the efficiency and reliability of recognition memory assessments.

Spatial Pattern Separation Testing Differentiates Alzheimer's Disease Biomarker-Positive and Biomarker-Negative Older Adults With Amnestic Mild Cognitive Impairment

Background: The hippocampus, entorhinal cortex (EC), and basal forebrain (BF) are among the earliest regions affected by Alzheimer’s disease (AD) pathology. They play an essential role in spatial pattern separation, a process critical for accurate discrimination between similar locations.

Objective: We examined differences in spatial pattern separation performance between older adults with amnestic mild cognitive impairment (aMCI) with AD versus those with non-Alzheimer’s pathologic change (non-AD) and interrelations between volumes of the hippocampal, EC subregions and BF nuclei projecting to these subregions (medial septal nuclei and vertical limb of the diagonal band of Broca – Ch1-2 nuclei) with respect to performance.

Methods: Hundred and eighteen older adults were recruited from the Czech Brain Aging Study. Participants with AD aMCI (n = 37), non-AD aMCI (n = 26), mild AD dementia (n = 26), and cognitively normal older adults (CN; n = 29) underwent spatial pattern separation testing, cognitive assessment and brain magnetic resonance imaging.

Results: The AD aMCI group had less accurate spatial pattern separation performance than the non-AD aMCI (p = 0.039) and CN (p < 0.001) groups. The AD aMCI and non-AD groups did not differ in other cognitive tests. Decreased BF Ch1-2 volume was indirectly associated with worse performance through reduced hippocampal tail volume and reduced posteromedial EC and hippocampal tail or body volumes operating in serial.

Conclusion: The study demonstrates that spatial pattern separation testing differentiates AD biomarker positive and negative older adults with aMCI and provides evidence that BF Ch1-2 nuclei influence spatial pattern separation through the posteromedial EC and the posterior hippocampus.

Unsupervised mobile cognitive testing for use in preclinical Alzheimer's disease

INTRODUCTION

Unsupervised digital cognitive testing is an appealing means to capture subtle cognitive decline in preclinical Alzheimer's disease (AD). Here, we describe development, feasibility, and validity of the Boston Remote Assessment for Neurocognitive Health (BRANCH) against in-person cognitive testing and amyloid/tau burden.

METHODS

BRANCH is web-based, self-guided, and assesses memory processes vulnerable in AD. Clinically normal participants (n = 234; aged 50-89) completed BRANCH; a subset underwent in-person cognitive testing and positron emission tomography imaging. Mean accuracy across BRANCH tests (Categories, Face-Name-Occupation, Groceries, Signs) was calculated.

RESULTS

BRANCH was feasible to complete on participants' own devices (primarily smartphones). Technical difficulties and invalid/unusable data were infrequent. BRANCH psychometric properties were sound, including good retest reliability. BRANCH was correlated with in-person cognitive testing (r = 0.617, P < .001). Lower BRANCH score was associated with greater amyloid (r = -0.205, P = .007) and entorhinal tau (r = -0.178, P = .026).

DISCUSSION

BRANCH reliably captures meaningful cognitive information remotely, suggesting promise as a digital cognitive marker sensitive early in the AD trajectory.

Current advances in digital cognitive assessment for preclinical Alzheimer's disease

There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost-effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech-adoption increases, and external events (i.e., COVID-19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in-clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study-provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.