Longitudinal changes in response time mean and inconsistency exhibit predictive dissociations for risk of cognitive impairment

Cognitive Speed in Neurodegenerative Disease: Comparing Mean Rate and Inconsistency Within and Across the Alzheimer's and Lewy Body Spectra in the COMPASS-ND Study

Background

Alzheimer's disease (AD) and Lewy body disease (LBD) are characterized by early and gradual worsening perturbations in speeded cognitive responses.

Objective

Using simple and choice reaction time tasks, we compared two indicators of cognitive speed within and across the AD and LBD spectra: mean rate (average reaction time across trials) and inconsistency (within person variability).

Methods

The AD spectrum cohorts included subjective cognitive impairment (SCI, n = 28), mild cognitive impairment (MCI, n = 121), and AD (n = 45) participants. The LBD spectrum included Parkinson's disease (PD, n = 32), mild cognitive impairment in PD (PD-MCI, n = 21), and LBD (n = 18) participants. A cognitively unimpaired (CU, n = 39) cohort served as common benchmark. We conducted multivariate analyses of variance and discrimination analyses.

Results

Within the AD spectrum, the AD cohort was slower and more inconsistent than the CU, SCI, and MCI cohorts. The MCI cohort was slower than the CU cohort. Within the LBD spectrum, the LBD cohort was slower and more inconsistent than the CU, PD, and PD-MCI cohorts. The PD-MCI cohort was slower than the CU and PD cohorts. In cross-spectra (corresponding cohort) comparisons, the LBD cohort was slower and more inconsistent than the AD cohort. The PD-MCI cohort was slower than the MCI cohort. Discrimination analyses clarified the group difference patterns.

Conclusions

For both speed tasks, mean rate and inconsistency demonstrated similar sensitivity to spectra-related comparisons. Both dementia cohorts were slower and more inconsistent than each of their respective non-dementia cohorts.

'With or without you': associations between noteworthy events and cognitive complaints across 100 days

OBJECTIVES

Daily noteworthy events have implications for physical and mental health, but less is known about the role daily events have for self-reported cognition and whether the involvement of close social partners differentiates these associations. The current study examined how daily positive and negative noteworthy events relate to subjective memory and attentional difficulties and whether close social partners moderated associations.

METHOD

We used data from a 100-day microlongitudinal web-based study of 104 older adults (Nobservations=7,051; Mage=63.13 years, SDage=7.81, 88.46% Female). Participants reported on exposure to and valence of noteworthy events, involvement of close social partners, and subjective cognitive complaints at the end of each day.

RESULTS

Logistic multilevel models revealed that days with a negative event were associated with increased odds of forgetting something and trouble concentrating whereas days with positive events were associated with decreased odds of trouble concentrating. Close social partner involvement did not moderate within-person associations.

CONCLUSION

Our results suggest that day-to-day events are correlates of cognitive complaints regardless of close social partner involvement in the events. Research should clarify the role of daily positive and negative events in personalized interventions and determine whether this person-centered approach to self-reported cognitive health helps inform diagnostic practices.

Naturalistic assessment of reaction time variability in older adults at risk for Alzheimer's disease

OBJECTIVE

Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer's disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD.

METHOD

Three hundred and seventy older adults (aged 75.8 +/- 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials.

RESULTS

Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites.

CONCLUSIONS

Attentional fluctuations over 20-40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.

Intraindividual variability measured with dispersion across diagnostic groups in a memory clinic sample

Increased intraindividual variability (IIV) has been linked to outcomes such as cognitive decline and dementia, suggesting IIV might add valuable diagnostic information beyond traditional neuropsychological interpretation. We explored whether a subtype of IIV, dispersion, can provide additional information for dementia diagnosis. In a sample of memory clinic patients, three cognitive status groups were identified: subjective cognitive impairment (SCI; n = 85), amnestic mild cognitive impairment (a-MCI; n = 16), and dementia due to Alzheimer's disease (AD; n = 48). Dispersion was computed as intraindividual standard deviations across multiple neuropsychological measures within three cognitive domains (executive functioning; immediate and delayed memory) and was compared for each diagnostic group using profile analysis. Patients with AD and a-MCI demonstrated less dispersion than patients with SCI in delayed memory. Results support existing theoretic perspectives on cognitive variability and age-related cognitive decline but suggest floor effects underlie suppression of dispersion in amnestic cognitive presentations. Questions remain about the contribution of IIV beyond impressions of impairment versus no impairment in these constrained representations of cognitive domains. Future investigations should investigate variability in SCI groups against controls to examine whether observed dispersion similarities between SCI and a-MCI or AD in immediate memory and executive functioning are meaningful.

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.

Ambulatory Assessment in Concussion Clinical Care and Rehabilitation

Concussion is a mild traumatic brain injury that is characterized by a wide range of physical, emotional, and cognitive symptoms as well as neurocognitive, vestibular, and ocular impairments that can negatively affect daily functioning and quality of life. Clinical consensus statements recommend a targeted, clinical profile-based approach for management and treatment. This approach requires that clinicians utilize information obtained via a clinical interview and a multi-domain assessment battery to identify clinical profile(s) (e.g., vestibular, mood/anxiety, ocular, migraine, cognitive fatigue) and prescribe a corresponding treatment/rehabilitation program. Despite this comprehensive approach, the clinical picture can be limited by the accuracy and specificity of patient reports (which often conflate timing and severity of symptomology), as well as frequency and duration of exposure to symptom exacerbating environments (e.g., busy hallways, sitting in the back seat of a car). Given that modern rehabilitation programs leverage the natural environment as a tool to promote recovery (e.g., expose-recover approach), accurate characterization of the patient clinical profile is essential to improving recovery outcomes. Ambulatory assessment methodology could greatly benefit concussion clinical care by providing a window into the symptoms and impairments experienced by patients over the course of their daily lives. Moreover, by evaluating the timing, onset, and severity of symptoms and impairments in response to changes in a patient's natural environment, ambulatory assessments can provide clinicians with a tool to confirm clinical profiles and gauge effectiveness of the rehabilitation program. In this perspective report, we review the motivations for utilizing ambulatory assessment methodology in concussion clinical care and report on data from a pilot project utilizing smart phone-based, ambulatory assessments to capture patient reports of symptom severity, environmental exposures, and performance-based assessments of cognition for 7 days following their initial evaluation.

Parameterizing Practice in a Longitudinal Measurement Burst Design to Dissociate Retest Effects From Developmental Change: Implications for Aging Neuroscience

Background: In longitudinal designs, the extraneous influence of retest effects can confound and obscure estimates of developmental change. The current study provides a novel approach to independently parameterize short-term retest effects and long-term developmental change estimates by leveraging a measurement burst design and three-level multilevel modeling. We further employ these short- and long-term slopes as predictors of cognitive status at long-term follow-up assessments.

Methods: Participants included 304 older adults from Project MIND: a longitudinal measurement burst study assessing cognitive performance across both biweekly sessions and annual retests. Participants were classified as either Healthy controls (HC) or Cognitively Impaired, not Demented (CIND) at baseline, the final burst assessment (Year 4), and at an additional four-year follow-up (Year 8). Response time inconsistencies (RTI) were computed at each burst occasion for a simple choice response time (CRT) task and a one-back response time (BRT) task. Three-level multilevel models were employed to simultaneously examine change in RTI for both CRT and BRT across weeks within years, as well as across years, in order to dissociate within-individual retest effects (short-term) from developmental (long-term) change slopes. Individual slopes were then extracted and utilized in a series of multinomial logistic regression equations to contrast short- vs. long-term RTI change as predictors of cognitive status.

Results: Separately parameterizing short- and long-term change estimates yielded distinct patterns of variation. CRT RTI remained stable across short-term weekly assessments, while significantly increasing across years. In contrast, BRT RTI decreased significantly across short-term assessments but showed no change across long-term assessments. After dissociating change estimates, short-term BRT as well as long-term CRT and BRT estimates predicted cognitive status at long-term follow-ups; increases in RTI, suggesting either an inability to benefit from retest or process-based developmental decline, were associated with an increased likelihood of being classified as CIND.

Conclusions: We showcase an innovative approach to dissociate retest effects from developmental change across and within individuals. Accurately parameterizing these distinct change estimates can both reduce systematic bias in longitudinal trend estimates as well as provide a clinically useful tool by utilizing retest effects to predict cognitive health and impairment.

Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study

Background and Objective: Within-person variability in cognitive performance has emerged as a promising indicator of cognitive health with potential to distinguish normative and pathological cognitive aging. We use a smartphone-based digital health approach with ecological momentary assessments (EMA) to examine differences in variability in performance among older adults with mild cognitive impairment (MCI) and those who were cognitively unimpaired (CU). Method: A sample of 311 systematically recruited, community-dwelling older adults from the Einstein Aging Study (Mean age = 77.46 years, SD = 4.86, Range = 70-90; 67% Female; 45% Non-Hispanic White, 40% Non-Hispanic Black) completed neuropsychological testing, neurological assessments, and self-reported questionnaires. One hundred individuals met Jak/Bondi criteria for MCI. All participants performed mobile cognitive tests of processing speed, visual short-term memory binding, and spatial working memory on a smartphone device up to six times daily for 16 days, yielding up to 96 assessments per person. We employed heterogeneous variance multilevel models using log-linear prediction of residual variance to simultaneously assess cognitive status differences in mean performance, within-day variability, and day-to-day variability. We further tested whether these differences were robust to the influence of environmental contexts under which assessments were performed. Results: Individuals with MCI exhibited greater within-day variability than those who were CU on ambulatory assessments that measure processing speed (p < 0.001) and visual short-term memory binding (p < 0.001) performance but not spatial working memory. Cognitive status differences in day-to-day variability were present only for the measure of processing speed. Associations between cognitive status and within-day variability in performance were robust to adjustment for sociodemographic and contextual variables. Conclusion: Our smartphone-based digital health approach facilitates the ambulatory assessment of cognitive performance in older adults and the capacity to differentiate individuals with MCI from those who were CU. Results suggest variability in mobile cognitive performance is sensitive to MCI and exhibits dissociative patterns by timescale and cognitive domain. Variability in processing speed and visual short-term memory binding performance may provide specific detection of MCI. The 16-day smartphone-based EMA measurement burst offers novel opportunity to leverage digital technology to measure performance variability across frequent assessments for studying cognitive health and identifying early clinical manifestations of cognitive impairment.