Intra-Individual Variability from a Lifespan Perspective: A Comparison of Latency and Accuracy Measures

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.

Intra-individual variability in task performance after cognitive training is associated with long-term outcomes in children

The potential benefits and mechanistic effects of working memory training (WMT) in children are the subject of much research and debate. We show that after five weeks of school-based, adaptive WMT 6-9 year-old primary school children had greater activity in prefrontal and striatal brain regions, higher task accuracy, and reduced intra-individual variability in response times compared to controls. Using a sequential sampling decision model, we demonstrate that this reduction in intra-individual variability can be explained by changes to the evidence accumulation rates and thresholds. Critically, intra-individual variability is useful in quantifying the immediate impact of cognitive training interventions, being a better predictor of academic skills and well-being 6-12 months after the end of training than task accuracy. Taken together, our results suggest that attention control is the initial mechanism that leads to the long-run benefits from adaptive WMT. Selective and sustained attention abilities may serve as a scaffold for subsequent changes in higher cognitive processes, academic skills, and general well-being. Furthermore, these results highlight that the selection of outcome measures and the timing of the assessments play a crucial role in detecting training efficacy. Thus, evaluating intra-individual variability, during or directly after training could allow for the early tailoring of training interventions in terms of duration or content to maximise their impact.

Cognitive Resources in Working Memory: Domain-Specific or General?

An experiment in the dual-task paradigm was carried out to explore the nature of domain-specific and domain-general resource distribution in working memory. The subjects (N = 32) performed symmetry span and letter reading span tasks under visuospatial (tapping) and verbal (articulatory suppression) cognitive load. The effects of task type and cognitive load modality were analyzed. The results are described within the concentric model framework: significant distinctions in relative accuracy under visuospatial and verbal cognitive load in visuospatial and verbal tasks were observed when N elements in the set exceeded the region of direct access capacity, while no such effect was observed for 2-3 element sets. This is attributed to domain-general resources in the region of direct access, and domain-specific resources in the activated long-term memory. We also found evidence for the asymmetric distribution of visuospatial and verbal working memory resources in that the verbal component is more susceptible to cognitive load.

Spelling out some unaddressed conceptual and methodological challenges in empirical lifespan research

The importance of taking a lifespan approach to describe and understand human development has long been acknowledged (e.g., Baltes, 1987). Nevertheless, theoretical or empirical research that actually encompasses the entire lifespan, that is, from early childhood to old age, is rare. This is not surprising given the challenges such an approach entails. Many of these challenges (e.g., establishing measurement invariance between age groups) have been addressed in the previous literature, but others have not yet been sufficiently considered. The main purpose of this article is to present several examples of such largely unaddressed conceptual and methodological challenges and reflect upon possible ways to address them. We discuss the usefulness of a lifespan approach and the generalization of the challenges to other research comparing different groups, such as gender, culture, or species.

Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI

The relationship between age-related changes in brain structural connectivity (SC) and functional connectivity (FC) with cognition is not well understood. Furthermore, it is not clear whether cognition is represented via a similar spatial pattern of FC and SC or instead is mapped by distinct sets of distributed connectivity patterns. To this end, we used a longitudinal, within-subject, multimodal approach aiming to combine brain data from diffusion-weighted MRI (DW-MRI), and functional MRI (fMRI) with behavioral evaluation, to better understand how changes in FC and SC correlate with changes in cognition in a sample of older adults. FC and SC measures were derived from the multimodal scans acquired at two time points. Change in FC and SC was correlated with 13 behavioral measures of cognitive function using Partial Least Squares Correlation (PLSC). Two of the measures indicate an age-related change in cognition and the rest indicate baseline cognitive performance. FC and SC—cognition correlations were expressed across several cognitive measures, and numerous structural and functional cortical connections, mainly cingulo-opercular, dorsolateral prefrontal, somatosensory and motor, and temporo-parieto-occipital, contributed both positively and negatively to the brain-behavior relationship. Whole-brain FC and SC captured distinct and independent connections related to the cognitive measures. Overall, we examined age-related function-structure associations of the brain in a comprehensive and integrated manner, using a multimodal approach. We pointed out the behavioral relevance of age-related changes in FC and SC. Taken together, our results highlight that the heterogeneity in distributed FC and SC connectivity patterns provide unique information about the variable nature of healthy cognitive aging.

Patterns of Movement Performance and Consistency From Childhood to Old Age

It is widely accepted that the general process of aging can be reflected by changes in motor function. Typically, optimal performance of a given motor task is observed for healthy young adults with declines being observed for individuals at either end of the lifespan. This study was designed to examine differences in the average and variability (i.e., intraindividual variability) of chewing, simple reaction time, postural control, and walking responses. For this study, 15 healthy children, 15 young adults, and 15 older adults participated. Our results indicated the movement performance for the reaction time and postural sway followed a U shape with young adults having faster reaction times and decreased postural sway compared to the children and older adults. However, this pattern was not preserved across all motor tasks with no age differences emerging for (normalized) gait speed, while chewing rates followed a U-shaped curve with older adults and children chewing at faster rates. Taken together, these findings would indicate that the descriptive changes in motor function with aging are heavily influenced by the nature of the task being performed and are unlikely to follow a singular pattern.

Intra-Individual Variability in Cognitive Performance Can Befuddle the Study of Cognitive Impairments and Decline

Using group-aggregated results and snapshot assessments of cognitive performance may prove problematic if the assessed construct shows substantial and rapid variation over time. To illustrate the significance of this issue, we analyzed cognitive performance data of ten older adults undergoing daily computerized cognitive assessments (CogState Brief Battery) for 36–93 days. In all cases, the day-to-day intra-individual variability was substantial when compared with group-level, between-person variability. This indicates that the results of studies using single snapshot assessments of cognitive functioning should be interpreted with caution. Additionally, group-aggregated measures of cognitive performance may not directly extrapolate to an individual.

Between-person and within-person associations of sleep and working-memory in the everyday lives of old and very old adults: initial level, learning, and variability

STUDY OBJECTIVES

Sleep duration affects various aspects of cognitive performance, such as working-memory and learning, among children and adults. However, it remains open, whether similar or even stronger associations exist in old and very old age when changes in sleep and cognitive decrements are common.

METHODS

Using repeated daily-life assessments from a sample of 121 young-old (66-69 years old) and 39 old-old adults (84-90 years old), we assessed links between sleep duration and different aspects of working-memory (initial level, practice-related learning, and residualized variability) between and within persons. Participants reported their sleep durations every morning and performed a numerical working-memory updating task six times a day for seven consecutive days.

RESULTS

Both people who slept longer and those who slept shorter than the sample average showed lower initial performance levels, but a stronger increase of WM over time (i.e. larger learning effects), relative to people with average sleep. Sleep duration did not predict performance variability. Within-person associations were found for people sleeping relatively little on average: For them, working-memory performance was lower on days with shorter than average sleep, yet higher on days with longer than average sleep. Except for lower initial levels of working-memory in old-old adults, no differences between young-old and old-old adults were observed.

CONCLUSION

We conclude that sufficient sleep remains important for working-memory performance in older adults and that it is relevant to include different aspects of working-memory performance, because effects differed for initial performance and learning.

Differential prioritization of intramaze cue and boundary information during spatial navigation across the human lifespan

Spatial learning can be based on intramaze cues and environmental boundaries. These processes are predominantly subserved by striatal- and hippocampal-dependent circuitries, respectively. Maturation and aging processes in these brain regions may affect lifespan differences in their contributions to spatial learning. We independently manipulated an intramaze cue or the environment's boundary in a navigation task in 27 younger children (6-8 years), 30 older children (10-13 years), 29 adolescents (15-17 years), 29 younger adults (20-35 years) and 26 older adults (65-80 years) to investigate lifespan age differences in the relative prioritization of either information. Whereas learning based on an intramaze cue showed earlier maturation during the progression from younger to later childhood and remained relatively stable across adulthood, maturation of boundary-based learning was more protracted towards peri-adolescence and showed strong aging-related decline. Furthermore, individual differences in prioritizing intramaze cue- over computationally more demanding boundary-based learning was positively associated with cognitive processing fluctuations and this association was partially mediated by spatial working memory capacity during adult, but not during child development. This evidence reveals different age gradients of two modes of spatial learning across the lifespan, which seem further influenced by individual differences in cognitive processing fluctuations and working memory, particularly during aging.

Beneath the surface: Unearthing within-person variability and mean relations with Bayesian mixed models

Mixed-effects models are becoming common in psychological science. Although they have many desirable features, there is still untapped potential. It is customary to view homogeneous variance as an assumption to satisfy. We argue to move beyond that perspective, and to view modeling within-person variance as an opportunity to gain a richer understanding of psychological processes. The technique to do so is based on the mixed-effects location scale model that can simultaneously estimate mixed-effects submodels to both the mean (location) and within-person variance (scale). We develop a framework that goes beyond assessing the submodels in isolation of one another and introduce a novel Bayesian hypothesis test for mean-variance correlations in the distribution of random effects. We first present a motivating example, which makes clear how the model can characterize mean-variance relations. We then apply the method to reaction times (RTs) gathered from 2 cognitive inhibition tasks. We find there are more individual differences in the within-person variance than the mean structure, as well as a complex web of structural mean-variance relations. This stands in contrast to the dominant view of within-person variance (i.e., "noise"). The results also point toward paradoxical within-person, as opposed to between-person, effects: several people had slower and less variable incongruent responses. This contradicts the typical pattern, wherein larger means tend to be associated with more variability. We conclude with future directions, spanning from methodological to theoretical inquires, that can be answered with the presented methodology. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Test-retest reliability of Picture My Participation in children with intellectual disability in South Africa

BACKGROUND

Picture My Participation (PmP) is a promising instrument for measuring the participation in everyday situations of children with intellectual disability (ID), particularly in low- and middle-income countries.

AIM

To explore test-retest reliability of PmP by comparing two repeated measurements of children with ID in an urban context in South Africa.

METHODS

A picture-supported interview with 31 children with ID, aged 7-17 years, was conducted twice, two weeks apart. The children rated their participation, operationalised as attendance and involvement, in 20 everyday activities. Analyses were completed for total scores, for the four subcomponents and at item level.

RESULTS

Test-retest agreement at an item level for both attendance and involvement showed slight/fair agreement for most activities (Kappa = 0.01-0.40), and moderate agreement for some activities (Kappa = 0.41-0.60). Moderate agreement was shown for the total scale and at component level (ICC = 0.5-0.75), except for (firstly) attendance of and involvement in 'Family Activities' (ICC = 0.26 for attendance, 0.33 for involvement), and (secondly) involvement in 'Personal Activities' (ICC = 0.33).

CONCLUSION

The result indicates that PmP can reliably be used at component level and as a screening tool for intervention planning to identify participation and participation restrictions in children with ID.

Distinct and similar patterns of emotional development in adolescents and young adults

Adolescence is a developmental period of increased sensitivity to social emotional cues, but it is less known whether young adults demonstrate similar social emotional sensitivity. The current study tested variation in reaction times to emotional face cues during different phases of emotional development. Ex‐Gaussian parameters mu, sigma, and tau were computed, in addition to mean, median and standard deviation (SD) in reaction times (RT) during an emotional go/nogo‐paradigm with fearful, happy, and calm facial expressions in 377 participants, 6–30 years of age. Across development, mean RT showed slowing to fearful facial expressions relative to both calm and happy facial cues, but mu revealed that this pattern was specific to adolescence. In young adulthood, increased variability to fearful expressions relative to both happy and calm ones was captured by SD and tau. The findings that adolescents had longer response latencies to fearful faces, whereas young adults demonstrated greater response variability to fearful faces, together reflect how social emotional processing continues to evolve from adolescence into early adulthood. The findings suggest that young adulthood is also a vulnerable period for processing social emotional cues that ultimately may be important to better understand why different psychopathologies emerge in early adulthood.

A Bayesian nonlinear mixed-effects location scale model for learning

We present a Bayesian nonlinear mixed-effects location scale model (NL-MELSM). The NL-MELSM allows for fitting nonlinear functions to the location, or individual means, and the scale, or within-person variance. Specifically, in the context of learning, this model allows the within-person variance to follow a nonlinear trajectory, where it can be determined whether variability reduces during learning. It incorporates a sub-model that can predict nonlinear parameters for both the location and scale. This specification estimates random effects for all nonlinear location and scale parameters that are drawn from a common multivariate distribution. This allows estimation of covariances among the random effects, within and across the location and the scale. These covariances offer new insights into the interplay between individual mean structures and intra-individual variability in nonlinear parameters. We take a fully Bayesian approach, not only for ease of estimation but also for inference because it provides the necessary and consistent information for use in psychological applications, such as model selection and hypothesis testing. To illustrate the model, we use data from 333 individuals, consisting of three age groups, who participated in five learning trials that assessed verbal memory. In an exploratory context, we demonstrate that fitting a nonlinear function to the within-person variance, and allowing for individual variation therein, improves predictive accuracy compared to customary modeling techniques (e.g., assuming constant variance). We conclude by discussing the usefulness, limitations, and future directions of the NL-MELSM.

Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes

The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or "BOLDSD," is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan.

Individual Differences in Developmental Change: Quantifying the Amplitude and Heterogeneity in Cognitive Change across Old Age

It is well known that cognitive decline in older adults is of smaller amplitude in longitudinal than in cross-sectional studies. Yet, the measure of interest rests generally with aggregated group data. A focus on individual developmental trajectories is rare, mainly because it is difficult to assess intraindividual change reliably. Individual differences in developmental trajectories may differ quantitatively (e.g., larger or smaller decline) or qualitatively (e.g., decline vs improvement), as well as in the degree of heterogeneity of change across different cognitive domains or different tasks. The present paper aims at exploring, within the Geneva Variability Study, individual change across several cognitive domains in 92 older adults (aged 59-89 years at baseline) over a maximum of seven years and a half. Two novel, complementary methods were used to explore change in cognitive performance while remaining entirely at the intra-individual level. A bootstrap based confidence interval was estimated, for each participant and for each experimental condition, making it possible to define three patterns: stability, increase or decrease in performance. Within-person ANOVAs were also conducted for each individual on all the tasks. Those two methods allowed quantifying the direction, the amplitude and the heterogeneity of change for each individual. Results show that trajectories differed widely among individuals and that decline is far from being the rule.