Cognitive-Cognitive Dual-task in aging: A cross-sectional online study

Abstract

The prevalence of neurodegenerative disorders, particularly dementia, is on the rise across many countries worldwide. This negative trend calls for improving our understanding of cognitive aging. While motor-cognitive dual-task approaches have already been proven valuable for clinical diagnosis, comparatively less research is available on the application of Cognitive-Cognitive Dual-Tasking (CCDT), across several cognitive domains. Moreover, there is limited understanding about how healthy aging affects performance in such dual-tasks in the general population. CCDT entails engaging individuals in multiple cognitive tasks simultaneously and holds promise for remote e-Health interventions. In this cross-sectional study, our objective was to evaluate the suitability of a newly developed, self-administered, online tool for examining age-related differences in memory performance under dual-tasking. 337 healthy adults aged 50-90 underwent a visual memory test (Memo) under both single and dual-task conditions (attend to auditory letters). Additional measures included questionnaires on subjective memory complaints (MAC-Q), on cognitive reserve (CR), and a cognitive screening (auto-GEMS). As expected, the accuracy of visual memory performance exhibited a negative correlation with age and MAC-Q, and a positive correlation with CR and auto-GEMS scores. Dual-tasking significantly impaired performance, and its detrimental effect decreased with increasing age. Furthermore, the protective effect of cognitive reserve diminished with advancing age. These findings suggest that the commonly observed age-related increase in dual-task costs is not universally applicable across all tasks and cognitive domains. With further refinement, a longitudinal implementation of this approach may assist in identifying individuals with a distinct cognitive trajectory and potentially at a higher risk of developing cognitive decline.

Fig 1. A representative set of trials.

During the encoding phase 15 images were shown for 5 seconds each while a stream of auditory letters was played (each for a duration of 1.6 sec, 45 letters in total). In the single-task condition participants had to ignore the sounds. In the dual-task condition, participants had to press a key each time the letter "X" was presented.

Fig 2. Correlation plot between remote global examination of mental state (auto-GEMS) and cognitive reserve index (CR) score.

Bands represent 95° confidence intervals.

Fig 3. Scatterplot matrix, with jittered bivariate scatter plots below the diagonal and histograms on the diagonal (see Table 5).

Pearson correlation coefficients and linear regression fits with C.I. 95% are reported. The colour gradient, ranging from blue (negative) to red (positive), illustrates the magnitude of correlation. Note the significant negative relationship between auto-GEMS-c and Age and between memory complaints (MAC-Q, increasing with Age) and objective performance both in auto-GEMS-c and in Memo single-task but not with DTC.

Fig 4. Density plots illustrating the age distribution of participants based on the number of Hits and False Alarms (FA) in the auditory Continuous Performance Test (CPT).

Panel A on the left displays the density plot for CPT Hits. The blue curve represents participants with zero Hits, while the red curve represents those with at least one Hit. Panel B on the right showcases the density plot for CPT FA. Here, the blue curve corresponds to participants with no FA, and the red curve represents those with at least one FA.

Fig 5

Left panel, Memo accuracy as a function of Age and Load (single or dual). Right panel, Memo accuracy as a function of CR, and Age. Bands represent 95° confidence intervals.

Fig 6

Memo accuracy as a function of auto-GEMS-c, Load (single or dual), and CR. Bands represent 95° confidence intervals.

Fig 7. Memo accuracy as a function of auto-GEMS-c, Load (single or dual), MAC-Q, and CR.

Bands represent 95° confidence intervals.

Fig 8. CCFI profiles from taxometric analyses of three unique sets of memory indicators, two objective—Memo single-task and DTC, and one subjective MAC-Q.

M = MAMBAC, X = MAXEIG, L = L-MODE, and solid dots = the average CCFI.