Reaction time variability and brain white matter integrity

Effects of an acute bout of cycling on different domains of cognitive function

The literature suggesting acute exercise benefits cognitive function has been largely confined to single cognitive domains and measures of reliant on measures of central tendencies. Furthermore, studies suggest cognitive intra-individual variability (IIV) to reflect cognitive efficiency and provide unique insights into cognitive function, but there is limited knowledge on the effects of acute exercise on IIV. To this end, this study examined the effects of acute exercise on three different cognitive domains, executive function, implicit learning, and hippocampal-dependent memory function using behavioral performance and event-related potentials (ERPs). Furthermore, this study also sought to explore the effects of an acute bout of exercise on IIV using the RIDE algorithm to separate signals into individuals components based on latency variability. Healthy adult participants (N=20; 26.3±4.8years) completed a randomized cross-over trial with seated rest or 30min of high intensity cycling. Before and after each condition, participants completed a cognitive battery consisting of the Eriksen Flanker task, implicit statistical learning task, and a spatial reconstruction task. While exercise did not affect Flanker or spatial reconstruction performance, there were exercise related decreases in accuracy (F=5.47; P=0.040), slowed reaction time (F=5.18; P=0.036), and decreased late parietal positivity (F=4.26; P=0.046). However, upon adjusting for performance and ERP variability, there were exercise related decreases in Flanker reaction time (F=24.00; P<0.001), and reduced N2 amplitudes (F=13.03; P=0.002), and slower P3 latencies (F=3.57; P=0.065) for incongruent trials. These findings suggest that acute exercise may impact cognitive IIV as an adaptation to maintain function following exercise.

Diagnostic accuracy of CompCog: reaction time as a screening measure for mild cognitive impairment

BACKGROUND

Reaction time is affected under different neurological conditions but has not been much investigated considering all types of mild cognitive impairment (MCI).

OBJECTIVE

This study investigated the diagnostic accuracy of CompCog, a computerized cognitive screening battery focusing on reaction time measurements.

METHODS

A sample of 52 older adults underwent neuropsychological assessments, including CompCog, and medical appointments, to be classified as a control group or be diagnosed with MCI. The accuracy of CompCog for distinguishing between the two groups was calculated.

RESULTS

The results from diagnostic accuracy analyses showed that the AUCs of ROC curves were as high as 0.915 (CI 0.837-0.993). The subtest with the highest sensitivity and specificity (choice reaction time subtest) had 91.7% sensitivity and 89.3% specificity. The logistic regression final model correctly classified 92.3% of individuals, with 92.9% specificity and 91.7% sensitivity, and included only four variables from different subtests.

CONCLUSIONS

In summary, the study showed that reaction time assessed through CompCog is a good screening measure to differentiate between normal aging and MCI. Reaction time measurements in milliseconds were more accurate than correct answers. This test can form part of routine clinical tests to achieve the objectives of screening for MCI, indicating further procedures for investigation and diagnosis and planning interventions.

Evaluation of Processing Speed of Different Cognitive Functions Across the Life Span Using Cognitive Mobile Games

Objective: Processing speed (PS) is an important indicator of cognitive functioning and normal aging. However, the tools used to evaluate these are often rather simplistic and only assess one cognitive component. The aim of this study was to use cognitive mobile games (CMG) to evaluate the evolution of reaction times over the life span during different cognitive tasks. Methodology: We carried out a retrospective observational study in which we obtained anonymized results of 15,000 subjects. Scores of five CMG that train arithmetic, vocabulary, response control, visual attention and recognition, and working memory were analyzed. Results: Overall, we observed a highly statistically significant decrease (P < 0.001) in PS and a decrease of accuracy (P < 0.001) with increasing participant age, indicating that for each cognitive function tested, older participants performed cognitive tasks more slowly than younger participants. We also observed an interaction between the age of the participants and the number of errors. These results are consistent with physiological data with respect to aging and cognition. Conclusion: Owing to their wide availability and ease of use, CMG could be used as a simple tool to monitor cognitive function such as PS. Further studies are needed to study the influence of pathologies on those variables.