Learning to play golf for elderly people with subjective memory complaints: feasibility of a single-blinded randomized pilot trial.

BACKGROUND: Subjective Memory Complaints (SMC) in elderly people due to preclinical Alzheimer's Disease may be associated with dysregulation of the Kynurenine Pathway (KP), with an increase in neurotoxic metabolites that affect cognition. Golf is a challenging sport with high demands on motor, sensory, and cognitive abilities, which might bear the potential to attenuate the pathological changes of preclinical AD. This trial investigated the feasibility of learning to play golf for elderly with cognitive problems and its effects on cognitive functions and the KP. METHODS: In a 22-week single-blinded randomized controlled trial, elderly people with SMC were allocated to the golf (n = 25, 180 min training/week) or control group (n = 21). Primary outcomes were feasibility (golf exam, adherence, adverse events) and general cognitive function (Alzheimer's Disease Assessment Scale). Secondary outcomes include specific cognitive functions (Response Inhibition, Corsi Block Tapping Test, Trail Making Test), KP metabolites and physical performance (6-Minute-Walk-Test). Baseline-adjusted Analysis-of-Covariance was conducted for each outcome. RESULTS: 42 participants were analyzed. All participants that underwent the golf exam after the intervention passed it (20/23). Attendance rate of the golf intervention was 75 %. No adverse events or drop-outs related to the intervention occurred. A significant time*group interaction (p = 0.012, F = 7.050, Cohen's d = 0.89) was found for correct responses on the Response Inhibition task, but not for ADAS-Cog. Moreover, a significant time*group interaction for Quinolinic acid to Tryptophan ratios (p = 0.022, F = 5.769, Cohen's d = 0.84) in favor of the golf group was observed. An uncorrected negative correlation between attendance rate and delta Quinolinic acid to Kynurenic acid ratios in the golf group (p = 0.039, r=-0.443) was found as well. CONCLUSIONS: The findings indicate that learning golf is feasible and safe for elderly people with cognitive problems. Preliminary results suggest positive effects on attention and the KP. To explore the whole potential of golfing and its effect on cognitive decline, a larger cohort should be studied over a longer period with higher cardiovascular demands. TRIAL REGISTRATION: The trial was retrospectively registered (2nd July 2018) at the German Clinical Trials Register ( DRKS00014921 ).

Classification of age groups and task conditions provides additional evidence for differences in electrophysiological correlates of inhibitory control across the lifespan.

The aim of this study was to extend previous findings on selective attention over a lifetime using machine learning procedures. By decoding group membership and stimulus type, we aimed to study differences in the neural representation of inhibitory control across age groups at a single-trial level. We re-analyzed data from 211 subjects from six age groups between 8 and 83 years of age. Based on single-trial EEG recordings during a flanker task, we used support vector machines to predict the age group as well as to determine the presented stimulus type (i.e., congruent, or incongruent stimulus). The classification of group membership was highly above chance level (accuracy: 55%, chance level: 17%). Early EEG responses were found to play an important role, and a grouped pattern of classification performance emerged corresponding to age structure. There was a clear cluster of individuals after retirement, i.e., misclassifications mostly occurred within this cluster. The stimulus type could be classified above chance level in ~ 95% of subjects. We identified time windows relevant for classification performance that are discussed in the context of early visual attention and conflict processing. In children and older adults, a high variability and latency of these time windows were found. We were able to demonstrate differences in neuronal dynamics at the level of individual trials. Our analysis was sensitive to mapping gross changes, e.g., at retirement age, and to differentiating components of visual attention across age groups, adding value for the diagnosis of cognitive status across the lifespan. Overall, the results highlight the use of machine learning in the study of brain activity over a lifetime.

Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults.

Cardiorespiratory fitness was found to influence age-related changes of resting state brain network organization. However, the influence on dedifferentiated involvement of wider and more unspecialized brain regions during task completion is barely understood. We analyzed EEG data recorded during rest and different tasks (sensory, motor, cognitive) with dynamic mode decomposition, which accounts for topological characteristics as well as temporal dynamics of brain networks. As a main feature the dominant spatio-temporal EEG pattern was extracted in multiple frequency bands per participant. To deduce a pattern's stability, we calculated its proportion of total variance among all activation patterns over time for each task. By comparing fit (N = 15) and less fit older adults (N = 16) characterized by their performance on a 6-min walking test, we found signs of a lower task specificity of the obtained network features for the less fit compared to the fit group. This was indicated by fewer significant differences between tasks in the theta and high beta frequency band in the less fit group. Repeated measures ANOVA revealed that a significantly lower proportion of total variance can be explained by the main pattern in high beta frequency range for the less fit compared to the fit group [F(1,29) = 12.572, p = .001, partial η2 = .300]. Our results indicate that the dedifferentiation in task-related brain activation is lower in fit compared to less fit older adults. Thus, our study supports the idea that cardiorespiratory fitness influences task-related brain network organization in different task domains. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s11571-020-09656-9) contains supplementary material, which is available to authorized users.