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Objective: To determine whether gait and accelerometric features can predict disorientation events in young and older adults. Methods: Cognitively healthy younger (18-40 years, n = 25) and older (60-85 years, n = 28) participants navigated on a treadmill through a virtual representation of the city of Rostock featured within the Gait Real-Time Analysis Interactive Lab (GRAIL) system. We conducted Bayesian Poisson regression to determine the association of navigation performance with domain-specific cognitive functions. We determined associations of gait and accelerometric features with disorientation events in real-time data using Bayesian generalized mixed effect models. The accuracy of gait and accelerometric features to predict disorientation events was determined using cross-validated support vector machines (SVM) and Hidden Markov models (HMM). Results: Bayesian analysis revealed strong evidence for the effect of gait and accelerometric features on disorientation. The evidence supported a relationship between executive functions but not visuospatial abilities and perspective taking with navigation performance. Despite these effects, the cross-validated percentage of correctly assigned instances of disorientation was only 72% in the SVM and 63% in the HMM analysis using gait and accelerometric features as predictors. Conclusion: Disorientation is reflected in spatiotemporal gait features and the accelerometric signal as a potentially more easily accessible surrogate for gait features. At the same time, such measurements probably need to be enriched with other parameters to be sufficiently accurate for individual prediction of disorientation events.
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Background: Normal aging is associated with working memory decline. A decrease in working memory performance is associated with age-related changes in functional activation patterns in the dorsolateral prefrontal cortex (DLPFC). Cognitive training can improve cognitive performance in healthy older adults. We implemented a cognitive training study to assess determinants of generalization of training gains to untrained tasks, a key indicator for the effectiveness of cognitive training. We aimed to investigate the association of resting-state functional connectivity (FC) of DLPFC with working memory performance improvement and cognitive gains after the training. Method: A sample of 60 healthy older adults (mean age: 68 years) underwent a 4-week neuropsychological training, entailing a working memory task. Baseline resting-state functional MRI (rs-fMRI) images were acquired in order to investigate the FC of DLPFC. To evaluate training effects, participants underwent a neuropsychological assessment before and after the training. A second follow-up assessment was applied 12 weeks after the training. We used cognitive scores of digit span backward and visual block span backward tasks representing working memory function. The training group was divided into subjects who had and who did not have training gains, which was defined as a higher improvement in working memory tasks than the control group (N = 19). Results: A high FC of DLPFC of the right hemisphere was significantly associated with training gains and performance improvement in the visuospatial task. The maintenance of cognitive gains was restricted to the time period directly after the training. The training group showed performance improvement in the digit span backward task. Conclusion: Functional activation patterns of the DLPFC were associated with the degree of working memory training gains and visuospatial performance improvement. Although improvement through cognitive training and acquisition of training gains are possible in aging, they remain limited.