Background: Hearing impairments are associated with reduced walking performance under Dual-task (DT) conditions. Little is known about the neural representation of DT performance while walking in this target group compared to healthy controls or younger adults. Therefore, utilizing the Mobile Brain/Body Imaging approach (MoBI), we aim at gaining deeper insights into the brain dynamics underlying the interaction of cognitive and motor processes during different DT conditions (visual and auditory) controlling for age and the potential performance decrements of older adults with hearing impairments.Methods: The cross-sectional study integrates a multifactorial mixed-measure design. Between-subject factors grouping the sample will be age (younger vs. older adults) and hearing impairment (mild vs. not hearing impaired). The within-subject factors will be the task complexity (single- vs. DT) and cognitive task modality (visual vs. auditory). Stimuli of the cognitive task will vary according to the stimulus modality (visual vs. auditory), presentation side (left vs. right), and presentation-response compatibility (ipsilateral vs. contralateral). Analyses of DT costs and underlying neuronal correlates focus either on gait or cognitive performance. Based on an a priori sample size calculation 96 (48 healthy and 48 mildly hearing impaired) community-dwelling older adults (50–70 years) and 48 younger adults (20–30 years) will be recruited. Gait parameters of speed and rhythm will be captured. EEG activity will be recorded using 64 active electrodes.Discussion: The study evaluates cognitive-motor interference (CMI) in groups of young and older adults as well as older adults with hearing impairment. The underlying processes of the interaction between motor and cognitive tasks will be identified at a behavioral and neurophysiological level comparing an auditory or a visual secondary task. We assume that performance differences are linked to different cognitive-motor processes, i.e., stimulus input, resource allocation, and movement execution. Moreover, for the different DT conditions (auditory vs. visual) we assume performance decrements within the auditory condition, especially for older, hearing-impaired adults. Findings will provide evidence of general mechanisms of CMI (ST vs. DT walking) as well as task-specific effects in dual-task performance while over ground walking.

With advanced age, there is a loss of reaction speed that may contribute to an increased risk of tripping and falling. Avoiding falls and injuries requires awareness of the threat, followed by selection and execution of the appropriate motor response. Using event-related potentials (ERPs) and a simple visual reaction task (RT), the goal of our study was to distinguish sensory and motor processing in the upper- and lower-limbs while attempting to uncover the main cause of age-related behavioral slowing. Strength (amplitudes) as well as timing and speed (latencies) of various stages of stimulus- and motor-related processing were analyzed in 48 healthy individuals (young adults, n = 24, mean age = 34 years; older adults, n = 24, mean age = 67 years). The behavioral results showed a significant age-related slowing, where the younger compared to older adults exhibited shorter RTs for the upper- (222 vs. 255 ms; p = 0.006, respectively) and the lower limb (257 vs. 274 ms; p = 0.048, respectively) as well as lower variability in both modalities (p = 0.001). Using ERP indices, age-related slowing of visual stimulus processing was characterized by overall larger amplitudes with delayed latencies of endogenous potentials in older compared with younger adults. While no differences were found in the P1 component, the later components of recorded potentials for visual stimuli processing were most affected by age. This was characterized by increased N1 and P2 amplitudes and delayed P2 latencies in both upper and lower extremities. The analysis of motor-related cortical potentials (MR) revealed stronger MRCP amplitude for upper- and a non-significant trend for lower limbs in older adults. The MRCP amplitude was smaller and peaked closer to the actual motor response for the upper- than for the lower limb in both age groups. There were longer MRCP onset latencies for lower- compared to upper-limb in younger adults, and a non-significant trend was seen in older adults. Multiple regression analyses showed that the onset of the MRCP peak consistently predicted reaction time across both age groups and limbs tested. However, MRCP rise time and P2 latency were also significant predictors of simple reaction time, but only in older adults and only for the upper limbs. Our study suggests that motor cortical processes contribute most strongly to the slowing of simple reaction time in advanced age. However, late-stage cortical processing related to sensory stimuli also appears to play a role in upper limb responses in the elderly. This process most likely reflects less efficient recruitment of neuronal resources required for the upper and lower extremity response task in older adults.

Introduction: The number of obese people in the world is increasing, as is the number of sarcopenic people among the older adults. Although both states are concerning, they can be positively influenced by selected behavioral factors such as adequate nutrition and physical activity. We were interested in the prevalence of sarcopenic obesity in active older people and the influence of behavioral factors on this phenomenon.Methods: The study included 38 older adults (21 women) with a mean age of 75.3 ± 5.0 years. Sarcopenic parameters were determined with different tests: Handgrip Test, Chair Stand Test, Gait Speed, Timed Up and Go Test, and Short Physical Performance Battery. Body composition was measured by dual-energy x-ray absorptiometry. Physical activity level was measured using accelerometers, and nutritional status was assessed using the Mini-Nutritional Assessment and MEDLIFE Index questionnaire.Results: Of all included active participants (the average number of steps per day was 8,916 ± 3,543), 47.4% of them were obese. Of all included women, 52.4% were obese. Sarcopenic obesity was found in three (7.9%) participants. Nutritional status correlated with strength of lower extremities and physical performance tests (gait speed, Timed Up and Go Test and Short Physical performance battery). Higher number of steps per day positively correlates with physical performance.Discussion: Interestingly, we did not find any correlation between the main obesity parameter such as percent body fat or body mass index (and thus sarcopenic obesity) and any of the selected behavioral factors (physical activity, sedentary behavior, or dietary habits). In conclusion, reaching the recommended levels of physical activity in older adults may not be sufficient to prevent the occurrence of obesity and sarcopenic obesity.

Background: Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. Methods: The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson’s Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. Discussion: This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems.  Clinical Trial Registration: ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).

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A plethora of evidence links SARS-CoV-2 infection with concomitant cognitive dysfunction, which often persists weeks to months after the acute stages of illness and affects executive function, attention, memory, orientation, and movement control. It remains largely unclear which conditions or factors exacerbate the recovery. In a cohort of N=37 Slovenian patients (5 females, aged M = 58, SD = 10.7 years) that were hospitalized because of COVID-19, the cognitive function and mood states were assessed immediately after discharge and 2-months later to investigate the early post-COVID recovery changes. We assessed the global Montreal Cognitive Assessment (MoCA), Simple and Choice Reaction Times, executive functions (Trail-Making Test – TMT-A and TMT-B), short-term memory (Auditory Verbal Learning Test – AVLT), and visuospatial memory. We monitored depressive and anxiety symptoms and applied general self-efficacy and cognitive complaints questionnaires. Our results showed a global cognitive impairment (MoCA, Z = 332.5; p = 0.012), poorer performance on executive functions (TMT-A, Z = 188; p = 0.014; and TMT-B, Z = 185; p = 0.012), verbal memory (AVLT, F = 33.4; p < 0.001), and delayed recall (AVLT7, F = 17.1; p < 0.001), and higher depressive (Z = 145; p = 0.015) and anxiety (Z = 141; p = 0.003) symptoms after hospital discharge compared to 2-month follow-up, indicating that SARS-CoV-2 may transiently impair cognitive function and adversely affect the mood. No improvement in MoCA was observed in 40.5% of the patients at follow-up, indicating possible long-term effects of COVID-19 on global cognitive performance. Medical comorbidities (p = 0.035) significantly predicted the change in MoCA score over time, while fat mass (FM, p = 0.518), Mediterranean diet index (p = .0.944), and Florida Cognitive Activities Score (p = 0.927) did not. These results suggest that the patients’ medical comorbidities at the time of SARS-CoV-2 infection could importantly contribute to the acute impairment of cognitive function and stress the importance of systemic implementation of countermeasures to limit the negative consequences on public health.

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The utilization of a non-invasive electroencephalogram (EEG) as an input sensor is a common approach in the field of the brain–computer interfaces (BCI). However, the collected EEG data pose many challenges, one of which may be the age-related variability of event-related potentials (ERPs), which are often used as primary EEG BCI signal features. To assess the potential effects of aging, a sample of 27 young and 43 older healthy individuals participated in a visual oddball study, in which they passively viewed frequent stimuli among randomly occurring rare stimuli while being recorded with a 32-channel EEG set. Two types of EEG datasets were created to train the classifiers, one consisting of amplitude and spectral features in time and another with extracted time-independent statistical ERP features. Among the nine classifiers tested, linear classifiers performed best. Furthermore, we show that classification performance differs between dataset types. When temporal features were used, maximum individuals’ performance scores were higher, had lower variance, and were less affected overall by within-class differences such as age. Finally, we found that the effect of aging on classification performance depends on the classifier and its internal feature ranking. Accordingly, performance will differ if the model favors features with large within-class differences. With this in mind, care must be taken in feature extraction and selection to find the correct features and consequently avoid potential age-related performance degradation in practice.