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Age-associated motor and cognitive deficits increase the risk of falls, a major cause of morbidity and mortality. Because of the significant ramifications of falls, many interventions have been proposed, but few have aimed to prevent falls via an integrated approach targeting both motor and cognitive function. We aimed to test the hypothesis that an intervention combining treadmill training with non-immersive virtual reality (VR) to target both cognitive aspects of safe ambulation and mobility would lead to fewer falls than would treadmill training alone. We carried out this randomised controlled trial at five clinical centres across five countries (Belgium, Israel, Italy, the Netherlands, and the UK). Adults aged 60–90 years with a high risk of falls based on a history of two or more falls in the 6 months before the study and with varied motor and cognitive deficits were randomly assigned by use of computer-based allocation to receive 6 weeks of either treadmill training plus VR or treadmill training alone. Randomisation was stratified by subgroups of patients (those with a history of idiopathic falls, those with mild cognitive impairment, and those with Parkinson's disease) and sex, with stratification per clinical site. Group allocation was done by a third party not involved in onsite study procedures. Both groups aimed to train three times per week for 6 weeks, with each session lasting about 45 min and structured training progression individualised to the participant's level of performance. The VR system consisted of a motion-capture camera and a computer-generated simulation projected on to a large screen, which was specifically designed to reduce fall risk in older adults by including real-life challenges such as obstacles, multiple pathways, and distracters that required continual adjustment of steps. The primary outcome was the incident rate of falls during the 6 months after the end of training, which was assessed in a modified intention-to-treat population. Safety was assessed in all patients who were assigned a treatment. This study is registered with ClinicalTrials.gov, NCT01732653. Between Jan 6, 2013, and April 3, 2015, 302 adults were randomly assigned to either the treadmill training plus VR group (n=154) or treadmill training alone group (n=148). Data from 282 (93%) participants were included in the prespecified, modified intention-to-treat analysis. Before training, the incident rate of falls was similar in both groups (10·7 [SD 35·6] falls per 6 months for treadmill training alone vs 11·9 [39·5] falls per 6 months for treadmill training plus VR). In the 6 months after training, the incident rate was significantly lower in the treadmill training plus VR group than it had been before training (6·00 [95% CI 4·36–8·25] falls per 6 months; p<0·0001 vs before training), whereas the incident rate did not decrease significantly in the treadmill training alone group (8·27 [5·55–12·31] falls per 6 months; p=0·49). 6 months after the end of training, the incident rate of falls was also significantly lower in the treadmill training plus VR group than in the treadmill training group (incident rate ratio 0·58, 95% CI 0·36–0·96; p=0·033). No serious training-related adverse events occurred. In a diverse group of older adults at high risk for falls, treadmill training plus VR led to reduced fall rates compared with treadmill training alone. European Commission.

The cortical control of gait and mobility involves multiple brain regions. Therefore, one could speculate that the association between specific spatial patterns of cortical thickness may be differentially associated with different mobility domains. To test this possibility, 115 healthy participants aged 27–82 (mean 60.5 ± 13.8) underwent a mobility assessment (usual-walk, dual-task walk, Timed Up and Go) and MRI scan. Ten mobility domains of relatively simple (e.g., usual-walking) and complex tasks (i.e., dual task walking, turns, transitions) and cortical thickness of 68 ROIs were extracted. All associations between mobility and cortical thickness were controlled for age and gender. Scaled Subprofile Modelling (SSM), a PCA-regression, identified thickness patterns that were correlated with the individual mobility domains, controlling for multiple comparisons. We found that lower mean global cortical thickness was correlated with worse general mobility (r = − 0.296, p  = 0.003), as measured by the time to complete the Timed Up and Go test. Three distinct patterns of cortical thickness were associated with three different gait domains during simple, usual-walking: pace, rhythm, and symmetry. In contrast, cortical thickness patterns were not related to the more complex mobility domains. These findings demonstrate that robust and topographically distinct cortical thickness patterns are linked to select mobility domains during relatively simple walking, but not to more complex aspects of mobility. Functional connectivity may play a larger role in the more complex aspects of mobility.

BackgroundThe ability to maintain adequate motor-cognitive performance under increasing task demands depends on the regulation and coordination of neural resources. Studies have shown that such resources diminish with aging and disease. EEG spectral analysis is a method that has the potential to provide insight into neural alterations affecting motor-cognitive performance. The aim of this study was to assess changes in spectral analysis during dual-task walking in aging and diseaseMethods10 young adults, ten older adults, and ten patients with Parkinson’s disease (PD) completed an auditory oddball task while standing and while walking on a treadmill. Spectral power within four frequency bandwidths, delta (< 4 Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–30 Hz), was calculated using Event-Related Spectral Perturbation (ERSP) analyses and compared between single task and dual task and between groups.ResultsDifferences in ERSP were found in all groups between the single and dual-task conditions. In response to dual-task walking, beta increased in all groups (p < 0.026), delta decreased in young adults (p = 0.03) and patients with PD (0.015) while theta increased in young adults (p = 0.028) but decreased in older adults (p = 0.02) and patients with PD (p = 0.015). Differences were seen between the young, the older adults, and the patients with PD.ConclusionsThese findings are the first to show changes in the power of different frequency bands during dual-task walking with aging and disease. These specific brain modulations may reflect deficits in readiness and allocation of attention that may be responsible for the deficits in dual-task performance.

Background Accumulating evidence suggests that gait is influenced by higher order cognitive and cortical control mechanisms. Recently, several studies used functional near infrared spectroscopy (fNIRS) to examine brain activity during walking, demonstrating increased oxygenated hemoglobin (HbO 2 ) levels in the frontal cortex during walking while subjects completed a verbal cognitive task. It is, however, still unclear whether this increase in activation was related to verbalization, if the response was specific to gait, or if it would also be observed during standing, a different motor control task. The aim of this study was to investigate whether an increase in frontal activation is specific to dual tasking during walking. Methods Twenty-three healthy young adults (mean 30.9 ± 3.7 yrs, 13 females) were assessed using an electronic walkway. Frontal brain activation was assessed using an fNIRS system consisting of two probes placed on the forehead of the subjects. Assessments included: walking in a self-selected speed; walking while counting forward; walking while serially subtracting 7s (Walking+S7); and standing while serially subtracting 7s (Standing+S7). Data was collected from 5 walks of 30 meters in each condition. Twenty seconds of quiet standing before each walk served as baseline frontal lobe activity. Repeated Measures Analysis of Variance (RM ANOVA) tested for differences between the conditions. Results Significant differences were observed in HbO 2 levels between all conditions (p = 0.007). HbO 2 levels appeared to be graded; walking alone demonstrated the lowest levels of HbO2 followed by walking+counting condition (p = 0.03) followed by Walking+S7 condition significantly increased compared to the two other walking conditions (p < 0.01). No significant differences in HbO 2 levels were observed between usual walking and the standing condition (p = 0.38) or between standing with or without serial subtraction (p = 0.76). Conclusions This study provides direct evidence that dual tasking during walking is associated with frontal brain activation in healthy young adults. The observed changes are apparently not a response to the verbalization of words and are related to the cognitive load during gait.

Background Early diagnosis of Parkinson’s disease (PD) can assist in designing efficient treatments. Reduced facial expressions are considered a hallmark of PD, making advanced artificial intelligence (AI) image processing a potential non-invasive clinical decision support tool for PD detection. This study aims to determine the sensitivity of image-to-text AI, which matches facial frames recorded in home settings with descriptions of PD facial expressions, in identifying patients with PD. Methods Facial image of 67 PD patients and 52 healthy-controls (HCs) were collected via standard video recording. Using clinical knowledge, we compiled descriptive sentences detailing facial characteristics associated with PD. The facial images were analyzed with OpenAI’s CLIP model to generate probability scores, indicating the likelihood of each image matching the PD-related descriptions. These scores were used in an XGBoost model to identify PD patients based on the total, motor, and facial-expression item of the MDS-UPDRS, a common scale for assessing disease severity. Results The image-to-text AI technology showed the best results in identifying PD patients based on the facial expression item (AUC = 0.78 ± 0.05), especially for those with ‘mild’ facial symptoms (AUC = 0.87 ± 0.04). The motor MDS-UPDRS score followed (AUC = 0.69 ± 0.05), while the total MDS-UPDRS score showed the lowest performance in identifying PD patients (AUC = 0.59 ± 0.05). PD matching probabilities between facial images and sentences revealed significant correlations across all MDS-UPDRS components (r > 0.23, p < 0.0001). Conclusions Our results demonstrate the feasibility of using advanced AI in a clinical decision support tool for PD diagnosis, suggesting a novel approach for home-based screening to identify PD patients. This method represents a significant innovation, transforming clinical knowledge into practical algorithms that can serve as effective screening tools. Clinical trial number MOH_2023-04-16_012535

The “levodopa-overdose hypothesis” posits that dopaminergic replacement therapy (1) increases performance on tasks that depend on the nigrostriatal-pathway (e.g., motor-control circuits), yet (2) decreases performance on tasks that depend upon the mesocorticolimbic-pathway (e.g., prefrontal cortex, PFC). Previous work in Parkinson’s disease (PD) investigated this model while focusing on cognitive function. Here, we evaluated whether this model applies to gait in patients with PD and freezing of gait (FOG). Forty participants were examined in both the OFF anti-Parkinsonian medication state (hypo-dopaminergic) and ON state (hyper-dopaminergic) while walking with and without the concurrent performance of a serial subtraction task. Wireless functional near-infrared spectroscopy measured PFC activation during walking. Consistent with the “overdose-hypothesis”, performance on the subtraction task decreased (p = 0.027) after dopamine intake. Moreover, the effect of walking condition on PFC activation depended on the dopaminergic state (i.e., interaction effect p = 0.001). Gait significantly improved after levodopa administration (p < 0.001). Nonetheless, PFC activation was higher (p = 0.013) in this state than in the OFF state during usual-walking. This increase in PFC activation in the ON state suggests that dopamine treatment interfered with PFC functioning. Otherwise, PFC activation, putatively a reflection of cognitive compensation, should have decreased. Moreover, in contrast to the OFF state, in the ON state, PFC activation failed to increase (p = 0.313) during dual-tasking, perhaps due to a “ceiling effect”. These findings extend the “levodopa-overdose hypothesis” and suggest that it also applies to gait in PD patients. While dopaminergic therapy improves certain aspects of motor performance, optimal treatment should consider the \"double-edged sword\" of levodopa.

Amyloid beta (Aβ) deposition has been implicated in the disruption of neuronal activity and large-scale network connectivity in older adults, contributing to impairments in cognitive function and mobility. Nevertheless, the extent to which regional patterns of Aβ accumulation differentially influence gait and cognition, and whether cognitive function modulates the association between Aβ burden and gait performance in healthy aging, remain insufficiently understood. This study examined the complex relationships among regional Aβ deposition, gait performance, and cognitive function in healthy older adults. The study included 33 healthy older adults (mean age = 65.72 ± 2.77 years; 12 females, 21 males). Participants underwent PET scans, cognitive assessments, and gait evaluations in usual-walk (UW) and dual-task (DT) conditions. Pittsburg Compound B (PiB-PET) imaging quantified Aβ burden across 68 brain regions. A three-step statistical analysis was conducted. Hierarchical regression models explored connections between Aβ, cognitive function (reasoning, vocabulary, memory, processing speed), and gait performance. Path analysis examined inter-relationships. All models were adjusted for age, sex, and years of education. A statistical threshold of p  ≤ 0.05, adjusted for multiple comparisons, was applied. Elevated Aβ levels in the pallidal (β=-0.05, p  < 0.001), and entorhinal cortex (β=-0.35, p  = 0.021), were significantly associated with poorer step regularity, and hippocampal Aβ levels (β=-1.3, p  = 0.037) were significantly associated with poorer step symmetry under UW conditions. During DT walking, higher Aβ in the cerebellar was associated with reduced stride regularity (β=-1.38, p  = 0.034), while higher cerebellar and pericalcarine Aβ was linked to lower step symmetry performance (β=-1.1, p  < 0.001). In contrast, elevated Aβ in the cingulate (β = 0.75, p  < 0.001) and cuneus (β = 0.49, p  = 0.024) was positively associated with step symmetry. Path analyses indicated that cognitive scores in vocabulary and reasoning moderated the relationship between regional Aβ deposition and DT stride regularity and step symmetry. The obtained results indicate that regional Aβ deposition is differentially associated with specific gait metrics depending on brain region and walking condition. Cognitive performance in vocabulary and reasoning moderated these associations, indicating a potential protective role. These findings highlight the relevance of region-specific pathology and cognition in early detection of age-related motor and cognitive decline.

Background: The G2019S-LRRK2 gene mutation is a common cause of hereditary Parkinson’s disease (PD), associated with a higher frequency of the postural instability gait difficulty (PIGD) motor phenotype yet with preserved cognition. This study investigated neurophysiological changes during motor and cognitive tasks in PD patients with and without the G2019S-LRRK2 mutation. Methods: 33 iPD patients and 22 LRRK2-PD patients performed the visual Go/NoGo task (VGNG) during sitting (single-task) and walking (dual-task) while wearing a 64-channel EEG cap. Event-related potentials (ERP) from Fz and Pz, specifically N200 and P300, were extracted and analyzed to quantify brain activity patterns. Results: The LRRK2-PD group performed better in the VGNG than the iPD group (group*task; p = 0.05). During Go, the iPD group showed reduced N2 amplitude and prolonged N2 latency during walking, whereas the LRRK2-PD group showed only shorter latency (group*task p = 0.027). During NoGo, opposite patterns emerged; the iPD group showed reduced N2 and increased P3 amplitudes during walking while the LRRK2-PD group demonstrated increased N2 and reduced P3 (N2: group*task, p = 0.010, P3: group*task, p = 0.012). Conclusions: The LRRK2-PD group showed efficient early cognitive processes, reflected by N2, resulting in greater neural synchronization and prominent ERPs. These processes are possibly the underlying mechanisms for the observed better cognitive performance as compared to the iPD group. As such, future applications of intelligent medical sensing should be capable of capturing these electrophysiological patterns in order to enhance motor–cognitive functions.

Background: Parkinson’s disease (PD) is currently considered to be a multisystem neurodegenerative disease that involves cognitive alterations. EEG slowing has been associated with cognitive decline in various neurological diseases, such as PD, Alzheimer’s disease (AD), and epilepsy, indicating cortical involvement. A novel method revealed that this EEG slowing is composed of paroxysmal slow-wave events (PSWE) in AD and epilepsy, but in PD it has not been tested yet. Therefore, this study aimed to examine the presence of PSWE in PD as a biomarker for cortical involvement. Methods: 31 PD patients, 28 healthy controls, and 18 juvenile myoclonic epilepsy (JME) patients (served as positive control), underwent four minutes of resting-state EEG. Spectral analyses were performed to identify PSWEs in nine brain regions. Mixed-model analysis was used to compare between groups and brain regions. The correlation between PSWEs and PD duration was examined using Spearman’s test. Results: No significant differences in the number of PSWEs were observed between PD patients and controls (p > 0.478) in all brain regions. In contrast, JME patients showed a higher number of PSWEs than healthy controls in specific brain regions (p < 0.023). Specifically in the PD group, we found that a higher number of PSWEs correlated with longer disease duration. Conclusions: This study is the first to examine the temporal characteristics of EEG slowing in PD by measuring the occurrence of PSWEs. Our findings indicate that PD patients who are cognitively intact do not have electrographic manifestations of cortical involvement. However, the correlation between PSWEs and disease duration may support future studies of repeated EEG recordings along the disease course to detect early signs of cortical involvement in PD.

Introduction: Aging affects the interplay between cognition and gait performance. Neuroimaging studies reported associations between gait performance and structural measures; however, functional connectivity (FC) analysis of imaging data can help to identify dynamic neural mechanisms underlying optimal performance. Here, we investigated the effects on divergent cognitive and inter-network FC patterns underlying gait performance during usual (UW) and dual-task (DT) walking. Methods: 115 community-dwelling, healthy participants between 20-80 years were enrolled. All participants underwent comprehensive cognitive and gait assessments in two conditions and resting state functional MRI scans. Inter-network FC from motor-related to 6 primary cognitive networks was estimated. Step-wise regression models tested the relationships between gait parameters, inter-network FC, neuropsychological scores, and demographic variables. A threshold of p 65 years) showed increased integration between motor, dorsal, and ventral attention, as well as default-mode networks, was negatively associated with UW gait performance. Inverse associations between motor and sustained attention inter-network connectivity and DT performance was observed. Conclusions: While UW relies on inter-network FC between motor and sustained attention networks, DT performance relies on additional cognitive capacities, increased motor, and executive control network integration. FC analyses demonstrate that the decline in cognitive performance with aging leads to the reliance on additional neural resources required maintaining routine walking tasks.