Investigating the Brain Mechanisms of Externally Cued Sit-to-Stand Movement in Parkinson's Disease.

BACKGROUND: One of the more challenging daily-life actions for Parkinson's disease patients is starting to stand from a sitting position. Parkinson's disease patients are known to have difficulty with self-initiated movements and benefit from external cues. However, the brain processes underlying external cueing as an aid remain unknown. The advent of mobile electroencephalography (EEG) now enables the investigation of these processes in dynamic sit-to-stand movements. OBJECTIVE: To identify cortical correlates of the mechanisms underlying auditory cued sit-to-stand movement in Parkinson's disease. METHODS: Twenty-two Parkinson's disease patients and 24 healthy age-matched participants performed self-initiated and externally cued sit-to-stand movements while cortical activity was recorded through 32-channel mobile EEG. RESULTS: Overall impaired integration of sensory and motor information can be seen in the Parkinson's disease patients exhibiting less modulation in the θ band during movement compared to healthy age-matched controls. How Parkinson's disease patients use external cueing of sit-to-stand movements can be seen in larger high ß power over sensorimotor brain areas compared to healthy controls, signaling sensory integration supporting the maintenance of motor output. This appears to require changes in cognitive processing to update the motor plan, reflected in frontal θ power increases in Parkinson's disease patients when cued. CONCLUSION: These findings provide the first neural evidence for why and how cueing improves motor function in sit-to-stand movement in Parkinson's disease. The Parkinson's disease patients' neural correlates indicate that cueing induces greater activation of motor cortical areas supporting the maintenance of a more stable motor output, but involves the use of cognitive resources to update the motor plan. © 2024 International Parkinson and Movement Disorder Society.

Digital Mobility Measures: A Window into Real-World Severity and Progression of Parkinson's Disease.

BACKGROUND: Real-world monitoring using wearable sensors has enormous potential for assessing disease severity and symptoms among persons with Parkinson's disease (PD). Many distinct features can be extracted, reflecting multiple mobility domains. However, it is unclear which digital measures are related to PD severity and are sensitive to disease progression. OBJECTIVES: The aim was to identify real-world mobility measures that reflect PD severity and show discriminant ability and sensitivity to disease progression, compared to the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scale. METHODS: Multicenter real-world continuous (24/7) digital mobility data from 587 persons with PD and 68 matched healthy controls were collected using an accelerometer adhered to the lower back. Machine learning feature selection and regression algorithms evaluated associations of the digital measures using the MDS-UPDRS (I-III). Binary logistic regression assessed discriminatory value using controls, and longitudinal observational data from a subgroup (n = 33) evaluated sensitivity to change over time. RESULTS: Digital measures were only moderately correlated with the MDS-UPDRS (part II-r = 0.60 and parts I and III-r = 0.50). Most associated measures reflected activity quantity and distribution patterns. A model with 14 digital measures accurately distinguished recently diagnosed persons with PD from healthy controls (81.1%, area under the curve: 0.87); digital measures showed larger effect sizes (Cohen's d: [0.19-0.66]), for change over time than any of the MDS-UPDRS parts (Cohen's d: [0.04-0.12]). CONCLUSIONS: Real-world mobility measures are moderately associated with clinical assessments, suggesting that they capture different aspects of motor capacity and function. Digital mobility measures are sensitive to early-stage disease and to disease progression, to a larger degree than conventional clinical assessments, demonstrating their utility, primarily for clinical trials but ultimately also for clinical care. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Cerebellar Direct Current Stimulation Reveals the Causal Role of the Cerebellum in Temporal Prediction.

Temporal prediction (TP) influences our perception and cognition. The cerebellum could mediate this multi-level ability in a context-dependent manner. We tested whether a modulation of the cerebellar neural activity, induced by transcranial Direct Current Stimulation (tDCS), changed the TP ability according to the temporal features of the context and the duration of target interval. Fifteen healthy participants received anodal, cathodal, and sham tDCS (15 min × 2 mA intensity) over the right cerebellar hemisphere during a TP task. We recorded reaction times (RTs) to a target during the task in two contextual conditions of temporal anticipation: rhythmic (i.e., interstimulus intervals (ISIs) were constant) and single-interval condition (i.e., the estimation of the timing of the target was based on the prior exposure of the train of stimuli). Two ISIs durations were explored: 600 ms (short trials) and 900 ms (long trials). Cathodal tDCS improved the performance during the TP task (shorter RTs) specifically in the rhythmic condition only for the short trials and in the single-interval condition only for the long trials. Our results suggest that the inhibition of cerebellar activity induced a different improvement in the TP ability according to the temporal features of the context. In the rhythmic context, the cerebellum could integrate the temporal estimation with the anticipatory motor responses critically for the short target interval. In the single-interval context, for the long trials, the cerebellum could play a main role in integrating representation of time interval in memory with the elapsed time providing an accurate temporal prediction.

Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study.

Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, ß, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and ß bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, ß ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.

Action Observation and Motor Imagery as a Treatment in Patients with Parkinson's Disease.

Action observation (AO) and motor imagery (MI) has emerged as promising tool for physiotherapy intervention in Parkinson's disease (PD). This narrative review summarizes why, how, and when applying AO and MI training in individual with PD. We report the neural underpinning of AO and MI and their effects on motor learning. We examine the characteristics and the current evidence regarding the effectiveness of physiotherapy interventions and we provide suggestions about their implementation with technologies. Neurophysiological data suggest a substantial correct activation of brain networks underlying AO and MI in people with PD, although the occurrence of compensatory mechanisms has been documented. Regarding the efficacy of training, in general evidence indicates that both these techniques improve mobility and functional activities in PD. However, these findings should be interpreted with caution due to variety of the study designs, training characteristics, and the modalities in which AO and MI were applied. Finally, results on long-term effects are still uncertain. Several elements should be considered to optimize the use of AO and MI in clinical setting, such as the selection of the task, the imagery or the video perspectives, the modalities of training. However, a comprehensive individual assessment, including motor and cognitive abilities, is essential to select which between AO and MI suite the best to each PD patients. Much unrealized potential exists for the use AO and MI training to provide personalized intervention aimed at fostering motor learning in both the clinic and home setting.

Motor imagery ability scores are related to cortical activation during gait imagery.

Motor imagery (MI) is the mental execution of actions without overt movements that depends on the ability to imagine. We explored whether this ability could be related to the cortical activity of the brain areas involved in the MI network. To this goal, brain activity was recorded using high-density electroencephalography in nineteen healthy adults while visually imagining walking on a straight path. We extracted Event-Related Desynchronizations (ERDs) in the θ, α, and ß band, and we measured MI ability via (i) the Kinesthetic and Visual Imagery Questionnaire (KVIQ), (ii) the Vividness of Movement Imagery Questionnaire-2 (VMIQ), and (iii) the Imagery Ability (IA) score. We then used Pearson's and Spearman's coefficients to correlate MI ability scores and average ERD power (avgERD). Positive correlations were identified between VMIQ and avgERD of the middle cingulum in the ß band and with avgERD of the left insula, right precentral area, and right middle occipital region in the θ band. Stronger activation of the MI network was related to better scores of MI ability evaluations, supporting the importance of testing MI ability during MI protocols. This result will help to understand MI mechanisms and develop personalized MI treatments for patients with neurological dysfunctions.

How Does Postural Control in Patients with Functional Motor Disorders Adapt to Multitasking-Based Immersive Virtual Reality?

BACKGROUND: Motor symptoms in functional motor disorders (FMDs) refer to involuntary, but learned, altered movement patterns associated with aberrant self-focus, sense of agency, and belief/expectations. These conditions commonly lead to impaired posture control, raising the likelihood of falls and disability. Utilizing visual and cognitive tasks to manipulate attentional focus, virtual reality (VR) integrated with posturography is a promising tool for exploring postural control disorders. OBJECTIVES: To investigate whether postural control can be adapted by manipulating attentional focus in a 3D immersive VR environment. METHODS: We compared postural parameters in 17 FMDs patients and 19 age-matched healthy controls over a single session under four increasingly more complex and attention-demanding conditions: simple fixation task (1) in the real room and (2) in 3D VR room-like condition; complex fixation task in a 3D VR city-like condition (3) avoiding distractors and (4) counting them. Dual-task effect (DTE) measured the relative change in performance induced by the different attention-demanding conditions on postural parameters. RESULTS: Patients reduced sway area and mediolateral center of pressure displacement velocity DTE compared to controls (all, P < 0.049), but only under condition 4. They also showed a significant reduction in the sway area DTE under condition 4 compared to condition 3 (P = 0.025). CONCLUSIONS: This study provides novel preliminary evidence for the value of a 3D immersive VR environment combined with different attention-demanding conditions in adapting postural control in patients with FMDs. As supported by quantitative and objective posturographic measures, our findings may inform interventions to explore FMDs pathophysiology.

A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders.

Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is not yet optimal. We developed machine-learning models to estimate step length based on data derived from a single lower-back inertial measurement unit worn by 472 young and older adults with different neurological conditions, including Parkinson's disease and healthy controls. Studying more than 80,000 steps, the best model showed high accuracy for a single step (root mean square error, RMSE = 6.08 cm, ICC(2,1) = 0.89) and higher accuracy when averaged over ten consecutive steps (RMSE = 4.79 cm, ICC(2,1) = 0.93), successfully reaching the predefined goal of an RMSE below 5 cm (often considered the minimal-clinically-important-difference). Combining machine-learning with a single, wearable sensor generates accurate step length measures, even in patients with neurologic disease. Additional research may be needed to further reduce the errors in certain conditions.

Factors influencing physiotherapy decisions between restorative and compensatory gait rehabilitation: an Italian multicenter study.

Background and purpose: This study aimed to investigate the factors that influence physiotherapists' decision in choosing restorative or compensatory rehabilitation during gait training in people with neurological disorders (PwNDs) and the different treatments used in the approaches. Methods: This cross-sectional analysis used the baseline data from an observational cohort study. We analyzed data from 83 PwNDs (65 people after stroke, 5 with multiple sclerosis, and 13 with Parkinson's disease) who underwent at least 10 sessions of physiotherapy (PT) focusing on gait function. Performance was quantified using the modified Dynamic Gait Index (MDGI), three impairment domains of Fugl-Meyer Assessment for lower extremity (mFM-LL), Activities-specific Balance Confidence (ABC), modified Barthel Index (mBI), Mini-Mental State Examination (MMSE), and Motivational Index (MI). Forty-three physiotherapists completed a treatment report form categorizing the rehabilitation approach and specifying treatments used (e.g., resistance training and proprioceptive exercises). Results: Fifty-six subjects underwent restorative rehabilitation approach. The univariate predictors of restorative approach were being in the subacute phase with a disease onset of less than 180 days, (odds ratio [95%CI]; 3.27[1.19-9.24]), mFM-LL (1.25[1.11-1.44]), MMSE (0.85[0.67-1.00]), and number of sessions (1.03[1-1.01]). The backward stepwise analysis revealed an association between restorative and subacute phase (36.32[4.11-545.50]), mFM-LL (3.11[1.55-9.73]), mBI (1.79[1.08-3.77]), MMSE (0.46[0.25-0.71]), and the interaction between mFM-LL and mBI (0.99[0.98-1.00]). No statistically significant association between treatments used and approach was found (p = 0.46). Discussion and conclusion: The restorative approach was more commonly used to improve gait. The main variables associated with this approach were: being in the subacute phase of the disease, a low level of impairment, and a high level of functional independence at baseline. However, few differences were found between the treatments used for the restorative or compensatory approaches, as similar PT treatments were used for both.

Modulation of response times in early-stage Parkinson's disease during emotional processing of embodied and non-embodied stimuli.

Valence (positive and negative) and content (embodied vs non-embodied) characteristics of visual stimuli have been shown to influence motor readiness, as tested with response time paradigms. Both embodiment and emotional processing are affected in Parkinson's disease (PD) due to basal ganglia dysfunction. Here we aimed to investigate, using a two-choice response time paradigm, motor readiness when processing embodied (emotional body language [EBL] and emotional facial expressions [FACS]) vs non-embodied (emotional scenes [IAPS]) stimuli with neutral, happy, and fearful content. We enrolled twenty-five patients with early-stage PD and twenty-five age matched healthy participants. Motor response during emotional processing was assessed by measuring response times (RTs) in a home-based, forced two-choice discrimination task where participants were asked to discriminate the emotional stimulus from the neutral one. Rating of valence and arousal was also performed. A clinical and neuropsychological evaluation was performed on PD patients. Results showed that RTs for PD patients were longer for all conditions compared to HC and that RTs were generally longer in both groups for EBL compared to FACS and IAPS, with the sole exception retrieved for PD, where in discriminating fearful stimuli, RTs for EBL were longer compared to FACS but not to IAPS. Furthermore, in PD only, when discriminating fearful respect to neutral stimuli, RTs were shorter when discriminating FACS compared to IAPS. This study shows that PD patients were faster in discriminating fearful embodied stimuli, allowing us to speculate on mechanisms involving an alternative, compensatory, emotional motor pathway for PD patients undergoing fear processing.

Supplementing Best Care with Specialized Rehabilitation Treatment in Parkinson's Disease: A Retrospective Study by Different Expert Centers.

Background: This is a retrospective longitudinal study comparing 374 patients with Parkinson's disease (PD) who were treated in centers offering a specialized program of enhanced rehabilitation therapy in addition to expert outpatient care to 387 patients with PD, who only received expert outpatient care at movement disorders centers in Italy. Methods: The data are from subjects recruited in the Parkinson's Outcome Project (POP) at six Italian centers that are part of a multicenter collaboration for care quality improvement (the Fresco Network). The effects were measured with a baseline and a follow-up clinical evaluation of the Timed-Up-and-Go test (TUG), Parkinson's Disease Questionnaire (PDQ-39), and Multidimensional Caregiver Strain Index (MCSI), the number of falls and hospitalizations for any cause. We used a generalized linear mixed model with the dependent variables being the response variable, which included the covariates demographics, evaluation, and treatment variables. Results: We found that the subjects who underwent specialized enhanced rehabilitation had a better motor outcome over time than those who were managed by expert neurologists but had participated in community programs for exercise and other allied health interventions. The greatest effects were seen in patients in the early stages of the disease with a high amount of vigorous exercise per week in the last six months. Similar effects were seen for PDQ39, MCSI, the number of falls, and hospitalization. Conclusions: Long-term benefits to motor function and the quality of life in patients with PD and burden reduction in their caregivers can be achieved through a systematic program of specialized enhanced rehabilitation interventions.

Characterizing neurocognitive impairments in Parkinson's disease with mobile EEG when walking and stepping over obstacles.

The neural correlates that help us understand the challenges that Parkinson's patients face when negotiating their environment remain under-researched. This deficit in knowledge reflects the methodological constraints of traditional neuroimaging techniques, which include the need to remain still. As a result, much of our understanding of motor disorders is still based on animal models. Daily life challenges such as tripping and falling over obstacles represent one of the main causes of hospitalization for individuals with Parkinson's disease. Here, we report the neural correlates of naturalistic ambulatory obstacle avoidance in Parkinson's disease patients using mobile EEG. We examined 14 medicated patients with Parkinson's disease and 17 neurotypical control participants. Brain activity was recorded while participants walked freely, and while they walked and adjusted their gait to step over expected obstacles (preset adjustment) or unexpected obstacles (online adjustment) displayed on the floor. EEG analysis revealed attenuated cortical activity in Parkinson's patients compared to neurotypical participants in theta (4-7 Hz) and beta (13-35 Hz) frequency bands. The theta power increase when planning an online adjustment to step over unexpected obstacles was reduced in Parkinson's patients compared to neurotypical participants, indicating impaired proactive cognitive control of walking that updates the online action plan when unexpected changes occur in the environment. Impaired action planning processes were further evident in Parkinson's disease patients' diminished beta power suppression when preparing motor adaptation to step over obstacles, regardless of the expectation manipulation, compared to when walking freely. In addition, deficits in reactive control mechanisms in Parkinson's disease compared to neurotypical participants were evident from an attenuated beta rebound signal after crossing an obstacle. Reduced modulation in the theta frequency band in the resetting phase across conditions also suggests a deficit in the evaluation of action outcomes in Parkinson's disease. Taken together, the neural markers of cognitive control of walking observed in Parkinson's disease reveal a pervasive deficit of motor-cognitive control, involving impairments in the proactive and reactive strategies used to avoid obstacles while walking. As such, this study identified neural markers of the motor deficits in Parkinson's disease and revealed patients' difficulties in adapting movements both before and after avoiding obstacles in their path.