Search

Freezing of gait (FOG) in Parkinson’s disease (PD) has a poorly understood pathophysiology, which hinders treatment development. Recent work showed a dysfunctional fronto-striato-limbic circuitry at rest in PD freezers compared to non-freezers in the dopamine “OFF” state. While other studies found that dopaminergic replacement therapy alters functional brain organization in PD, the specific effect of dopamine medication on fronto-striato-limbic functional connectivity in freezers remains unclear.

Background: Freezing of gait is one of the most disturbing motor symptoms of Parkinson's disease (PD). However, the effective connectivity between key brain hubs that are associated with the pathophysiological mechanism of freezing of gait remains elusive., Objective: The aim of this study was to identify effective connectivity underlying freezing of gait., Methods: This study applied spectral dynamic causal modeling (DCM) of resting-state functional magnetic resonance imaging in dedicated regions of interest determined using a data-driven approach., Results: Abnormally increased functional connectivity between the bilateral dorsolateral prefrontal cortex (DLPFC) and the bilateral mesencephalic locomotor region (MLR) was identified in freezers compared with nonfreezers. Subsequently, spectral DCM analysis revealed that increased top-down excitatory effective connectivity from the left DLPFC to bilateral MLR and an independent self-inhibitory connectivity within the left DLPFC in freezers versus nonfreezers (>99% posterior probability) were inversely associated with the severity of freezing of gait. The lateralization of these effective connectivity patterns was not attributable to the initial dopaminergic deficit nor to structural changes in these regions., Conclusions: We have identified novel effective connectivity and an independent self-inhibitory connectivity underlying freezing of gait. Our findings imply that modulating the effective connectivity between the left DLPFC and MLR through neurostimulation or other interventions could be a target for reducing freezing of gait in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

The prediction of motor learning in Parkinson's disease (PD) is vastly understudied. Here, we investigated which clinical and neural factors predict better long-term gains after an intensive 6-week motor learning program to ameliorate micrographia. We computed a composite score of learning through principal component analysis, reflecting better writing accuracy on a tablet in single and dual task conditions. Three endpoints were studied-acquisition (pre- to post-training), retention (post-training to 6-week follow-up), and overall learning (acquisition plus retention). Baseline writing, clinical characteristics, as well as resting-state network segregation were used as predictors. We included 28 patients with PD (13 freezers and 15 non-freezers), with an average disease duration of 7 (±3.9) years. We found that worse baseline writing accuracy predicted larger gains for acquisition and overall learning. After correcting for baseline writing accuracy, we found female sex to predict better acquisition, and shorter disease duration to help retention. Additionally, absence of FOG, less severe motor symptoms, female sex, better unimanual dexterity, and better sensorimotor network segregation impacted overall learning positively. Importantly, three factors were retained in a multivariable model predicting overall learning, namely baseline accuracy, female sex, and sensorimotor network segregation. Besides the room to improve and female sex, sensorimotor network segregation seems to be a valuable measure to predict long-term motor learning potential in PD., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Background: Freezing of gait (FOG) is an episodic and highly disabling symptom of Parkinson's Disease (PD). Traditionally, FOG assessment relies on time-consuming visual inspection of camera footage. Therefore, previous studies have proposed portable and automated solutions to annotate FOG. However, automated FOG assessment is challenging due to gait variability caused by medication effects and varying FOG-provoking tasks. Moreover, whether automated approaches can differentiate FOG from typical everyday movements, such as volitional stops, remains to be determined. To address these questions, we evaluated an automated FOG assessment model with deep learning (DL) based on inertial measurement units (IMUs). We assessed its performance trained on all standardized FOG-provoking tasks and medication states, as well as on specific tasks and medication states. Furthermore, we examined the effect of adding stopping periods on FOG detection performance., Methods: Twelve PD patients with self-reported FOG (mean age 69.33 ± 6.02 years) completed a FOG-provoking protocol, including timed-up-and-go and 360-degree turning-in-place tasks in On/Off dopaminergic medication states with/without volitional stopping. IMUs were attached to the pelvis and both sides of the tibia and talus. A temporal convolutional network (TCN) was used to detect FOG episodes. FOG severity was quantified by the percentage of time frozen (%TF) and the number of freezing episodes (#FOG). The agreement between the model-generated outcomes and the gold standard experts' video annotation was assessed by the intra-class correlation coefficient (ICC)., Results: For FOG assessment in trials without stopping, the agreement of our model was strong (ICC (%TF) = 0.92 [0.68, 0.98]; ICC(#FOG) = 0.95 [0.72, 0.99]). Models trained on a specific FOG-provoking task could not generalize to unseen tasks, while models trained on a specific medication state could generalize to unseen states. For assessment in trials with stopping, the agreement of our model was moderately strong (ICC (%TF) = 0.95 [0.73, 0.99]; ICC (#FOG) = 0.79 [0.46, 0.94]), but only when stopping was included in the training data., Conclusion: A TCN trained on IMU signals allows valid FOG assessment in trials with/without stops containing different medication states and FOG-provoking tasks. These results are encouraging and enable future work investigating automated FOG assessment during everyday life., (© 2024. The Author(s).)

Freezing of gait (FOG) is an episodic and highly disabling symptom of Parkinson's disease (PD). Although described as a single phenomenon, FOG is heterogeneous and can express as different manifestations, such as trembling in place or complete akinesia. We aimed to analyze the efficacy of deep learning (DL) trained on inertial measurement unit data to classify FOG into both manifestations. We adapted and compared four state-of-the-art FOG detection algorithms for this task and investigated the advantages of incorporating a refinement model to address oversegmentation errors. We evaluated the model's performance in distinguishing between trembling and akinesia, as well as other forms of movement cessation (e.g., stopping and sitting), against gold-standard video annotations. Experiments were conducted on a dataset of eighteen PD patients completing a FOG-provoking protocol in a gait laboratory. Results showed our model achieved an F1 score of 0.78 and segment F1@50 of 0.75 in detecting FOG manifestations. Assessment of FOG severity was strong for trembling (ICC=0.86, [0.66,0.95]) and moderately strong for akinesia (ICC=0.78, [0.51,0.91]). Importantly, our model successfully differentiated FOG from other forms of movement cessation during 360-degree turning-in-place tasks. In conclusion, our study demonstrates that DL can accurately assess different types of FOG manifestations, warranting further investigation in larger and more diverse verification cohorts.

Background: Measurement of freezing of gait (FOG) relies on the sensitivity and reliability of tasks to provoke FOG. It is currently unclear which tasks provide the best outcomes and how medication state plays into this., Objective: To establish the sensitivity and test-retest reliability of various FOG-provoking tasks for presence and severity of FOG, with (ON) and without (OFF) dopaminergic medication., Methods: FOG-presence and percentage time frozen (% TF) were derived from video annotations of a home-based FOG-provoking protocol performed in OFF and ON. This included: the four meter walk (4MW), Timed Up and Go (TUG) single (ST) and dual task (DT), 360° turns in ST and DT, a doorway condition, and a personalized condition. Sensitivity was tested at baseline in 63 definite freezers. Test-retest reliability was evaluated over 5 weeks in 26 freezers., Results: Sensitivity and test-retest reliability were highest for 360° turns and higher in OFF than ON. Test-retest intra-class correlation coefficients of % TF varied between 0.63-0.90 in OFF and 0.18-0.87 in ON, and minimal detectable changes (MDCs) were high. The optimal protocol included TUG ST, 360° turns ST, 360° turns DT and a doorway condition, provoking FOG in all freezers in OFF and 91.9% in ON and this could be done reliably in 95.8% (OFF) and 84.0% (ON) of the sample. Combining OFF and ON further improved outcomes., Conclusions: The highest sensitivity and reliability was achieved with a multi-trigger protocol performed in OFF + ON. However, the high MDCs for % TF underscore the need for further optimization of FOG measurement.

Older adults with and without Parkinson's disease show impaired retention after training of motor or cognitive skills. This systematic review with meta-analysis aims to investigate whether adding transcranial direct current stimulation (tDCS) to motor or cognitive training versus placebo boosts motor sequence and working memory training. The effects of interest were estimated between three time points, i.e. pre-training, post-training and follow-up. This review was conducted according to the PRISMA guidelines (PROSPERO: CRD42022348885). Electronic databases were searched from conception to March 2023. Following initial screening, 24 studies were eligible for inclusion in the qualitative synthesis and 20 could be included in the meta-analysis, of which 5 studies concerned motor sequence learning (total n = 186) and 15 working memory training (total n = 650). Results were pooled using an inverse variance random effects meta-analysis. The findings showed no statistically significant additional effects of tDCS over placebo on motor sequence learning outcomes. However, there was a strong trend showing that tDCS boosted working memory training, although methodological limitations and some heterogeneity were also apparent. In conclusion, the present findings do not support wide implementation of tDCS as an add-on to motor sequence training at the moment, but the promising results on cognitive training warrant further investigations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Gait freezing is a common, disabling symptom of Parkinson's disease characterized by sudden motor arrest during walking. Adaptive deep brain stimulation devices that detect freezing and deliver real-time, symptom-specific stimulation are a potential treatment strategy. Real-time alterations in subthalamic nucleus firing patterns have been demonstrated with lower limb freezing, however, whether similar abnormal signatures occur with freezing provoked by cognitive load, is unknown., Methods: We obtained subthalamic nucleus microelectrode recordings from eight Parkinson's disease patients performing a validated virtual reality gait task, requiring responses to on-screen cognitive cues while maintaining motor output., Results: Signal analysis during 15 trials containing freezing or significant motor output slowing precipitated by dual-tasking demonstrated reduced θ frequency (3-8 Hz) firing compared to 18 unaffected trials., Conclusions: These preliminary results reveal a potential neurobiological basis for the interplay between cognitive factors and gait disturbances including freezing in Parkinson's disease, informing development of adaptive deep brain stimulation protocols. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

Maintaining physical activity is an important clinical goal for people with Parkinson's disease (PwPD). We investigated the validity of two commercial activity trackers (ATs) to measure daily step counts. We compared a wrist- and a hip-worn commercial AT against the research-grade Dynaport Movemonitor (DAM) during 14 days of daily use. Criterion validity was assessed in 28 PwPD and 30 healthy controls (HCs) by a 2 × 3 ANOVA and intraclass correlation coefficients (ICC 2,1 ). The ability to measure daily step fluctuations compared to the DAM was studied by a 2 × 3 ANOVA and Kendall correlations. We also explored compliance and user-friendliness. Both the ATs and the DAM measured significantly fewer steps/day in PwPD compared to HCs ( p < 0.01). Step counts derived from the ATs showed good to excellent agreement with the DAM in both groups (ICC 2,1 > 0.83). Daily fluctuations were detected adequately by the ATs, showing moderate associations with DAM-rankings. While compliance was high overall, 22% of PwPD were disinclined to use the ATs after the study. Overall, we conclude that the ATs had sufficient agreement with the DAM for the purpose of promoting physical activity in mildly affected PwPD. However, further validation is needed before clinical use can be widely recommended.

Significance: Functional near-infrared spectroscopy (fNIRS) is increasingly employed in studies requiring repeated measurements, yet test-retest reliability is largely unknown., Aim: To investigate test-retest reliability during a postural and a finger-tapping task with and without cap-removal., Approach: Twenty healthy older adults performed a postural and a finger-tapping task. The tasks were repeated twice in one session and once the next day. A portable fNIRS system measured cortical hemodynamics ( HbO 2 ) in five regions of interest for the postural task and in the hand motor region for finger-tapping., Results: Test-retest reliability without cap-removal was excellent for the prefrontal cortex (PFC), the premotor cortex (PMC) and the somatosensory cortex (SSC) (intraclass correlation coefficient ( ICC ) ≥ 0.78 ), and fair for the frontal eye fields (FEF) and the supplementary motor area (SMA) ( ICC ≥ 0.48 ). After cap-removal, reliability reduced for PFC and SSC ( ICC ≥ 0.50 ), became poor for SMA ( ICC = 0.01 ) and PMC ( ICC = 0.00 ) and remained good for FEF ( ICC = 0.64 ). Similarly, good reliability ( ICC = 0.66 ) was apparent for the hand motor region without cap-removal, which deteriorated after cap-removal ( ICC = 0.38 )., Conclusions: Test-retest reliability of fNIRS measurements during two separate motor tasks in healthy older adults was fair to excellent when the cap remained in place. However, removing the fNIRS cap between measurements compromised reliability., (© 2023 The Authors.)

Rapid Eye Movement sleep behavior disorder (RBD) is a parasomnia causing sufferers to physically act out their dreams. These behaviors can disrupt sleep and sometimes lead to injuries in patients and their bed-partners. Clonazepam and melatonin are the first-line pharmacological treatment options for RBD based on direct uncontrolled clinical observations and very limited double-blind placebo-controlled trials. Given the risk for adverse outcomes, especially in older adults, it is of great importance to assess the existing level of evidence for the use of these treatments. In this update, we therefore critically review the clinical and scientific evidence on the pharmacological management of RBD in people aged over 50. We focus on the first-line treatments, and provide an overview of all other alternative pharmacological agents trialed for RBD we could locate as supplementary materials. By amalgamating all clinical observations, our update shows that 66.7% of 1,026 RBD patients reported improvements from clonazepam and 32.9% of 137 RBD patients reported improvements from melatonin treatment on various outcome measures in published accounts. Recently, however, three relatively small randomized placebo-controlled trials did not find these agents to be superior to placebo. Given clonazepam and melatonin are clinically assumed to majorly modify or eliminate RBD in nearly all patients-there is an urgent need to test whether this magnitude of treatment effect remains intact in larger placebo-controlled trials., (© 2021. The Author(s).)

Freezing of gait (FOG) in Parkinson's disease (PD) causes severe patient burden despite pharmacological management. Exercise and training are therefore advocated as important adjunct therapies. In this meta-analysis, we assess the existing evidence for such interventions to reduce FOG, and further examine which type of training helps the restoration of gait function in particular. The primary meta-analysis across 41 studies and 1838 patients revealed a favorable moderate effect size (ES = -0.37) of various training modalities for reducing subjective FOG-severity (p < 0.00001), though several interventions were not directly aimed at FOG and some included non-freezers. However, exercise and training also proved beneficial in a secondary analysis on freezers only (ES = -0.32, p = 0.007). We further revealed that dedicated training aimed at reducing FOG episodes (ES = -0.24) or ameliorating the underlying correlates of FOG (ES = -0.40) was moderately effective (p < 0.01), while generic exercises were not (ES = -0.14, p = 0.12). Relevantly, no retention effects were seen after cessation of training (ES = -0.08, p = 0.36). This review thereby supports the implementation of targeted training as a treatment for FOG with the need for long-term engagement., (© 2021. The Author(s).)

The onset of freezing of gait (FOG) in Parkinson's disease (PD) is a critical milestone, marked by a higher risk of falls and reduced quality of life. FOG is associated with alterations in subcortical neural circuits, yet no study has assessed whether subcortical morphology can predict the onset of clinical FOG. In this prospective multimodal neuroimaging cohort study, we performed vertex-based analysis of grey matter morphology in fifty-seven individuals with PD at study entry and two years later. We also explored the behavioral correlates and resting-state functional connectivity related to these local volume differences. At study entry, we found that freezers (N = 12) and persons who developed FOG during the course of the study (converters) (N = 9) showed local inflations in bilateral thalamus in contrast to persons who did not (non-converters) (N = 36). Longitudinally, converters (N = 7) also showed local inflation in the left thalamus, as compared to non-converters (N = 36). A model including sex, daily levodopa equivalent dose, and local thalamic inflation predicted conversion with good accuracy (AUC: 0.87, sensitivity: 88.9%, specificity: 77.8%). Exploratory analyses showed that local thalamic inflations were associated with larger medial thalamic sub-nuclei volumes and better cognitive performance. Resting-state analyses further revealed that converters had stronger thalamo-cortical coupling with limbic and cognitive regions pre-conversion, with a marked reduction in coupling over the two years. Finally, validation using the PPMI cohort suggested FOG-specific non-linear evolution of thalamic local volume. These findings provide markers of, and deeper insights into conversion to FOG, which may foster earlier intervention and better mobility for persons with PD.

Mobility is severely impacted in patients with Parkinson's disease (PD), who often experience involuntary stopping from the freezing of gait (FOG). Understanding the neurophysiological difference between "voluntary stopping" and "involuntary stopping" caused by FOG is vital for the detection of and potential intervention for FOG in the daily lives of patients. This study characterised the electroencephalographic (EEG) signature associated with FOG in contrast to voluntary stopping. The protocol consisted of a timed up-and-go (TUG) task and an additional TUG task with a voluntary stopping component, where participants reacted to verbal "stop" and "walk" instructions by voluntarily stopping or walking. Event-related spectral perturbation (ERSP) analysis was performed to study the dynamics of the EEG spectra induced by different walking phases, including normal walking, voluntary stopping and episodes of involuntary stopping (FOG), as well as the transition windows between normal walking and voluntary stopping or FOG. These results demonstrate for the first time that the EEG signal during the transition from walking to voluntary stopping is distinguishable from that during the transition to involuntary stopping caused by FOG. The EEG signature of voluntary stopping exhibits a significantly decreased power spectrum compared with that of FOG episodes, with distinctly different patterns in the delta and low-beta power in the central area. These findings suggest the possibility of a practical EEG-based tool that can accurately predict FOG episodes, excluding the potential confounding of voluntary stopping.

Background: People with Parkinson's disease and freezing of gait (FOG; freezers) suffer from pronounced postural instability. However, the relationship between these phenomena remains unclear and has mostly been tested in paradigms requiring step generation., Objective: To determine if freezing-related dynamic balance deficits are present during a task without stepping and determine the influence of dopaminergic medication on dynamic balance control., Methods: Twenty-two freezers, 16 non-freezers, and 20 healthy age-matched controls performed mediolateral weight-shifts at increasing frequencies when following a visual target projected on a screen (MELBA task). The amplitude and phase shift differences between center of mass and target motion were measured. Balance scores (Mini-BESTest), 360° turning speed and the freezing ratio were also measured. Subjects with Parkinson's disease were tested ON and partial OFF (overnight withdrawal) dopaminergic medication., Results: Freezers had comparable turning speed and balance scores to non-freezers and took more levodopa. Freezers produced hypokinetic weight-shift amplitudes throughout the MELBA task compared to non-freezers (p = 0.002), which were already present at task onset (p < 0.001). Freezers also displayed an earlier weight-shift breakdown than controls when OFF-medication (p = 0.008). Medication improved mediolateral weight-shifting in freezers and non-freezers. Freezers decreased their freezing ratio in response to medication., Conclusion: Hypokinetic weight-shifting proved a marked postural control deficit in freezers, while balance scores and turning speed were similar to non-freezers. Both weight-shift amplitudes and the freezing ratio were responsive to medication in freezers, suggesting axial motor vigor is levodopa-responsive. Future work needs to test whether weight-shifting and freezing severity can be further ameliorated through training.

Virtual reality (VR) technology has emerged as a promising tool for studying and rehabilitating gait and balance impairments in people with Parkinson disease (PD) as it allows users to be engaged in an enriched and highly individualized complex environment. This Review examines the rationale and evidence for using VR in the assessment and rehabilitation of people with PD, makes recommendations for future research and discusses the use of VR in the clinic. In the assessment of people with PD, VR has been used to manipulate environments to enhance study of the behavioural and neural underpinnings of gait and balance, improving understanding of the motor-cognitive neural circuitry involved. Despite suggestions that VR can provide rehabilitation that is more effective and less labour intensive than non-VR rehabilitation, little evidence exists to date to support these claims. Nevertheless, much unrealized potential exists for the use of VR to provide personalized assessment and rehabilitation that optimizes motor learning in both the clinic and home environments and adapts to changes in individuals over time. Design of such systems will require collaboration between all stakeholders to maximize useability, engagement, safety and effectiveness.

Postural instability is a strong risk factor for falls that becomes more prominent with aging. To facilitate treatment and prevention of falls in an aging society, a thorough understanding of the neural networks underlying postural control is warranted. Here, we present a systematic review of the functional neuroimaging literature of studies measuring posture-related neural activity in healthy subjects. Study methods were overall heterogeneous. Eleven out of the 14 studies relied on postural simulation in a supine position (e.g. motor imagery). The key nodes of human postural control involved the brainstem, cerebellum, basal ganglia, thalamus and several cortical regions. An activation likelihood estimation meta-analysis revealed that the anterior cerebellum was consistently activated across the wide range of postural tasks. The cerebellum is known to modulate the brainstem nuclei involved in the control of posture. Hence, this systematic review with meta-analysis provides insight into the neural correlates which underpin human postural control and which may serve as a reference for future neural network and region of interest analyses., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Melatonin may reduce REM-sleep behavior disorder (RBD) symptoms in Parkinson's disease (PD), though robust clinical trials are lacking., Objective: To assess the efficacy of prolonged-release (PR) melatonin for RBD in PD., Methods: Randomized, double-blind, placebo-controlled, parallel-group trial with an 8-week intervention and 4-week observation pre- and postintervention (ACTRN12613000648729). Thirty PD patients with rapid eye movement sleep behavior disorder were randomized to 4 mg of prolonged-release melatonin (Circadin) or matched placebo, ingested orally once-daily before bedtime. Primary outcome was the aggregate of rapid eye movement sleep behavior disorder incidents averaged over weeks 5 to 8 of treatment captured by a weekly diary. Data were included in a mixed-model analysis of variance (n = 15 per group)., Results: No differences between groups at the primary endpoint (3.4 events/week melatonin vs. 3.6 placebo; difference, 0.2; 95% confidence interval = -3.2 to 3.6; P = 0.92). Adverse events included mild headaches, fatigue, and morning sleepiness (n = 4 melatonin; n = 5 placebo)., Conclusion: Prolonged-release melatonin 4 mg did not reduce rapid eye movement sleep behavior disorder in PD. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society., (© 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.)