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BackgroundFreezing 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.MethodsTwelve PD patients with self-reported FOG (mean age 69.33 ± 6.28 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 multi-stage temporal convolutional network was developed 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).ResultsFor 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 model trained on stopping trials made fewer false positives than the model trained without stopping (ICC(%TF) = 0.95 [0.73, 0.99]; ICC(#FOG) = 0.79 [0.46, 0.94]).ConclusionA DL model 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.

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. ispartof: IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING vol:29 pages:1774-1783 ispartof: location:United States status: published

ispartof: LANCET NEUROLOGY vol:20 issue:7 pages:505-505 ispartof: location:England status: published

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. ispartof: MOVEMENT DISORDERS vol:35 issue:2 pages:344-349 ispartof: location:United States status: published

Freezing of gait (FOG) in Parkinson's disease (PD) is frequently triggered upon passing through narrow spaces such as doorways. However, despite being common the neural mechanisms underlying this phenomenon are poorly understood. In our study, 19 patients who routinely experience FOG performed a previously validated virtual reality (VR) gait paradigm where they used foot-pedals to navigate a series of doorways. Patients underwent testing randomised between both their "ON" and "OFF" medication states. Task performance in conjunction with blood oxygenation level dependent (BOLD) signal changes between "ON" and "OFF" states were compared within each patient. Specifically, as they passed through a doorway in the VR environment patients demonstrated significantly longer "footstep" latencies in the OFF state compared to the ON state. As seen clinically in FOG this locomotive delay was primarily triggered by narrow doorways rather than wide doorways. Functional magnetic resonance imaging revealed that footstep prolongation on passing through doorways was associated with selective hypoactivation in the presupplementary motor area (pSMA) bilaterally. Task-based functional connectivity analyses revealed that increased latency in response to doorways was inversely correlated with the degree of functional connectivity between the pSMA and the subthalamic nucleus (STN) across both hemispheres. Furthermore, increased frequency of prolonged footstep latency was associated with increased connectivity between the bilateral STN. These findings suggest that the effect of environmental cues on triggering FOG reflects a degree of impaired processing within the pSMA and disrupted signalling between the pSMA and STN, thus implicating the "hyperdirect" pathway in the generation of this phenomenon. ispartof: HUMAN BRAIN MAPPING vol:40 issue:7 pages:2055-2064 ispartof: location:United States status: published

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.

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 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 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.

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

Thousands of resting state functional magnetic resonance imaging (RS-fMRI) articles have been published on brain disorders. For precise localization of abnormal brain activity, a voxel-level comparison is needed. Because of the large number of voxels in the brain, multiple comparison correction (MCC) must be performed to reduce false positive rates, and a smaller P value (usually including either liberal or stringent MCC) is widely recommended. The study suggests that a stringent MCC may reduce the number of false positive results and that the brain regions surviving MCC are true positive results and thus can improve the reproducibility between studies. However, determining the clusters that represent true positives is difficult because ground truths have not been established for many brain disorders that do not present visible structural abnormalities, e.g., Parkinson's disease (PD) and many psychiatric disorders. Meta-analysis provides robust results that can be used to investigate reproducibility across studies. However, most existing neuroimaging meta-analytic articles are based on only a few peak coordinates reported in the original articles, namely coordinate-based meta-analysis (CB-meta). The current REST-meta-PD study included raw RS-fMRI data from 15 cohorts of PD patients and performed a meta-analysis of the amplitude of low frequency fluctuations (ALFF). We used the robustness results of the meta-analysis to test whether liberal or stringent MCC could increase reproducibility and reduce false positive rates.

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. Supplementary Information The online version of this article (10.1007/s00415-020-10353-0) contains supplementary material, which is available to authorized users.

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. ispartof: NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS vol:115 pages:351-362 ispartof: location:United States status: published

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.

Background The purpose of this study is to identify and characterize subtypes of freezing of gait by using a novel questionnaire designed to delineate freezing patterns based on self-reported and behavioral gait assessment. Methods A total of 41 Parkinson's patients with freezing completed the Characterizing Freezing of Gait questionnaire that identifies situations that exacerbate freezing. This instrument underwent examination for construct validity and internal consistency, after which a data-driven clustering approach was employed to identify distinct patterns amongst individual responses. Behavioral freezing assessments in both dopaminergic states were compared across 3 identified subgroups. Results This novel questionnaire demonstrated construct validity (severity scores correlated with percentage of time frozen; r = 0.54) and internal consistency (Cronbach's α = .937), and thus demonstrated promising utility for identifying patterns of freezing that are independently related to motor, anxiety, and attentional impairments. Conclusions Patients with freezing may be dissociable based on underlying neurobiological underpinnings that would have significant implications for targeting future treatments. © 2018 International Parkinson and Movement Disorder Society.

Freezing of gait is a complex, heterogeneous, and highly variable phenomenon whose pathophysiology and neural signature remains enigmatic. Evidence suggests that freezing is associated with impairments across cognitive, motor and affective domains; however, most research to date has focused on investigating one axis of freezing of gait in isolation. This has led to inconsistent findings and a range of different pathophysiological models of freezing of gait, due in large part to the tendency for studies to investigate freezing of gait as a homogeneous entity. To investigate the neural mechanisms of this heterogeneity, we used an established virtual reality paradigm to elicit freezing behaviour in 41 Parkinson's disease patients with freezing of gait and examined individual differences in the component processes (i.e. cognitive, motor and affective function) that underlie freezing of gait in conjunction with task-based functional MRI. First, we combined three unique components of the freezing phenotype: impaired set-shifting ability, step time variability, and self-reported anxiety and depression in a principal components analysis to estimate the severity of freezing behaviour with a multivariate approach. By combining these measures, we were then able to interrogate the pattern of task-based functional connectivity associated with freezing (compared to normal foot tapping) in a sub-cohort of 20 participants who experienced sufficient amounts of freezing during task functional MRI. Specifically, we used the first principal component from our behavioural analysis to classify patterns of functional connectivity into those that were associated with: (i) increased severity; (ii) increased compensation; or (iii) those that were independent of freezing severity. Coupling between the cognitive and limbic networks was associated with 'worse freezing severity', whereas anti-coupling between the putamen and the cognitive and limbic networks was related to 'increased compensation'. Additionally, anti-coupling between cognitive cortical regions and the caudate nucleus were 'independent of freezing severity' and thus may represent common neural underpinnings of freezing that are unaffected by heterogenous factors. Finally, we related these connectivity patterns to each of the individual components (cognitive, motor, affective) in turn, thus exposing latent heterogeneity in the freezing phenotype, while also identifying critical functional network signatures that may represent potential targets for novel therapeutic intervention. In conclusion, our findings provide confirmatory evidence for systems-level impairments in the pathophysiology of freezing of gait and further advance our understanding of the whole-brain deficits that mediate symptom expression in Parkinson's disease.

Freezing of gait (FOG) is a poorly understood symptom affecting many patients with Parkinson's disease (PD). Despite growing evidence of a behavioral link between anxiety, attention and FOG in PD, no research to date has investigated the neural mechanisms that might explain this relationship. The present study therefore examined resting-state MRI functional connectivity between the amygdala, striatum and frontoparietal attentional control network in PD patients with (freezers: n = 19) and without FOG (non-freezers: n = 21) in the dopaminergic 'off' state. Functional connectivity was subsequently correlated with an objective measure of FOG severity and a subjective scale of affective disorder within each group. Connectivity between the right amygdala and right putamen was significantly increased in freezers compared to non-freezers (p 0.01). Furthermore, freezers showed increased anti-coupling between the frontoparietal network and left amygdala (p = 0.011), but reduced anti-coupling between this network and the right putamen (p = 0.027) as compared to non-freezers. Key functional connections between the amygdala, putamen and frontoparietal network were significantly associated with FOG severity and a fear of falling. This study provides the first evidence that dysfunctional fronto-striato-limbic processes may underpin the link between anxiety and FOG in PD. It is proposed that freezers have heightened striato-limbic load and reduced top-down attentional control at rest, which when further challenged by the parallel processing demands of walking may precipitate FOG.

Freezing of gait is a disabling symptom of Parkinson's disease that ultimately affects approximately 80% of patients, yet very little research has focused on predicting the onset of freezing of gait and tracking the longitudinal progression of symptoms prior to its onset. The objective of the current study was to examine longitudinal data spanning the transition period when patients with PD developed freezing of gait to identify symptoms that may precede freezing and create a prediction model that identifies those "at risk" for developing freezing of gait in the year to follow. Two hundred and twenty-one patients with PD were divided into 3 groups (88 nonfreezers, 41 transitional freezers, and 92 continuing freezers) based on their responses to the validated Freezing of Gait-Questionnaire item 3 at baseline and follow-up. Critical measures across motor, cognitive, mood, and sleep domains were assessed at 2 times approximately 1 year apart. A logistic regression model that included age, disease duration, gait symptoms, motor phenotype, attentional set-shifting, and mood measures could predict with 70% and 90% accuracy those patients who would and would not develop, respectively, freezing of gait over the next year. Notably, the Freezing of Gait-Questionnaire total and the anxiety section of the Hospital Anxiety and Depression Scale were the strongest predictors and alone could significantly predict if one might develop freezing of gait in the next 15 months with 82% accuracy. Our results suggest that it is possible to identify the majority of patients who will develop freezing of gait in the following year, potentially allowing targeted interventions to delay or possibly even prevent the onset of freezing. © 2017 International Parkinson and Movement Disorder Society.

Parkinson's disease (PD) is frequently accompanied by cognitive and neuropsychiatric symptoms including impairments in affective processing. Despite this, mechanisms underlying vulnerability to deficits in affective processing remain unclear. In this study, we utilized functional Magnetic Resonance Imaging (fMRI) and an Affective Go-NoGo paradigm, to examine the neural correlates of emotional valence processing in PD. Results suggest that PD is associated with aberrant processing of emotional valence in subcortical limbic structures. Specifically, we found significant group-by-valence interactions in the ventral striatum and amygdala in response to words of differing emotional valence. Our findings contribute to a broader understanding of affective processing in PD and may provide insights into the mechanisms underlying vulnerability to mood disorders in PD.

Visually scoring freezing of gait (FOG) from video is increasingly recognized as the gold-standard for assessing FOG severity in Parkinson's disease. Surprisingly, no guidelines exist on how to visually score FOG. Here, I present a free template that can be implemented in open-source software to annotate FOG from video. I provide a user guide on how to implement the template and standardize the scoring of FOG and the percentage of time spent with FOG (% FOG). It is hoped that by disseminating this method investigators will be better able to employ % FOG as an outcome in their studies and therapeutic trials. ispartof: JOURNAL OF PARKINSONS DISEASE vol:9 issue:4 pages:821-824 ispartof: location:Netherlands status: published

Gait freezing is a complex and devastating paroxysmal motor arrest commonly suffered in Parkinson's disease that causes significant impairment to mobility, commonly resulting in falls and subsequent injury. The neurobiological basis of gait freezing in Parkinson's disease is poorly understood and thus, currently available therapies are partially effective at best. We used a validated virtual reality gait paradigm to elicit freezing behaviour intraoperatively in eight patients undergoing subthalamic nucleus deep brain stimulation surgery while microelectrode recordings were obtained. This allowed us to directly test the hypothesis that increases in pathological multi-unit activity in the subthalamic nucleus are associated with freezing onset in real time, manifest as dysfunctional firing of lower limb muscles typical of freezing that were detected by EMG. We present evidence that freezing is related to transient increases in pathological subthalamic nucleus activity. We performed time-frequency analysis to characterize the oscillatory dynamics of subthalamic nucleus activity coincident with freezing onset, demonstrating an increase in pathological beta and theta rhythms that are followed by a temporal chain of activity culminating in characteristically abnormal lower limb muscle firing detected by EMG. Finally, we interrogate the potential clinical utility of our findings by contrasting the subthalamic nucleus activity signature during pathological freezing against purposeful stopping. These results advance our understanding of the neurobiological basis of gait freezing in Parkinson's disease, highlighting the role of the subthalamic nucleus and emergent synchronous activity in basal ganglia circuits in driving non-purposeful motor arrests in individuals with Parkinson's disease. Pathological subthalamic nucleus activity identified in association with freezing is discernible from that of volitional stopping, paving the way towards more effective therapeutics such as adaptive closed-loop deep brain stimulation protocols.

Purpose of review: Whilst gait impairment is a main cause for disability in Parkinson’s disease (PD), its neural control remains poorly understood. We performed a systematic review and meta-analysis of neuroimaging studies of surrogate features of gait in PD. Findings: Assessing the results from PET or SPECT scans after a period of actual walking as well as fMRI during mental imagery or Virtual Reality (VR) gait paradigms, we found a varying pattern of gait-related brain activity. Overall, a decrease in activation of the SMA during gait was found in PD compared to elderly controls. In addition, the meta-analysis showed that the most consistent gait-related activation was situated in the cerebellar locomotor region (CLR) in PD. Summary: Despite methodological heterogeneity, the combined neuroimaging studies of gait provide new insights into its neural control in PD, suggesting that CLR activation likely serves a compensatory role in locomotion. ispartof: Current Neurology And Neuroscience Reports vol:19 issue:8 pages:1-12 ispartof: location:United States status: published

Previous research has shown that anxiety in Parkinson's disease (PD) is associated with freezing of gait (FOG), and may even contribute to the underlying mechanism. However, limited research has investigated whether PD patients with FOG (PD+FOG) have higher anxiety levels when compared directly to non-freezing PD patients (PD-NF) and moreover, how anxiety might contribute to FOG. The current study evaluated whether: (i) PD+FOG have greater anxiety compared to PD-NF, and (ii) anxiety in PD is related to attentional set-shifting, in order to better understand how anxiety might be contributing to FOG. In addition, we explored whether anxiety levels differed between those PD patients with mild FOG (PD+MildFOG) compared to PD-NF. Four hundred and sixty-one patients with PD (231 PD-NF, 180 PD+FOG, 50 PD+MildFOG) were assessed using the Freezing of Gait Questionnaire item 3 (FOG-Q3), Hospital Anxiety and Depression Scale (HADS), Digit Span Test, Logical Memory Retention Test and Trail Making Tests. Compared to PD-NF, PD+FOG had significantly greater anxiety (p

Research on the implications of anxiety in Parkinson’s disease (PD) has been neglected despite its prevalence in nearly 50% of patients and its negative impact on quality of life. Previous reports have noted that neuropsychiatric symptoms impair cognitive performance in PD patients; however, to date, no study has directly compared PD patients with and without anxiety to examine the impact of anxiety on cognitive impairments in PD. This study compared cognitive performance across 50 PD participants with and without anxiety (17 PDA+; 33 PDA−), who underwent neurological and neuropsychological assessment. Group performance was compared across the following cognitive domains: simple attention/visuomotor processing speed, executive function (e.g., set-shifting), working memory, language, and memory/new verbal learning. Results showed that PDA+ performed significantly worse on the Digit Span forward and backward test and Part B of the Trail Making Task (TMT-B) compared to the PDA− group. There were no group differences in verbal fluency, logical memory, or TMT-A performance. In conclusion, anxiety in PD has a measurable impact on working memory and attentional set-shifting.

ispartof: CLINICAL NEUROPHYSIOLOGY vol:129 issue:11 pages:2448-2450 ispartof: location:Netherlands status: Published online

Freezing of gait (FOG) is a common symptom in advanced Parkinson's disease (PD). Despite current advances, the neural mechanisms underpinning this disturbance remain poorly understood. To this end, we investigated the structural organisation of the white matter connectome in PD freezers and PD non-freezers. We hypothesized that freezers would show an altered network architecture, which could hinder the effective information processing that characterizes the disorder. Twenty-six freezers and twenty-four well-matched non-freezers were included in this study. Using diffusion tensor imaging, we investigated the modularity and integration of the regional connectome by calculating the module degree z score and the participation coefficient, respectively. Compared to non-freezers, freezers demonstrated lower participation coefficients in the right caudate, thalamus, and hippocampus, as well as within superior frontal and parietal cortical regions. Importantly, several of these nodes were found within the brain's 'rich club'. Furthermore, group differences in module degree z scores within cortical frontal and sensory processing areas were found. Together, our results suggest that changes in the structural network topology contribute to the manifestation of FOG in PD, specifically due to a lack of structural integration between key information processing hubs of the brain. ispartof: JOURNAL OF NEUROLOGY vol:265 issue:6 pages:1353-1364 ispartof: location:Germany status: published

The pathophysiological mechanism of freezing of gait (FoG) has been linked to executive dysfunction. Cognitive training (CT) is a non-pharmacological intervention which has been shown to improve executive functioning in Parkinson’s disease (PD). This study aimed to explore whether targeted CT can reduce the severity of FoG in PD. Patients with PD who self-reported FoG and were free from dementia were randomly allocated to receive either a CT intervention or an active control. Both groups were clinician-facilitated and conducted twice-weekly for seven weeks. The primary outcome was percentage of time spent frozen during a Timed Up and Go task, assessed both on and off dopaminergic medications. Secondary outcomes included multiple neuropsychological and psychosocial measures. A full analysis was first conducted on all participants randomized, followed by a sample of interest including only those who had objective FoG at baseline, and completed the intervention. Sixty-five patients were randomized into the study. The sample of interest included 20 in the CT group and 18 in the active control group. The primary outcome of percentage time spent frozen during a gait task was significantly improved in the CT group compared to active controls in the on-state. There were no differences in the off-state. Patients who received CT also demonstrated improved processing speed and reduced daytime sleepiness compared to those in the active control. The findings suggest that CT can reduce the severity of FoG in the on-state, however replication in a larger sample is required., Freezing of gait: a non-pharmacological approach Cognitive training can reduce the severity of gait freezing in Parkinson’s disease (PD) patients on dopaminergic medication. The inability to move forwards despite the intention to walk is one of the most debilitating symptoms in patients with PD and has been linked to cognitive dysfunction. Simon Lewis at the University of Sydney, Australia, and colleagues examined the effects of cognitive training in patients with self-reported freezing of gait and without dementia. Patients receiving cognitive therapy twice a week for seven weeks showed a significant reduction in gait freezing compared to the control group. Interestingly, the effect was observed when patients had maximum benefit from their PD medication (on-state) but not in the off-state. Cognitive training also improved patients’ processing speed and reduced their daytime sleepiness highlighting the usefulness of non-pharmacological interventions in the treatment of PD.

Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric isorders together with healthy individuals have been analyzed. Parkinson’s disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named amplitude of low frequency fluctuation (ALFF) showed that the effect size (Hedges’ g) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t-maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.

Freezing of gait is a devastating symptom of Parkinson's disease and other forms of parkinsonism. It poses a major burden on both patients and their families, as freezing often leads to falls, fall-related injuries and a loss of independence. Treating freezing of gait is difficult for a variety of reasons: it has a paroxysmal and unpredictable nature; a multifaceted pathophysiology, with an interplay between motor elements (disturbed stepping mechanisms) and non-motor elements (cognitive decline, anxiety); and a complex (and likely heterogeneous) underlying neural substrate, involving multiple failing neural networks. In recent years, advances in translational neuroscience have offered new insights into the pathophysiology underlying freezing. Furthermore, the mechanisms behind the effectiveness of available treatments (or lack thereof) are better understood. Driven by these concepts, researchers and clinicians have begun to improve currently available treatment options, and develop new and better treatment methods. Here, we evaluate the range of pharmacological (i.e. closed-looped approaches), surgical (i.e. multi-target and adaptive deep brain and spinal cord stimulation) and behavioural (i.e. biofeedback and cueing on demand) treatment options that are under development, and propose novel avenues that are likely to play a crucial role in the clinical management of freezing of gait in the near future. The outcomes of this review suggest that the successful future management of freezing of gait will require individualized treatments that can be implemented in an on-demand manner in response to imminent freezing. With this review we hope to guide much-needed advances in treating this devastating symptom of Parkinson's disease. ispartof: Parkinsonism & Related Disorders vol:52 pages:7-16 ispartof: location:England status: accepted

Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson's disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.