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Dual-task gait can be a useful biomarker for cognitive decline and a sensitive predictor of future neurodegeneration in certain clinical populations, such as patients with idiopathic rapid eye movement sleep behavior disorder. Objectives The objective of this cross-sectional study was to determine the neural signature of dual-tasking deficits in idiopathic rapid eye movement sleep behavior disorder using a validated gait paradigm. Methods Fifty-eight participants (28 controls; 30 idiopathic rapid eye movement sleep behavior disorder patients) were recruited; 52 participants had functional MRI scans as they performed a validated dual-task virtual reality gait paradigm using foot pedals. Forty-one participants completed single- and dual-task "overground walking" on a pressure sensor carpet. Results Idiopathic rapid eye movement sleep behavior disorder patients showed deficits in dual-tasking (i.e., greater mean step time) compared to controls during "overground walking." Functional MRI revealed that idiopathic rapid eye movement sleep behavior disorder patients had reduced blood-oxygen-level-dependent signal change in the dorsal caudate nucleus, and significantly different corticostriatal functional connectivity patterns from controls, when dual-tasking in high versus low cognitive load. While controls showed greater connectivity between frontoparietal and motor networks, idiopathic rapid eye movement sleep behavior disorder patients exhibited less change in this connectivity as a function of cognitive load. Conclusions These findings demonstrate evidence of dual-task gait deficits in idiopathic rapid eye movement sleep behavior disorder patients, underpinned by disrupted corticostriatal connectivity. Minimal differences in the level of functional connectivity between dual-tasking conditions of high and low cognitive load suggest that idiopathic rapid eye movement sleep behavior disorder patients recruit cognitive networks to control gait even when the cognitive demands are low. This may indicate a compensatory strategy for early cognitive decline in idiopathic rapid eye movement sleep behavior disorder. © 2020 International Parkinson and Movement Disorder Society.

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

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 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.

Impairments in motor automaticity cause patients with Parkinson's disease to rely on attentional resources during gait, resulting in greater motor variability and a higher risk of falls. Although dopaminergic circuitry is known to play an important role in motor automaticity, little evidence exists on the neural mechanisms underlying the breakdown of locomotor automaticity in Parkinson's disease. This impedes clinical management and is in great part due to mobility restrictions that accompany the neuroimaging of gait. This study therefore utilized a virtual reality gait paradigm in conjunction with functional MRI to investigate the role of dopaminergic medication on lower limb motor automaticity in 23 patients with Parkinson's disease that were measured both on and off dopaminergic medication. Participants either operated foot pedals to navigate a corridor (‘walk’ condition) or watched the screen while a researcher operated the paradigm from outside the scanner (‘watch’ condition), a setting that controlled for the non-motor aspects of the task. Step time variability during walk was used as a surrogate measure for motor automaticity (where higher variability equates to reduced automaticity), and patients demonstrated a predicted increase in step time variability during the dopaminergic “off” state. During the “off” state, subjects showed an increased blood oxygen level-dependent response in the bilateral orbitofrontal cortices (walk>watch). To estimate step time variability, a parametric modulator was designed that allowed for the examination of brain regions associated with periods of decreased automaticity. This analysis showed that patients on dopaminergic medication recruited the cerebellum during periods of increasing variability, whereas patients off medication instead relied upon cortical regions implicated in cognitive control. Finally, a task-based functional connectivity analysis was conducted to examine the manner in which dopamine modulates large-scale network interactions during gait. A main effect of medication was found for functional connectivity within an attentional motor network and a significant condition by medication interaction for functional connectivity was found within the striatum. Furthermore, functional connectivity within the striatum correlated strongly with increasing step time variability during walk in the off state (r=0.616, p=0.002), but not in the on state (r=−0.233, p=0.284). Post-hoc analyses revealed that functional connectivity in the dopamine depleted state within an orbitofrontal-striatal limbic circuit was correlated with worse step time variability (r=0.653, p

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.

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

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.

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.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.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.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 (FOG) is a highly debilitating and poorly understood symptom of Parkinson's disease (PD), causing severe immobility and decreased quality of life. Turning Freezing (TF) is known as the most common sub-type of FOG, also causing the highest rate of falls in PD patients. During a TF, the feet of PD patients appear to become stuck whilst making a turn. This paper presents an electroencephalography (EEG) based classification method for detecting turning freezing episodes in six PD patients during Timed Up and Go Task experiments. Since EEG signals have a time-variant nature, time-frequency Stockwell Transform (S-Transform) techniques were used for feature extraction. The EEG sources were separated by means of independent component analysis using entropy bound minimization (ICA-EBM). The distinctive frequency-based features of selected independent components of EEG were extracted and classified using Bayesian Neural Networks. The classification demonstrated a high sensitivity of 84.2%, a specificity of 88.0% and an accuracy of 86.2% for detecting TF. These promising results pave the way for the development of a real-time device for detecting different sub-types of FOG during ambulation.

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.

Gait initiation Failure (GIF) is the situation in which patients with Parkinson's disease (PD) feel as if their feet get “stuck” to the floor when initiating their first steps. GIF is a subtype of Freezing of Gait (FOG) and often leads to falls and related injuries. Understanding of neurobiological mechanisms underlying GIF has been limited by difficulties in eliciting and objectively characterizing such gait phenomena in the clinical setting. Studies investigating the effects of GIF on brain activity using EEG offer the potential to study such behavior. In this preliminary study, we present a novel methodology where wavelet transform was used for feature extraction and Support Vector Machine for classifying GIF events in five patients with PD and FOG. To deal with the large amount of EEG data, a Principal Component Analysis (PCA) was applied to reduce the data dimension from 15 EEG channels into 6 principal components (PCs), retaining 93% of the information. Independent Component Analysis using Entropy Bound Minimization (ICA-EBM) was applied to 6 PCs for source separation with the aim of improving detection ability of GIF events as compared to the normal initiation of gait (Good Starts). The results of this analysis demonstrated the correct identification of GIF episodes with an 83.1% sensitivity, 89.5% specificity and 86.3% accuracy. These results suggest that our proposed methodology is a promising non-invasive approach to improve GIF detection in PD and FOG.

Freezing of gait (FOG) is a common, disabling symptom of Parkinson's disease (PD) that is associated with deficits in motor initiation and inhibition. Understanding of underlying neurobiological mechanisms has been limited by difficulties in eliciting and objectively characterizing such gait phenomena in the clinical setting. However, recent work suggests that virtual reality (VR) techniques might offer the potential to study motor control. This study utilized a VR paradigm to explore deficits in motor initiation and stopping performance, including stop failure in PD patients with (Freezers, 31) and without (Non-Freezers, 23) FOG, and healthy age-matched Controls (15). The VR task required subjects to respond to a series of start and stop cues while navigating a corridor using ankle flexion/extension movements on foot pedals. We found that Freezers experienced slower motor output initiation and more frequent start hesitations (SHs) (initiations greater than twice a subject's usual initiation latency) compared to Non-Freezers and Controls. Freezers also showed more marked inhibitory impairments, taking significantly longer to execute motor inhibition, and experiencing an increased frequency of failed stopping in response to stop cues compared to Non-Freezers and Controls. Stopping impairments were exacerbated by stop cues requiring additional cognitive processing. These results suggest that PD patients with FOG have marked impairments in motor initiation and inhibition that are not prominent in patients without FOG, nor healthy controls. Future work combining such VR paradigms with neuroimaging techniques and intra-operative deep brain recordings may increase our understanding of these phenomena, promoting the development of novel technologies and therapeutic approaches.