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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., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In the past decade, neurorehabilitation has been shown to be an effective therapeutic supplement for patients with Parkinson's disease (PD). However, patients still experience severe problems with the consolidation of learned motor skills. Knowledge on the neural correlates underlying this process is thus essential to optimize rehabilitation for PD. This review investigates the existing studies on neural network connectivity changes in relation to motor learning in healthy aging and PD and critically evaluates the imaging methods used from a methodological point of view. The results indicate that despite neurodegeneration there is still potential to modify connectivity within and between motor and cognitive networks in response to motor training, although these alterations largely bypass the most affected regions in PD. However, so far training-related changes are inferred and possible relationships are not substantiated by brain-behavior correlations. Furthermore, the studies included suffer from many methodological drawbacks. This review also highlights the potential for using neural network measures as predictors for the response to rehabilitation, mainly based on work in young healthy adults. We speculate that future approaches, including graph theory and multimodal neuroimaging, may be more sensitive than brain activation patterns and model-based connectivity maps to capture the effects of motor learning. Overall, this review suggests that methodological developments in neuroimaging will eventually provide more detailed knowledge on how neural networks are modified by training, thereby paving the way for optimized neurorehabilitation for patients.

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. 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.

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., (© 2019 Wiley Periodicals, Inc.)

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.

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., (© 2018 International Parkinson and Movement Disorder Society.)

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., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

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.

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., Competing Interests: The authors declare no competing interests.

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., (Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.)

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.

Background: 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., Methods: 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., Results: 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., Conclusions: 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., (© 2017 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.

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.

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<0.001). Overall, this study demonstrates that dopamine ameliorates gait automaticity in Parkinson's disease by altering striatal, limbic and cerebellar processing, thereby informing future therapeutic avenues for gait and falls prevention., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Experimental data show that perceptual cues can either exacerbate or ameliorate freezing of gait (FOG) in Parkinson's Disease (PD). For example, simple visual stimuli like stripes on the floor can alleviate freezing whereas complex stimuli like narrow doorways can trigger it. We present a computational model of the cognitive and motor cortico-basal ganglia loops that explains the effects of sensory and cognitive processes on FOG. The model simulates strong causative factors of FOG including decision conflict (a disagreement of various sensory stimuli in their association with a response) and cognitive load (complexity of coupling a stimulus with downstream mechanisms that control gait execution). Specifically, the model simulates gait of PD patients (freezers and non-freezers) as they navigate a series of doorways while simultaneously responding to several Stroop word cues in a virtual reality setup. The model is based on an actor-critic architecture of Reinforcement Learning involving Utility-based decision making, where Utility is a weighted sum of Value and Risk functions. The model accounts for the following experimental data: (a) the increased foot-step latency seen in relation to high conflict cues, (b) the high number of motor arrests seen in PD freezers when faced with a complex cue compared to the simple cue, and (c) the effect of dopamine medication on these motor arrests. The freezing behavior arises as a result of addition of task parameters (doorways and cues) and not due to inherent differences in the subject group. The model predicts a differential role of risk sensitivity in PD freezers and non-freezers in the cognitive and motor loops. Additionally this first-of-its-kind model provides a plausible framework for understanding the influence of cognition on automatic motor actions in controls and Parkinson's Disease.

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., (Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.)

Our research team has previously used four Electroencephalography (EEG) leads to successfully detect and predict Freezing of Gait (FOG) in Parkinson's disease (PD). However, it remained to be determined whether these four sensor locations that were arbitrarily chosen based on their role in motor control are indeed the most optimal for FOG detection. The aim of this study was therefore to determine the most optimal location and combination of sensors to detect FOG amongst a 32-channel EEG montage using our EEG classification system. EEG measures, including power spectral density, centroid frequency and power spectral entropy, were extracted from 7 patients with PD and FOG during a series of Timed up and Go tasks. By applying a feed-forward neural networks to classify EEG data, the obtained results showed that even a small number of electrodes suffice to construct a FOG detector with expected performance, which is comparable to the use of a full 32 channels montage. This finding therefore progresses the realization of a FOG detection system that can be effectively implemented on a daily basis for FOG prevention, improving the quality of life for many patients with PD.

Gait Initiation Failure (GIF) is one of the most disabling gait disturbances seen in advanced Parkinson's disease (PD). Gait Initiation is a complex motor task that requires motor and cognitive processing to enable the correct selection, timing and scaling of movement. Failure to initiate the first step often precipitates falls and leads to significant morbidity. However, the brain mechanisms underlying GIF remain unknown. This study utilized an ambulatory electroencephalography (EEG) technique to investigate the brain dynamic changes underlying GIF and aims to detect the occurrence of GIF in four PD patients. We sought to determine whether episodes of GIF might be associated with a characteristic brain signal that could be detected by surface EEG. This preliminary investigation analyzed the EEG signals through power spectra density (PSD) and centroid frequency (CF) to show that the GIF episodes were associated with significant increases in the high beta band (21-38Hz) across the central, frontal, occipital and parietal EEG sites. By implementing PSD and CF as input features with two-layer Back Propagation neural networks as a classifier, the proposed system was able to detect GIF events with a classification performance of 84.27% sensitivity and 84.80% accuracy. This is the first study to show cortical dynamic changes associated with GIF in Parkinson's disease, providing valuable information to enhance the performance of future GIF detection that could be translated into clinical practice.

Background: Recent attempts to standardise the definition of Mild Cognitive Impairment (MCI) in Parkinson's disease (PD) by the Movement Disorder Society Task Force has led to a greater understanding of this entity but to date, there has been a paucity of research regarding the impact of PD-MCI on caregiver outcomes., Objective: The aim of this study was to utilise the newly established PD-MCI diagnostic criteria to investigate caregiver outcomes in relation to four specific aspects: (1) caregiver burden, (2) quality of life (QoL), (3) caregiving experience, and (4) psychological distress., Methods: This study included a total of 166 patient-caregiver dyads. Caregiver outcomes including quality of life, caregiver burden, mood disturbances, and caregiver experience were compared between caregivers of PD patients classified as having normal cognition (PD-NC) and PD-MCI., Results: Despite the two groups being matched on demographic and clinical features, caregivers of PD-MCI patients reported a lower level of QoL with regard to physical health and more interruptions with usual activities. On the other hand, a higher impact on finances was reported in caregivers of PD-NC patients, relative to caregivers of PD-MCI patients., Conclusions: This study has shown that even at earlier stages of cognitive impairment, PD-MCI caregivers already experience elevated levels of distress in the role of providing care to their care-recipients. These findings highlight the need to include management of caregiver distress and associated sequelae alongside the management of PD-MCI patients, early on in the disease course.

Freezing of gait is a poorly understood symptom of Parkinson's disease (PD) that is commonly accompanied by executive dysfunction. This study employed an antisaccade task to measure deficits in inhibitory control in patients with freezing, and to determine if these are associated with a specific pattern of grey matter loss using voxel-based morphometry. PD patients with (n = 15) and without (n = 11) freezing along with 10 age-matched controls were included. A simple prosaccade task was administered, followed by a second antisaccade task that required subjects to either look towards or away from a peripheral target. Behavioral results from the antisaccade task were entered as covariates in the voxel-based morphometry analysis. Patient and control groups performed equally well on the first task. However, patients with freezing were significantly worse on the second, which was driven by a specific impairment in suppressing their responses toward the target on the antisaccade trials. Impaired antisaccade performance was associated with grey matter loss across bilateral visual and fronto-parietal regions. These results suggest that patients with freezing have a significant deficit of inhibitory control that is associated with volume reductions in regions crucial for orchestrating both complex motor behaviors and cognitive control. These findings highlight the inter-relationship between freezing of gait and cognition and confirm that dysfunction along common neural pathways is likely to mediate the widespread cognitive dysfunction that emerges with this symptom.

Functional connectivity provides an informative and powerful framework for exploring brain organization. Despite this, few statistical methods are available for the accurate estimation of dynamic changes in functional network architecture. To date, the majority of existing statistical techniques have assumed that connectivity structure is stationary, which is in direct contrast to emerging data that suggests that the strength of connectivity between regions is variable over time. Therefore, the development of statistical methods that enable exploration of dynamic changes in functional connectivity is currently of great importance to the neuroscience community. In this paper, we introduce the 'Multiplication of Temporal Derivatives' (MTD) and then demonstrate the utility of this metric to: (i) detect dynamic changes in connectivity using data from a novel state-switching simulation; (ii) accurately estimate graph structure in a previously-described 'ground-truth' simulated dataset; and (iii) identify task-driven alterations in functional connectivity. We show that the MTD is more sensitive than existing sliding-window methods in detecting dynamic alterations in connectivity structure across a range of correlation strengths and window lengths in simulated data. In addition to the temporal precision offered by MTD, we demonstrate that the metric is also able to accurately estimate stationary network structure in both simulated and real task-based data, suggesting that the method may be used to identify dynamic changes in network structure as they evolve through time., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: Freezing of gait is a debilitating symptom affecting many patients with Parkinson's disease (PD), causing severe immobility and decreased quality of life. Turning is known to be the most common trigger for freezing and also causes the highest rates of falls. However, the pathophysiological basis for these effects is not well understood., Methods: This study used a virtual reality paradigm in combination with functional magnetic resonance imaging to explore the neural correlates underlying turning in 17 PD patients with freezing of gait (FOG) and 10 PD patients without FOG while off their dopaminergic medication. Participants used foot pedals to navigate a virtual environment, which allowed for blood oxygen level-dependent (BOLD) responses and footstep latencies to be compared between periods of straight "walking" and periods of turning through 90°. BOLD data were then analyzed using a mixed effects analysis., Results: Within group similarities revealed that overall, PD patients with freezing relied heavily on cortical control to enable effective stepping with increased visual cortex activation during turning. Between groups differences showed that when turning, patients with freezing preferentially activated inferior frontal regions that have been implicated in the recruitment of a putative stopping network. In addition, freezers failed to activate premotor and superior parietal cortices. Finally, increased task-based functional connectivity was found in subcortical regions associated with gait and stopping within the freezers group during turning., Conclusions: These findings suggest that an increased propensity towards stopping in combination with reduced sensorimotor integration may underlie the neurobiology of freezing of gait during turning., Competing Interests: None of the authors have any competing financial interests to declare in relation to the work described.

Freezing of gait is a frequent and disabling symptom experienced by many patients with Parkinson's disease. A number of executive deficits have been shown to be associated with the phenomenon suggesting a common underlying pathophysiology, which as of yet remains unclear. Neuroimaging studies have also implicated the role of the cognitive control network in patients with freezing. To explore this concept, the current study examined error-monitoring as a measure of cognitive control. Thirty-four patients with and 38 without freezing of gait, who were otherwise well matched on disease severity, completed a colour-word interference task that allowed the specific assessment of error monitoring during conflict. Whilst both groups performed colour-naming and word-reading tasks equally well, those patients with freezing showed a pattern between conditions whereby they were better able to monitor performance and self-correct errors in the pure inhibition task but not after a switching rule was introduced. The novel results shown here provide insight into possible pathophysiological mechanisms involved in cognitive load and error monitoring in patients with freezing of gait. These results provide further evidence for the role of functional frontostriatal circuitry impairments in patients with freezing of gait and have implications for future studies and possible therapeutic interventions.

The pathological hallmark of Parkinson's disease is the degeneration of dopaminergic nigrostriatal neurons, leading to depletion of striatal dopamine. Recent neuroanatomical work has identified pathways for communication across striatal subdivisions, suggesting that the striatum provides a platform for integration of information across parallel corticostriatal circuits. The aim of this study was to investigate whether dopaminergic dysfunction in Parkinson's disease was associated with impairments in functional connectivity across striatal subdivisions, which could potentially reflect reduced integration across corticostriatal circuits. Utilizing resting-state functional magnetic resonance imaging (fMRI), we analyzed functional connectivity in 39 patients with Parkinson's disease, both "on" and "off" their regular dopaminergic medications, along with 40 age-matched healthy controls. Our results demonstrate widespread impairments in connectivity across subdivisions of the striatum in patients with Parkinson's disease in the "off" state. The administration of dopaminergic medication significantly improved connectivity across striatal subdivisions in Parkinson's disease, implicating dopaminergic deficits in the pathogenesis of impaired striatal interconnectivity. In addition, impaired striatal interconnectivity in the Parkinson's disease "off" state was associated with pathological decoupling of the striatum from the thalamic and sensorimotor (SM) networks. Specifically, we found that although the strength of striatal interconnectivity was positively correlated with both (i) the strength of internal thalamic connectivity, and (ii) the strength of internal SM connectivity, in both healthy controls and the Parkinson's disease "on" state, these relationships were absent in Parkinson's disease when in the "off" state. Taken together our findings emphasize the central role of dopamine in integrated striatal function and the pathological consequences of striatal dopamine denervation in Parkinson's disease., (© 2014 Wiley Periodicals, Inc.)

Freezing of gait (FOG) is a disabling motor symptom experienced by a large proportion of patients with Parkinson's disease (PD). While it is known that FOG contributes to lower health-related quality of life (HRQoL), previous studies have not accounted for other important factors when measuring the specific impact of this symptom. The aim of this study was to examine FOG and HRQoL while controlling for other factors that are known to impact patient well-being, including cognition, motor severity, sleep disturbance and mood. Two hundred and three patients with idiopathic PD (86 with FOG) were included in the study. All patients were between Hoehn and Yahr stages I-III. A forced entry multiple regression model evaluating the relative contribution of all symptoms was conducted, controlling for time since diagnosis and current dopaminergic treatment. Entering all significantly correlated variables into the regression model accounted for the majority of variance exploring HRQoL. Self-reported sleep-wake disturbances, depressive and anxious symptoms and FOG were individually significant predictors. FOG accounted for the highest amount of unique variance. While sleep-wake disturbance and mood have a significant negative impact on HRQoL in PD, the emergence of FOG represents the most substantial predictor among patients in the earlier clinical stages of disease. This finding presumably reflects the disabling loss of independence and fear of injury associated with FOG and underlines the importance of efforts to reduce this common symptom.

Background: Using the Movement Disorder Society (MDS) Task Force Level 1 criteria, this study examined the classification of mild cognitive impairment in Parkinson's Disease (PD-MCI) derived from a range of cut-off scores that have previously been suggested by the MDS Task Force. Furthermore, differences in PD-MCI frequencies were examined when comparing performance on current neuropsychological testing to the normative sample, as opposed to decline from premorbid functioning, as evidence of cognitive impairment., Method: Two hundred and thirty-four non-demented PD patients underwent neurological and neuropsychological assessment at the Parkinson's Disease Research Clinic at the Brain and Mind Research Institute, University of Sydney., Results: When cognitive impairment was defined as 1SD and 1.5SD below premorbid intellect, 109 patients (47%) and 76 (32%) patients met criteria for PD-MCI respectively. This proportion dropped considerably to 50 patients (21%) with a 2SD cut-off score. However, when calculating impairment based on comparisons with normative data, only 68 patients (29%) and 41 patients (18%) met PD-MCI criteria when a cut-off score of 1 and 1.5SD was employed. This proportion dropped to just 22 patients (9%) with a 2SD cut-off score., Conclusion: Results from the present study suggest that the MDS PD-MCI criteria may be too broad, as substantial differences in frequencies of PD-MCI were observed with the application of differing criteria. We propose that a 1.5SD cut-off score below premorbid functioning may provide greater utility in characterizing PD-MCI than a 1.5SD cut-off below normative data, which has been widely applied in previous studies examining the MDS PD-MCI criteria., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Freezing of gait is a very debilitating symptom affecting many patients with Parkinson's disease, leading to a reduced mobility and increased risk for falls. Turning is known to be the most provocative trigger for freezing of gait. However, the underlying brain dynamic changes associated with a turning freeze remain unknown. This study therefore used ambulatory EEG to investigate the brain dynamic changes associated with freezing of gait during turning. In addition, this study aimed to determine the most suitable EEG sensor location to detect freezing of gait during turning using our classification system. Data from four Parkinson's disease patients with freezing of gait was analysed using power spectral density and brain effective connectivity, comparing periods of successful turning with freezing of gait during turning. Results showed that freezing of gait during turning is associated with significant alterations in the high beta and theta power spectral densities across the occipital and parietal areas. Furthermore, brain effective connectivity showed that freezing during turning was associated with increased connectivity towards the visual area, which also had the highest accuracy to detect freezing episodes in the O1 regions by using power spectral density in our classification analyses. This is the first study to show cortical dynamic changes associated with freezing of gait during turning, providing valuable information to enhance the performance of future freezing of gait detection systems.

Background: Freezing of gait is a common disabling symptom of Parkinson's disease (PD) with limited treatment options. The pathophysiological mechanisms of freezing behaviour are still contentious., Objective: To investigate the prevalence of freezing of gait and its associations with increasing disease severity to gain a better understanding of the underlying pathophysiology., Methods: This exploratory study included 389 idiopathic PD patients, divided into four groups; early and advanced PD with freezing of gait, and early and advanced PD without freezing of gait. Motor, cognitive and affective symptoms, REM sleep behaviour disorder and autonomic function were assessed., Results: Regardless of disease stage, patients with freezing of gait had more severe motor symptoms and a predominant non-tremor phenotype. In the early stages, freezers had a selective impairment in executive function and had more marked REM sleep behaviour disorder. Autonomic disturbances were not associated with freezing of gait across early or advanced disease stages., Conclusion: These findings support the notion that impairments across the frontostriatal pathways are intricately linked to the pathophysiology underlying freezing of gait across all stages of PD. Features of REM sleep behaviour disorder suggest a contribution to freezing from brainstem pathology but this does not extend to more general autonomic dysfunction.

Visual misperceptions and hallucinations represent a problematic symptom of Parkinson's disease. The pathophysiological mechanisms underlying these symptoms remain poorly understood, however, a recent hypothesis has suggested that visual misperceptions and hallucinations may arise from disrupted processing across attentional networks. To test the specific predictions of this hypothesis, 22 patients with Parkinson's disease underwent 3T fMRI while performing the Bistable Percept Paradigm, a task that has previously been shown to identify patients with hallucinations. Subjects are required to study a battery of randomly assigned "monostable" and "bistable" monochromatic images for the presence or absence of a bistable percept. Those patients who scored a high percentage of misperceptions and missed images on the task were less able to activate frontal and parietal hubs of the putative Dorsal Attention Network. Furthermore, poor performance on the task was significantly correlated with the degree of decreased activation in a number of these hubs. At the group level, the difference between processing a bistable versus a monostable cue was associated with increased recruitment of the anterior insula. In addition, those patients with impaired performance on the paradigm displayed decreased resting state functional connectivity between hubs of the Ventral and Dorsal Attention Networks. These same patients had significantly decreased gray matter in the insula bilaterally. In addition, a combined analysis of the separate neuroimaging approaches revealed significant relationships across the impaired networks. These findings are consistent with specific predictions from a recently proposed hypothesis that implicates dysfunction within attentional networks in Parkinsonian hallucinations., (Copyright © 2013 Wiley Periodicals, Inc.)

Rapid eye movement (REM) sleep behavior disorder (RBD) is frequently observed in patients with Parkinson's disease (PD). Accurate diagnosis is essential for managing this condition. Furthermore, the emergence of idiopathic RBD in later life can represent a premotor feature, heralding the development of PD. Reliable, accurate methods for identifying RBD may offer a window for early intervention. This study sought to identify whether the RBD screening questionnaire (RBDSQ) and three questionnaires focused on dream enactment were able to correctly identify patients with REM without atonia (RWA), the neurophysiological hallmark of RBD. Forty-six patients with PD underwent neurological and sleep assessment in addition to completing the RBDSQ, the RBD single question (RBD1Q), and the Mayo Sleep Questionnaire (MSQ). The REM atonia index was derived for all participants as an objective measure of RWA. Patients identified to be RBD positive on the RBDSQ did not show increased RWA on polysomnography (80% sensitivity and 55% specificity). However, patients positive for RBD on questionnaires specific to dream enactment correctly identified higher degrees of RWA and improved the diagnostic accuracy of these questionnaires. This study suggests that the RBDSQ does not accurately identify RWA, essential for diagnosing RBD in PD. Furthermore, the results suggest that self-report measures of RBD need to focus questions on dream enactment behavior to better identify RWA and RBD. Further studies are needed to develop accurate determination and quantification of RWA in RBD to improve management of patients with PD in the future., (© 2014 International Parkinson and Movement Disorder Society.)

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD), in which patients experience sudden difficulties in starting or continuing locomotion. It is described by patients as the sensation that their feet are suddenly glued to the ground. This, disturbs their balance, and hence often leads to falls. In this study, directed transfer function (DTF) and partial directed coherence (PDC) were used to calculate the effective connectivity of neural networks, as the input features for systems that can detect FOG based on a Multilayer Perceptron Neural Network, as well as means for assessing the causal relationships in neurophysiological neural networks during FOG episodes. The sensitivity, specificity and accuracy obtained in subject dependent analysis were 82%, 77%, and 78%, respectively. This is a significant improvement compared to previously used methods for detecting FOG, bringing this detection system one step closer to a final version that can be used by the patients to improve their symptoms.

Background: Freezing of gait is a common and debilitating symptom affecting many patients with advanced Parkinson's disease. Although the pathophysiology of freezing of gait is not fully understood, a number of observations regarding the pattern of gait in patients with this symptom have been made. Increased 'Stride Time Variability' has been one of the most robust of these features. In this study we sought to identify whether patients with freezing of gait demonstrated similar fluctuations in their stepping rhythm whilst performing a seated virtual reality gait task that has recently been used to demonstrate the neural correlate of the freezing phenomenon., Methods: Seventeen patients with freezing and eleven non-freezers performed the virtual reality task twice, once whilst 'On' their regular Parkinsonian medication and once in their practically defined 'Off' state., Results: All patients displayed greater step time variability during their 'Off' state assessment compared to when medicated. Additionally, in the 'Off' state, patients with freezing of gait had greater step time variability compared to non-freezers. The five steps leading up to a freezing episode in the virtual reality environment showed a significant increase in step time variability although the final three steps preceding the freeze were not characterized by a progressive shortening of latency., Conclusions: The results of this study suggest that characteristic features of gait disturbance observed in patients with freezing of gait can also be demonstrated with a virtual reality paradigm. These findings suggest that virtual reality may offer the potential to further explore the freezing phenomenon in Parkinson's disease.

Freezing of gait is a devastating symptom of advanced Parkinson's disease yet the neural correlates of this phenomenon remain poorly understood. In this study, severity of freezing of gait was assessed in 18 patients with Parkinson's disease on a series of timed 'up and go' tasks, in which all patients suffered from episodes of clinical freezing of gait. The same patients also underwent functional magnetic resonance imaging with a virtual reality gait paradigm, performance on which has recently been shown to correlate with actual episodes of freezing of gait. Statistical parametric maps were created that compared the blood oxygen level-dependent response associated with paroxysmal motor arrests (freezing) to periods of normal motor output. The results of a random effects analysis revealed that these events were associated with a decreased blood oxygen level-dependent response in sensorimotor regions and an increased response within frontoparietal cortical regions. These signal changes were inversely correlated with the severity of clinical freezing of gait. Motor arrests were also associated with decreased blood oxygen level-dependent signal bilaterally in the head of caudate nucleus, the thalamus and the globus pallidus internus. Utilizing a mixed event-related/block design, we found that the decreased blood oxygen level-dependent response in the globus pallidus and the subthalamic nucleus persisted even after controlling for the effects of cognitive load, a finding which supports the notion that paroxysmal increases in basal ganglia outflow are associated with the freezing phenomenon. This method also revealed a decrease in the blood oxygen level-dependent response within the mesencephalic locomotor region during motor arrests, the magnitude of which was positively correlated with the severity of clinical freezing of gait. These results provide novel insights into the pathophysiology underlying freezing of gait and lend support to models of freezing of gait that implicate dysfunction across coordinated neural networks.