ORCID Profile
0000-0002-0072-4637
Current Organisation
KU Leuven
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Publisher: Springer Science and Business Media LLC
Date: 22-10-2015
Abstract: 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. 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. 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. 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.
Publisher: Wiley
Date: 11-03-2014
DOI: 10.1002/MDS.25832
Abstract: 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.
Publisher: Elsevier BV
Date: 2015
DOI: 10.1016/J.PARKRELDIS.2014.10.020
Abstract: 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 s le, as opposed to decline from premorbid functioning, as evidence of cognitive impairment. 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. 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. 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.
Publisher: Hindawi Limited
Date: 2016
DOI: 10.1155/2016/6254092
Abstract: 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.
Publisher: Springer Science and Business Media LLC
Date: 26-06-2020
DOI: 10.1038/S41582-020-0370-2
Abstract: 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 in idualized 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 in iduals over time. Design of such systems will require collaboration between all stakeholders to maximize useability, engagement, safety and effectiveness.
Publisher: Frontiers Media SA
Date: 2015
Publisher: Elsevier BV
Date: 05-2017
DOI: 10.1016/J.NEUROIMAGE.2017.02.073
Abstract: 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.
Publisher: Wiley
Date: 07-2018
DOI: 10.1002/MDS.27417
Abstract: 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 in idual 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.
Publisher: Springer Science and Business Media LLC
Date: 10-09-2021
DOI: 10.1038/S41531-021-00224-4
Abstract: Freezing of gait (FOG) in Parkinson’s disease (PD) causes severe patient burden despite pharmacological management. Exercise and training are therefore advocated as important adjunct therapies. In this meta-analysis, we assess the existing evidence for such interventions to reduce FOG, and further examine which type of training helps the restoration of gait function in particular. The primary meta-analysis across 41 studies and 1838 patients revealed a favorable moderate effect size (ES = −0.37) of various training modalities for reducing subjective FOG-severity ( p 0.00001), though several interventions were not directly aimed at FOG and some included non-freezers. However, exercise and training also proved beneficial in a secondary analysis on freezers only (ES = −0.32, p = 0.007). We further revealed that dedicated training aimed at reducing FOG episodes (ES = −0.24) or ameliorating the underlying correlates of FOG (ES = −0.40) was moderately effective ( p 0.01), while generic exercises were not (ES = −0.14, p = 0.12). Relevantly, no retention effects were seen after cessation of training (ES = −0.08, p = 0.36). This review thereby supports the implementation of targeted training as a treatment for FOG with the need for long-term engagement.
Publisher: IEEE
Date: 05-1970
Publisher: Elsevier BV
Date: 09-2016
DOI: 10.1016/J.GAITPOST.2016.07.182
Abstract: 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<0.001). PD+MildFOG, however, demonstrated similar levels of anxiety as the PD+FOG. In all patients, the severity of anxiety symptoms was significantly correlated to their degree of self-reported FOG on FOG-Q3 (p<0.001) and TMT B-A (p=0.039). Similar results were found for depression. In conclusion, these results confirm the key role played by anxiety in FOG and also suggest that anxiety might be a promising biomarker for FOG. Future research should consider whether treating anxiety with pharmacological and/or cognitive behavioural therapies at early stages of gait impairment in PD may alleviate troublesome FOG.
Publisher: Springer Science and Business Media LLC
Date: 15-08-2017
DOI: 10.1007/S11682-017-9754-3
Abstract: 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.
Publisher: Springer Science and Business Media LLC
Date: 02-03-2021
DOI: 10.1038/S41531-021-00163-0
Abstract: 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 in iduals 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.
Publisher: IEEE
Date: 08-2016
Publisher: Elsevier BV
Date: 03-2018
Publisher: Springer Science and Business Media LLC
Date: 18-05-2018
DOI: 10.1038/S41531-018-0052-6
Abstract: 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 s le of interest including only those who had objective FoG at baseline, and completed the intervention. Sixty-five patients were randomized into the study. The s le 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 s le is required.
Publisher: Elsevier BV
Date: 07-2018
DOI: 10.1016/J.PARKRELDIS.2018.03.009
Abstract: 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 in idualized 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.
Publisher: Springer Science and Business Media LLC
Date: 13-10-2015
DOI: 10.1007/S00415-015-7910-5
Abstract: 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.
Publisher: Frontiers Media SA
Date: 09-01-2017
Publisher: Elsevier BV
Date: 11-2015
DOI: 10.1016/J.NEUROIMAGE.2015.07.064
Abstract: 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.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Cold Spring Harbor Laboratory
Date: 20-03-2018
DOI: 10.1101/285171
Abstract: 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 in iduals 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 litude 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.
Publisher: Springer Science and Business Media LLC
Date: 29-11-2016
Publisher: Springer Science and Business Media LLC
Date: 22-07-2014
DOI: 10.1007/S00702-014-1271-6
Abstract: 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.
Publisher: Oxford University Press (OUP)
Date: 24-04-2017
DOI: 10.1093/BRAIN/AWX063
Publisher: Cold Spring Harbor Laboratory
Date: 05-05-2023
DOI: 10.1101/2023.05.05.23289387
Abstract: Freezing of gait (FOG) is an episodic and highly disabling symptom of Parkinson’s Disease (PD). Traditionally, FOG assessment relies on time-consuming visual inspection of camera footage. Therefore, previous studies have proposed portable and automated solutions to annotate FOG. However, automated FOG assessment is challenging due to gait variability caused by medication effects and varying FOG-provoking tasks. Moreover, whether automated approaches can differentiate FOG from typical everyday movements, such as volitional stops, remains to be determined. To address these questions, we evaluated an automated FOG assessment model with deep learning (DL) based on inertial measurement units (IMUs). We assessed its performance trained on all standardized FOG-provoking tasks and medication states, as well as on specific tasks and medication states. Furthermore, we examined the effect of adding stopping periods on FOG detection performance. Twelve 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). For FOG assessment in trials without stopping, the agreement of our model was strong (ICC(%TF) = 0.92 [0.68, 0.98] ICC(#FOG) = 0.95 [0.72, 0.99]). Models trained on a specific FOG-provoking task could not generalize to unseen tasks, while models trained on a specific medication state could generalize to unseen states. For assessment in trials with stopping, the 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]). A 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.
Publisher: Public Library of Science (PLoS)
Date: 21-06-2013
Publisher: Wiley
Date: 18-11-2017
DOI: 10.1002/MDS.27208
Abstract: 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 ided 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.
Publisher: IEEE
Date: 08-2014
Publisher: BMJ
Date: 24-05-2018
DOI: 10.1136/JNNP-2018-ANZAN.24
Abstract: Freezing of gait (FOG) in Parkinson’s disease (PD) is a disabling symptom of advanced PD and is frequently triggered upon passing through narrow spaces such as doorways. 1 Despite being common, the mechanisms underlying this phenomenon are poorly understood. We have previously shown that increased footstep latency in a virtual reality (VR) environment is a surrogate measure of FOG. 2 In this study we aimed to model doorway freezing utilising the VR paradigm in conjunction with functional magnetic resonance imaging (fMRI) to determine the neural correlates of this phenomenon. In our study, nineteen patients who routinely experience FOG performed a previously validated VR gait paradigm 3 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 signal changes were compared within each patient. We were able to reproduce the finding that patients in the OFF state demonstrated significantly longer ‘footstep’ latencies as they passed through a doorway in the VR environment compared to the ON state. As seen clinically with FOG this locomotive delay was primarily triggered by narrow doorways rather than wide doorways. fMRI analysis revealed that doorway-provoked footstep delay was associated with selective hypoactivation in the pre-supplementary motor area (pSMA) bilaterally. Task-based functional connectivity analyses showed that this delay 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. . Giladi N, Treves TA, Simon ES, Shabtai H, Orlov Y, Kandinov B, Paleacu D, Korczyn AD. Freezing of gait in patients with advanced Parkinson’s disease. J Neural Transm (Vienna)2001 :53–61. . Matar E, Shine JM, Naismith SL, Lewis SJ.Virtual realitywalking and dopamine: opening new doorways to understanding freezing of gait in Parkinson’s disease. J Neurol Sci 2014 :182–5. . Shine JM, Matar E, Bolitho SJ, Dilda V, Morris TR, Naismith SL, Moore ST, Lewis SJ. Modelling freezing of gait in Parkinson’s disease with a virtual reality paradigm. Gait Posture2013 :104–8.
Publisher: Wiley
Date: 13-06-2013
DOI: 10.1002/HBM.22321
Publisher: IEEE
Date: 07-2017
Publisher: Oxford University Press (OUP)
Date: 02-11-2014
DOI: 10.1093/BRAIN/AWU315
Publisher: IEEE
Date: 08-2015
Publisher: Elsevier BV
Date: 11-2016
DOI: 10.1016/J.NEUROSCIENCE.2016.09.019
Abstract: 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.
Publisher: Wiley
Date: 25-11-2014
DOI: 10.1002/HBM.22701
Publisher: Elsevier BV
Date: 11-2018
Publisher: Cold Spring Harbor Laboratory
Date: 12-07-2023
DOI: 10.1101/2023.07.10.23292437
Abstract: Freezing of gait (FOG) is an episodic and highly disabling symptom of Parkinson’s disease (PD). Although described as a single phenomenon, FOG is not univocal and can express as different manifestations, such as trembling in place or complete akinesia. We aimed to analyze the utility of deep learning trained on inertial measurement unit data to classify FOG into both manifestations. We developed a temporal convolutional neural network, which we compared to three state-of-the-art FOG detection algorithms that were adapted to the FOG manifestation detection task. Next, we investigated its performance in distinguishing between the two manifestations and other forms of movement cessation (e.g., volitional stopping and sitting) based on gold-standard video annotations. Experiments were conducted on a dataset of twelve PD patients with FOG that completed a FOG-provoking protocol, including the timed-up-and-go and 360-degree turning-in-place tasks during ON and OFF anti-Parkinsonian medication. The results showed that our model enables accurate detection of FOG manifestations with an 11.43% higher F1 score than the second-best model. Assessment of FOG manifestation severity was moderately strong for trembling in place (Intra-class Correlation Coefficient (ICC)=0.64, [0.16,0.88]) and strong for complete akinesia (ICC=0.87, [0.63,0.96]). Remarkably, our results show that complete akinesia can be distinguished from volitional stopping. In conclusion, we established that FOG manifestations could be accurately detected and assessed with deep learning. Future work should establish whether these results hold firm for a more extensive and varied verification cohort.
Publisher: Springer Science and Business Media LLC
Date: 03-04-2018
DOI: 10.1007/S00415-018-8846-3
Abstract: 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 hippoc us, 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.
Publisher: Oxford University Press (OUP)
Date: 09-03-2018
DOI: 10.1093/BRAIN/AWY019
Abstract: 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 in idual 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 in idual 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.
Publisher: IEEE
Date: 08-2016
Publisher: Springer Science and Business Media LLC
Date: 16-10-2014
DOI: 10.1007/S00415-014-7524-3
Abstract: 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 in idually 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.
Publisher: Oxford University Press (OUP)
Date: 12-03-2013
DOI: 10.1093/BRAIN/AWT049
Abstract: 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.
No related grants have been discovered for Moran Gilat.