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Gait Initiation in Parkinson’s Disease: Impact of Dopamine Depletion and Initial Stance Condition
(2020)
Postural instability, in particular at gait initiation (GI), and resulting falls are a major determinant of poor quality of life in subjects with Parkinson’s disease (PD). Still, the contribution of the basal ganglia and dopamine on the feedforward postural control associated with this motor task is poorly known. In addition, the influence of anthropometric measures (AM) and initial stance condition on GI has never been consistently assessed. The biomechanical resultants of anticipatory postural adjustments contributing to GI [imbalance (IMB), unloading (UNL), and stepping phase) were studied in 26 unmedicated subjects with idiopathic PD and in 27 healthy subjects. A subset of 13 patients was analyzed under standardized medication conditions and the striatal dopaminergic innervation was studied in 22 patients using FP-CIT and SPECT. People with PD showed a significant reduction in center of pressure (CoP) displacement and velocity during the IMB phase, reduced first step length and velocity, and decreased velocity and acceleration of the center of mass (CoM) at toe off of the stance foot. All these measurements correlated with the dopaminergic innervation of the putamen and substantially improved with levodopa. These results were not influenced by anthropometric parameters or by the initial stance condition. In contrast, most of the measurements of the UNL phase were influenced by the foot placement and did not correlate with putaminal dopaminergic innervation. Our results suggest a significant role of dopamine and the putamen particularly in the elaboration of the IMB phase of anticipatory postural adjustments and in the execution of the first step. The basal ganglia circuitry may contribute to defining the optimal referent body configuration for a proper initiation of gait and possibly gait adaptation to the environment.
Pathophysiological understanding of gait and balance disorders in Parkinson’s disease is insufficient and late recognition of fall risk limits efficacious followup to prevent or delay falls. We show a distinctive reduction of glucose metabolism in the left posterior parietal cortex, with increased metabolic activity in the cerebellum, in parkinsonian patients 6–8 months before their first fall episode. Falls in Parkinson’s disease may arise from altered cortical processing of body spatial orientation, possibly predicted by abnormal cortical metabolism.
Controlling posture, i.e., governing the ensemble of involuntary muscular activities that manage body equilibrium, represents a demanding function in which the cerebellum plays a key role. Postural activities are particularly important during gait initiation when passing from quiet standing to locomotion. Indeed, several studies used such motor task for evaluating pathological conditions, including cerebellar disorders. The linkage between cerebellum maturation and the development of postural control has received less attention. Therefore, we evaluated postural control during quiet standing and gait initiation in children affected by a slow progressive generalized cerebellar atrophy (SlowP) or non-progressive vermian hypoplasia (Joubert syndrome, NonP), compared to that of healthy children (H). Despite the similar clinical evaluation of motor impairments in NonP and SlowP, only SlowP showed a less stable quiet standing and a shorter and slower first step than H. Moreover, a descriptive analysis of lower limb and back muscle activities suggested a more severe timing disruption in SlowP. Such differences might stem from the extent of cerebellar damage. However, literature reports that during childhood, neural plasticity of intact brain areas could compensate for cerebellar agenesis. We thus proposed that the difference might stem from disease progression, which contrasts the consolidation of compensatory strategies.
Freezing of gait (FOG) is a sudden episodic inability to produce effective stepping despite the intention to walk. It typically occurs during gait initiation (GI) or modulation and may lead to falls. We studied the anticipatory postural adjustments (imbalance, unloading, and stepping phase) at GI in 23 patients with Parkinson’s disease (PD) and FOG (PDF), 20 patients with PD and no previous history of FOG (PDNF), and 23 healthy controls (HCs). Patients performed the task when off dopaminergic medications. The center of pressure (CoP) displacement and velocity during imbalance showed significant impairment in both PDNF and PDF, more prominent in the latter patients. Several measurements were specifically impaired in PDF patients, especially the CoP displacement along the anteroposterior axis during unloading. The pattern of segmental center of mass (SCoM) movements did not show differences between groups. The standing postural profile preceding GI did not correlate with outcome measurements. We have shown impaired motor programming at GI in Parkinsonian patients. The more prominent deterioration of unloading in PDF patients might suggest impaired processing and integration of somatosensory information subserving GI. The unaltered temporal movement sequencing of SCoM might indicate some compensatory cerebellar mechanisms triggering time-locked models of body mechanics in PD.
Objective: Gait adaptation to environmental challenges is fundamental for independent and safe community ambulation. The possibility of precisely studying gait modulation using standardized protocols of gait analysis closely resembling everyday life scenarios is still an unmet need.
Methods: We have developed a fully-immersive virtual reality (VR) environment where subjects have to adjust their walking pattern to avoid collision with a virtual agent (VA) crossing their gait trajectory. We collected kinematic data of 12 healthy young subjects walking in real world (RW) and in the VR environment, both with (VR/A+) and without (VR/A-) the VA perturbation. The VR environment closely resembled the RW scenario of the gait laboratory. To ensure standardization of the obstacle presentation the starting time speed and trajectory of the VA were defined using the kinematics of the participant as detected online during each walking trial.
Results: We did not observe kinematic differences between walking in RW and VR/A-, suggesting that our VR environment per se might not induce significant changes in the locomotor pattern. When facing the VA all subjects consistently reduced stride length and velocity while increasing stride duration. Trunk inclination and mediolateral trajectory deviation also facilitated avoidance of the obstacle.
Conclusions: This proof-of-concept study shows that our VR/A+ paradigm effectively induced a timely gait modulation in a standardized immersive and realistic scenario. This protocol could be a powerful research tool to study gait modulation and its derangements in relation to aging and clinical conditions.
Parkinson’s Disease (PD) constitutes a major healthcare burden in Europe. Accounting for aging alone, ~700,000 PD cases are predicted by 2040. This represents an approximately 56% increase in the PD population between 2005 and 2040, with a consequent rise in annual disease‐related medical costs. Gait and balance disorders are a major problem for patients with PD and their caregivers, mainly because to their correlation with falls. Falls occur as a result of a complex interaction of risk factors. Among them, Freezing of Gait (FoG) is a peculiar gait derangement characterized by a sudden and episodic inability to produce effective stepping, causing falls, mobility restrictions, poor quality of life, and increased morbidity and mortality. Between 50–70% of PD patients have FoG and/or falls after a disease duration of 10 years, only partially and inconsistently improved by dopaminergic treatment and Deep Brain Stimulation (DBS). Treatment-induced worsening has been also observed under certain conditions. Effective treatments for gait disturbances in PD are lacking, probably because of the still poor understanding of the supraspinal locomotor network.
In my thesis, I wanted to expand our knowledge of the supraspinal locomotor network and in particular the contribution of the basal ganglia to the control of locomotion. I believe this is a key step towards new preventive and personalized therapies for postural and gait problems in patients with PD and related disorders. In addition to patients with PD, my studies also included people affected by Progressive Supranuclear Palsy (PSP). PSP is a rare primary progressive parkinsonism characterized at a very early disease stage by poor balance control and frequent backwards falls, thus providing an in vivo model of dysfunctional locomotor control.
I focused my attention on one of the most common motor transitions in daily living, the initiation of gait (GI). GI is an interesting motor task and a relevant paradigm to address balance and gait impairments in patients with movement disorders, as it is associated with FoG and high risk of falls. It combines a preparatory (i.e., the Anticipatory Postural Adjustments [APA]) and execution phase (the stepping) and allows the study of movement scaling and timing as an expression of muscular synergies, which follow precise and online feedback information processing and integration into established feedforward patterns of motor control.
By applying a multimodal approach that combines biomechanical assessments and neuroimaging investigations, my work unveiled the fundamental contribution of striatal dopamine to GI in patients with PD. Results in patients with PSP further supported the fundamental role of the striatum in GI execution, revealing correlations between the metabolic intake of the left caudate nucleus with diverse GI measurements. This study also unveiled the interplay of additional brain areas in the motor control of GI, namely the Thalamus, the Supplementary Motor Area (SMA), and the Cingulate cortex. Involvement of cortical areas was also suggested by the analysis of GI in patients with PD and FoG. Indeed, I found major alterations in the preparatory phase of GI in these patients, possibly resulting from FoG-related deficits of the SMA. Alterations of the weight shifting preceding the stepping phase were also particularly important in PD patients with FoG, thus suggesting specific difficulties in the integration of somatosensory information at a cortical level. Of note, all patients with PD showed preserved movement timing of GI, possibly suggesting preserved and compensatory activity of the cerebellum. Postural abnormalities (i.e., increased trunk and thigh flexion) showed no relationship with GI, ruling out an adaptation of the motor pattern to the altered postural condition. In a group of PD patients implanted with DBS, I further explored the pathophysiological functioning of the locomotor network by analysing the timely activity of the Subthalamic Nucleus (STN) during static and dynamic balance control (i.e., standing and walking). For this study, I used novel DBS devices capable of delivering stimulation and simultaneously recording Local Field Potentials (LFP) of the implanted nucleus months and years after surgery. I showed a gait-related frequency shift in the STN activity of PD patients, possibly conveying cortical (feedforward) and cerebellar (feedback) information to mesencephalic locomotor areas. Based on this result, I identified for each patient a Maximally Informative Frequency (MIF) whose power changes can reliably classify standing and walking conditions. The MIF is a promising input signal for new DBS devices that can monitor LFP power modulations to timely adjust the stimulation delivery based on the ongoing motor task (e.g., gait) performed by the patient (adaptive DBS).
Altogether my achievements allowed to define the role of different cortical and subcortical brain areas in locomotor control, paving the way for a better understanding of the pathophysiological dynamics of the supraspinal locomotor network and the development of tailored therapies for gait disturbances and falls prevention in PD and related disorders.
Deep brain stimulation (DBS) of the subthalamic nucleus or the globus pallidus is an established treatment for Parkinson’s disease (PD) that yields a marked and lasting improvement of motor symptoms. Yet, DBS benefit on gait disturbances in PD is still debated and can be a source of dissatisfaction and poor quality of life. Gait disturbances in PD encompass a variety of clinical manifestations and rely on different pathophysiological bases. While gait disturbances arising years after DBS surgery can be related to disease progression, early impairment of gait may be secondary to treatable causes and benefits from DBS reprogramming. In this review, we tackle the issue of gait disturbances in PD patients with DBS by discussing their neurophysiological basis, providing a detailed clinical characterization, and proposing a pragmatic programming approach to support their management.
Gait disturbances are common manifestations of Parkinson’s disease (PD), with unmet therapeutic needs. Inertial measurement units (IMUs) are capable of monitoring gait, but they lack neurophysiological information that may be crucial for studying gait disturbances in these patients. Here, we present a machine learning approach to approximate IMU angular velocity profiles and subsequently gait events using electromyographic (EMG) channels during overground walking in patients with PD. We recorded six parkinsonian patients while they walked for at least three minutes. Patient-agnostic regression models were trained on temporally embedded EMG time series of different combinations of up to five leg muscles bilaterally (i.e., tibialis anterior, soleus, gastrocnemius medialis, gastrocnemius lateralis, and vastus lateralis). Gait events could be detected with high temporal precision (median displacement of <50 ms), low numbers of missed events (<2%), and next to no false-positive event detections (<0.1%). Swing and stance phases could thus be determined with high fidelity (median F1-score of ~0.9). Interestingly, the best performance was obtained using as few as two EMG probes placed on the left and right vastus lateralis. Our results demonstrate the practical utility of the proposed EMG-based system for gait event prediction, which allows the simultaneous acquisition of an electromyographic signal to be performed. This gait analysis approach has the potential to make additional measurement devices such as IMUs and force plates less essential, thereby reducing financial and preparation overheads and discomfort factors in gait studies.
Low-frequency oscillatory patterns of pallidal local field potentials (LFPs) have been proposed as a physiomarker for dystonia and hold the promise for personalized adaptive deep brain stimulation. Head tremor, a low-frequency involuntary rhythmic movement typical of cervical dystonia, may cause movement artifacts in LFP signals, compromising the reliability of low-frequency oscillations as biomarkers for adaptive neurostimulation. We investigated chronic pallidal LFPs with the Percept\(^{TM}\) PC (Medtronic PLC) device in eight subjects with dystonia (five with head tremors). We applied a multiple regression approach to pallidal LFPs in patients with head tremors using kinematic information measured with an inertial measurement unit (IMU) and an electromyographic signal (EMG). With IMU regression, we found tremor contamination in all subjects, whereas EMG regression identified it in only three out of five. IMU regression was also superior to EMG regression in removing tremor-related artifacts and resulted in a significant power reduction, especially in the theta-alpha band. Pallido-muscular coherence was affected by a head tremor and disappeared after IMU regression. Our results show that the Percept PC can record low-frequency oscillations but also reveal spectral contamination due to movement artifacts. IMU regression can identify such artifact contamination and be a suitable tool for its removal.