Does visual cueing improve gait initiation in people with Parkinson's disease?

Auditory cues modulate the short timescale dynamics of STN activity during stepping in Parkinson's disease

BACKGROUND

Gait impairment has a major impact on quality of life in patients with Parkinson's disease (PD). It is believed that basal ganglia oscillatory activity at β frequencies (15-30 Hz) may contribute to gait impairment, but the precise dynamics of this oscillatory activity during gait remain unclear. Additionally, auditory cues are known to lead to improvements in gait kinematics in PD. If the neurophysiological mechanisms of this cueing effect were better understood they could be leveraged to treat gait impairments using adaptive Deep Brain Stimulation (aDBS) technologies.

OBJECTIVE

We aimed to characterize the dynamics of subthalamic nucleus (STN) oscillatory activity during stepping movements in PD and to establish the neurophysiological mechanisms by which auditory cues modulate gait.

METHODS

We studied STN local field potentials (LFPs) in eight PD patients while they performed stepping movements. Hidden Markov Models (HMMs) were used to discover transient states of spectral activity that occurred during stepping with and without auditory cues.

RESULTS

The occurrence of low and high β bursts was suppressed during and after auditory cues. This manifested as a decrease in their fractional occupancy and state lifetimes. Interestingly, α transients showed the opposite effect, with fractional occupancy and state lifetimes increasing during and after auditory cues.

CONCLUSIONS

We show that STN oscillatory activity in the α and β frequency bands are differentially modulated by gait-promoting oscillatory cues. These findings suggest that the enhancement of α rhythms may be an approach for ameliorating gait impairments in PD.

The Efficacy of Wearable Cueing Devices on Gait and Motor Function in Parkinson Disease: A Systematic Review and Meta-analysis of Randomized Controlled Trials

OBJECTIVE

To summarize the efficacy of wearable cueing devices for improving gait and motor function of patients with Parkinson disease (PWP).

DATA SOURCES

PubMed, Embase, and Cochrane CENTRAL databases were searched for papers published in English, from inception to October 23, 2022.

STUDY SELECTION

Randomized controlled trials focusing on the effects of wearable cueing devices on gait and motor function in PWP were included.

DATA EXTRACTION

Two reviewers independently selected articles and extracted the data. The Cochrane Bias Risk Assessment Tool was used to assess risk of bias and the Grading of Recommendations Assessment, Development and Evaluation was used to evaluate the quality of evidence.

DATA SYNTHESIS

Seven randomized controlled trials with 167 PWP were included in the meta-analysis. Significant effect of wearable cueing devices on walking speed (mean difference [MD]=0.07 m/s, 95% confidence interval [CI]: [0.05, 0.09], P<.00001) was detected; however, after sensitivity analysis, no significant overall effect on walking speed was noted (MD=0.04 m/s, 95% CI: [-0.03, 0.12], P=.25). No significant improvements were found in stride length (MD=0.06 m, 95% CI: [0.00, 0.13], P=.05), the Unified Parkinson's Disease Rating Scale-III score (MD=-0.61, 95% CI: [-4.10, 2.88], P=.73), Freezing of Gait Questionnaire score (MD=-0.83, 95% CI: [-2.98, 1.33], P=.45), or double support time (MD=-0.91, 95% CI: [-3.09, 1.26], P=.41). Evidence was evaluated as low quality.

CONCLUSIONS

Wearable cueing devices may result in an immediate improvement on walking speed; however, there is no evidence that their use results in a significant improvement in other gait or motor functions.

Gait initiation in Parkinson's disease: comparison of timing and displacement during anticipatory postural adjustments as a function of motor severity and apathy in a large cohort

Introduction

Gait initiation is preceded by three anticipatory postural adjustment (APA) phases. In Parkinson's disease (PD) generated force, displacement and timing during APA differ from healthy controls. APA might be influenced by disease status, weight or emotion. It is unknown how motor severity, disease duration or presence of apathy influences APA timing and displacement.

Methods

We included 99 people with PD and 50 healthy controls (HC) to perform five gait initiation trials following an auditory cue. Force plates measured timing and center of pressure (CoP) displacement during APA phases.

Results

Time to gait initiation (tGI) was higher in the PD group (p < 0.001, t = 2.74, 95%CI (0.008, 0.066)). The first two APA phases (APA1 and APA2a) lasted longer in PD (respectively p < 0.001, t = 3.87, 95%CI (0.091, 0.28) and p < 0.001, t = 4.1, 95%CI (0.031, 0.091)). Mean CoP displacement, variability in timing and displacement did not differ. A multiple regression model was used to determine if clinical variables were related to gait initiation parameters. tGI was predicted by age (p < 0.001) and weight (p = 0.005). The duration of APA1 was predicted by weight (p = 0.006) and APA2a by age (p < 0.001). Variability in duration of the locomotor phase (LOC) was predicted by age (p < 0.001).

Conclusion

tGI and initial APA phases are longer in PD than in HC. There are no significant differences in variability of timing or displacement between the two groups. Gait initiation parameters are independent of disease duration, motor severity, medication usage or apathy in PD. Our findings suggest that cueing does not speed up gait initiation but reduces variability.

Motor networks, but also non-motor networks predict motor signs in Parkinson's disease

OBJECTIVE

Investigate the brain functional networks associated with motor impairment in people with Parkinson's disease (PD).

BACKGROUND

PD is primarily characterized by motor dysfunction. Resting-state functional connectivity (RsFC) offers a unique opportunity to non-invasively characterize brain function. In this study, we hypothesized that the motor dysfunction observed in people with PD involves atypical connectivity not only in motor but also in higher-level attention networks. Understanding the interaction between motor and non-motor RsFC that are related to the motor signs could provide insights into PD pathophysiology.

METHODS

We used data from 88 people with PD (mean age: 68.2(SD:10), 55 M/33F) coming from 2 cohorts. Motor severity was assessed in practical OFF-medication state, using MDS-UPDRS Part-III motor scores (mean: 49 (SD:10)). RsFC was characterized using an atlas of 384 regions that were grouped into 13 functional networks. Associations between RsFC and motor severity were assessed independently for each RsFC using predictive modeling.

RESULTS

The top 5 % models that predicted the MDS-UPDRS-III motor scores with effect size >0.5 were the connectivity between (1) the somatomotor and Subcortical-Basal-ganglia, (2) somatomotor and Visual and (3) CinguloOpercular (CiO) and language/Ventral attention (Lan/VeA) network pairs.

DISCUSSION

Our findings suggest that, along with motor networks, visual- and attention-related cortical networks are also associated with the motor symptoms of PD. Non-motor networks may be involved indirectly in motor-coordination. When people with PD have deficits in motor networks, more attention may be needed to carry out formerly automatic motor functions, consistent with compensatory mechanisms in parkinsonian movement disorders.

Discovering individual-specific gait signatures from data-driven models of neuromechanical dynamics

Locomotion results from the interactions of highly nonlinear neural and biomechanical dynamics. Accordingly, understanding gait dynamics across behavioral conditions and individuals based on detailed modeling of the underlying neuromechanical system has proven difficult. Here, we develop a data-driven and generative modeling approach that recapitulates the dynamical features of gait behaviors to enable more holistic and interpretable characterizations and comparisons of gait dynamics. Specifically, gait dynamics of multiple individuals are predicted by a dynamical model that defines a common, low-dimensional, latent space to compare group and individual differences. We find that highly individualized dynamics-i.e., gait signatures-for healthy older adults and stroke survivors during treadmill walking are conserved across gait speed. Gait signatures further reveal individual differences in gait dynamics, even in individuals with similar functional deficits. Moreover, components of gait signatures can be biomechanically interpreted and manipulated to reveal their relationships to observed spatiotemporal joint coordination patterns. Lastly, the gait dynamics model can predict the time evolution of joint coordination based on an initial static posture. Our gait signatures framework thus provides a generalizable, holistic method for characterizing and predicting cyclic, dynamical motor behavior that may generalize across species, pathologies, and gait perturbations.

One cue does not fit all: a systematic review with meta-analysis of the effectiveness of cueing on freezing of gait in Parkinson's disease

The difficulty in assessing FOG and the variety of existing cues, hamper to determine which cueing modality should be applied and which FOG-related aspect should be targeted to reach personalized treatments for FOG. This systematic review aimed to highlight: i) whether cues could reduce FOG and improve FOG-related gait parameters, ii) which cues are the most effective, iii) whether medication state (ON-OFF) affects cues-related results. Thirty-three repeated measure design studies assessing cueing effectiveness were included and subdivided according to gait tasks (gait initiation, walking, turning) and to the medication state. Main results reveal that: preparatory phase of gait initiation benefit from visual and auditory cues; spatio-temporal parameters (e.g., step and stride length) and are improved by visual cues during walking; turning time and step time variability are reduced by applying auditory and visual cues. Some findings on the potential benefits of cueing on FOG and FOG gait-related parameters were found. Questions remain about which are the best behavioral strategies according to FOG features and PD clinical characteristics.