Approximately 50% of people with Parkinson disease experience freezing of gait, described as a transient inability to produce effective stepping. Complex gait tasks such as turning typically elicit freezing more commonly than simple gait tasks, such as forward walking. Despite the frequency of this debilitating and dangerous symptom, the brain mechanisms underlying freezing remain unclear. Gait imagery during functional magnetic resonance imaging permits investigation of brain activity associated with locomotion. We used this approach to better understand neural function during gait-like tasks in people with Parkinson disease who experience freezing- “FoG+” and people who do not experience freezing- ”FoG−“. Nine FoG+ and nine FoG− imagined complex gait tasks (turning, backward walking), simple gait tasks (forward walking), and quiet standing during measurements of blood oxygen level dependent (BOLD) signal. Changes in BOLD signal (i.e. beta weights) during imagined walking and imagined standing were analyzed across FoG+ and FoG− groups in locomotor brain regions including supplementary motor area, globus pallidus, putamen, mesencephalic locomotor region, and cerebellar locomotor region. Beta weights in locomotor regions did not differ for complex tasks compared to simple tasks in either group. Across imagined gait tasks, FoG+ demonstrated significantly lower beta weights in the right globus pallidus with respect to FoG−. FoG+ also showed trends toward lower beta weights in other right-hemisphere locomotor regions (supplementary motor area, mesencephalic locomotor region). Finally, during imagined stand, FoG+ exhibited lower beta weights in the cerebellar locomotor region with respect to FoG−. These data support previous results suggesting FoG+ exhibit dysfunction in a number of cortical and subcortical regions, possibly with asymmetric dysfunction towards the right hemisphere.

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This literature review addressed wearable sensor systems to monitor motor symptoms in individuals with Parkinson's disease (PD) during activities of daily living (ADLs). Specifically, progress in monitoring tremor, freezing of gait, dyskinesia, bradykinesia, and hypokinesia was reviewed. Twenty-seven studies were found that met the criteria of measuring symptoms in a home or home-like setting, with some studies examining multiple motor disorders. Accelerometers, gyroscopes, and electromyography sensors were included, with some studies using more than one type of sensor. Five studies measured tremor, five studies examined bradykinesia or hypokinesia, thirteen studies included devices to measure dyskinesia or motor fluctuations, and ten studies measured akinesia or freezing of gait. Current sensor technology can detect the presence and severity of each of these symptoms; however, most systems require sensors on multiple body parts, which is challenging for remote or ecologically valid observation. Different symptoms are detected by different sensor placement, suggesting that the goal of detecting all symptoms with a reduced set of sensors may not be achievable. For the goal of monitoring motor symptoms during ADLs in a home setting, the measurement system should be simple to use, unobtrusive to the wearer and easy for an individual with PD to put on and take off. Machine learning algorithms such as neural networks appear to be the most promising way to detect symptoms using a small number of sensors. More work should be done validating the systems during unscripted and unconstrained ADLs rather than in scripted motions.

Background: Balance challenges are associated with not only the aging process but also a wide variety of psychiatric and neurological disorders. However, relatively little is known regarding the neural basis of balance and the effects of balance interventions on the brain. Research Question: This review synthesizes the existing literature to answer the question: What are the key brain structures associated with balance? Methods: This review examined 37 studies that assessed brain structures in relation to balance assessment or intervention. These studies provided 234 findings implicating 71 brain structures. The frequency of implication for each structure was examined based upon specific methodological parameters, including study design (assessment/intervention), type of balance measured (static/ dynamic), population (clinical/non-clinical), and imaging analysis technique (region of interest [ROI]/voxel-based morphometry [VBM]).Results: Although a number of structures were associated with balance across the brain, the most frequently implicated structures included the cerebellum, basal ganglia, thalamus, hippocampus,

Objective Motor imagery during functional magnetic resonance imaging (fMRI) allows assessment of brain activity during tasks, like walking, that cannot be completed in a scanner. We used gait imagery to assess the neural pathophysiology of locomotion in Parkinson disease (PD). Methods Brain activity was measured in five locomotor regions (supplementary motor area (SMA), globus pallidus (GP), putamen, mesencephalic locomotor region, cerebellar locomotor region) during simple (forward) and complex (backward, turning) gait imagery. Brain activity was correlated to overground walking velocity. Results Across tasks, PD exhibited reduced activity in the globus pallidus compared to controls. People with PD, but not controls, exhibited more activity in the SMA during imagined turning compared to forward or backward walking. In PD, walking speed was correlated to brain activity in several regions. Conclusions Altered SMA activity in PD during imagined turning may represent compensatory neural adaptations during complex gait. The lowered activity and positive correlation to locomotor function in GP suggests reduced activity in this region may relate to locomotor dysfunction. Significance This study elucidates changes in neural activity during gait in PD, underscoring the importance of testing simple and complex tasks. Results support a positive relationship between activity in locomotor regions and walking ability.