Our long-term goal is to advance our scientific knowledge and computational approaches to identify causes of balance impairments leading to falls in Parkinson?s disease (PD) to guide the rational development more effective treatments and rehabilitation for improving balance. Recent insights from our neuromechanical simulation studies in tandem with our ongoing work characterizing changes reactive balance control after rehabilitation in people with PD have implicated our overall hypothesis that the cardinal parkinsonian sign of rigidity is a cause of balance impairments. Rigidity is not typically considered in fall risk, yet our ongoing studies demonstrate a previously-unreported association between leg rigidity and prior falls. We believe that identifying the causes of this association will lead to improved diagnosis and treatment of balance impairments in PD. Our objective is to identify the effects of leg rigidity on postural robustness, defined as the ability to maintain the feet in place in reactive balance. Based on our neuromechanical simulations, we hypothesize that parkinsonian rigidity increases two distinct aspects of postural muscle activity that can each reduce postural robustness: tonic muscle activity, defined as the magnitude of muscle activity in static postures, and dynamic muscle activity is defined as the magnitude and timing of muscle activity generated by sensorimotor feedback in reactive balance. We will use combined experimental and computational approaches to systematically isolate the causal linkages and interactions between rigidity, muscle activity, and postural robustness in PD. In addition to electromyographic (EMG) recordings, we will also establish the reliability of measuring tonic muscle activity during standing using frequency domain near-infrared spectroscopy (FDNIRS) combined with diffuse correlation spectroscopy (DCS).
In Aim 1 we will test well-characterized PD participants with confirmed dopamine-responsive rigidity to identify the effects of leg rigidity on tonic muscle activity, dynamic muscle activity, and postural robustness; we will manipulate rigidity using dopamine medication and an activation maneuver.
In Aim 2 we will test neurotypical participants to identify causal role of modulating tonic and dynamic muscle activity on postural robustness; we will modulate muscle activity using EMG biofeedback and adaptation.
In Aim 3 we will develop neuromechanical simulations to quantitatively demonstrate mechanistic relationships between tonic muscle activity, dynamic muscle activity, and postural robustness. We will augment our neuromechanical models of balance with agonist-antagonist muscle models. If successful, we will 1) identify the causal role of rigidity on impaired balance in PD, 2) validate a novel and clinically-feasible method (NIRS) to measure rigidity in functionally-relevant tasks, and 3) establish a broadly extendable generative neuromechanical model of balance to simulate how multiple mechanisms interact to cause balance impairments. These outcomes will enable us to identify optimal treatment targets for the rational development of rehabilitation and other therapies for balance impairments across many disorders.
A major barrier to effective treatments for balance impairments leading to falls in Parkinson?s disease (PD) and other neurological disorders is that we simply do not understand the underlying causes. We will use novel computational and experimental techniques to advance mechanistic understanding of how muscle rigidity, a cardinal sign of PD, contributes to balance impairments. Our results will provide essential scientific knowledge and methods for investigating and ultimately developing rational treatments and rehabilitation which, rather than being palliative, target the root causes for balance impairments in PD.
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