Impaired control of multi-muscle synergies in Parkinson's disease
Open Access
- Author:
- Falaki, Ali
- Graduate Program:
- Kinesiology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- August 01, 2018
- Committee Members:
- Mark Latash, Dissertation Advisor/Co-Advisor
Mark Latash, Committee Chair/Co-Chair
Xuemei Huang, Committee Member
Robert L Sainburg, Committee Member
Rick Owen Gilmore, Outside Member - Keywords:
- Motor control
Synergy
Parkinson's disease
Stability
Posture
Uncontrolled manifold - Abstract:
- One of the main features of the human motor control system is its ability to control the stability of our actions, which involve multiple elements, such as digits, joints, and muscles. This is highly challenging given the poorly predictable environment and continuously changing intrinsic body states. Understanding the mechanisms of action stability and effects of neurological disorders on these mechanisms is, therefore, a highly important field of study. This dissertation quantifies changes in multi-muscle synergies that stabilize the vertical posture in Parkinson’s disease (PD), explore the relations between stability and agility of actions in PD, and try to link these effects to neural structures. Stability of the vertical posture is quantified using across-trials variance analysis in the space of hypothetical neural commands that form muscle groups with parallel modulation of their activation levels. This analysis quantifies the stability of the center of pressure coordinate and its changes in preparation to quick actions (agility). Early-stage PD patients with no clinically identifiable postural instability showed reduced indices of postural stability and an impairment in the ability to attenuate postural stability in preparation to a quick action. Indices of both stability and agility improve on dopamine-replacement drugs, and are getting worse by changes in the visual scene prior to step initiation. Comparing synergy indices across different multi-finger force production and multi-muscle whole body tasks suggests that synergy indices reflect systemic neural mechanisms shared across tasks and effectors. The contrasting effects of deep brain stimulation on indices of stability and agility suggest that these indices and their changes in PD reflect different functional neural subsystems. Analysis of multi-muscle synergies may provide a clinically sensitive biomarker for early diagnosis of PD and emergence of balance problems.