Several opensource or commercially available software platforms are widely used to develop dynamic simulations of movement. While computational approaches are conceptually similar across platforms, technical differences in implementation may influence output. We present a new upper limb dynamic model as a tool to evaluate potential differences in predictive behavior between platforms. We evaluated to what extent differences in technical implementations in popular simulation software environments result in differences in kinematic predictions for single and multijoint movements using EMG- and optimization-based approaches for deriving control signals. We illustrate the benchmarking comparison using SIMM-Dynamics Pipeline-SD/Fast and OpenSim platforms. The most substantial divergence results from differences in muscle model and actuator paths. This model is a valuable resource and is available for download by other researchers. The model, data, and simulation results presented here can be used by future researchers to benchmark other software platforms and software upgrades for these two platforms.
Beta power was conserved during resting and forward walking states and was attenuated in a voltage-dependent manner during 140-Hz DBS. Phenotype may be an important consideration if this is used for closed-loop DBS.
Freezing of gait (FOG) is a devastating axial motor symptom in Parkinson's disease (PD) leading to falls, institutionalization, and even death. The response of FOG to dopaminergic medication and deep brain stimulation (DBS) is complex, variable, and yet to be optimized. Fundamental gaps in the knowledge of the underlying neurobiomechanical mechanisms of FOG render this symptom one of the unsolved challenges in the treatment of PD. Subcortical neural mechanisms of gait impairment and FOG in PD are largely unknown due to the challenge of accessing deep brain circuitry and measuring neural signals in real time in freely-moving subjects. Additionally, there is a lack of gait tasks that reliably elicit FOG. Since FOG is episodic, we hypothesized that dynamic features of subthalamic (STN) beta oscillations, or beta bursts, may contribute to the Freezer phenotype in PD during gait tasks that elicit FOG. We also investigated whether STN DBS at 60 Hz or 140 Hz affected beta burst dynamics and gait impairment differently in Freezers and Non-Freezers. Synchronized STN local field potentials, from an implanted, sensing neurostimulator (Activa® PC + S, Medtronic, Inc.), and gait kinematics were recorded in 12 PD subjects, off-medication during forward walking and stepping-in-place tasks under the following randomly presented conditions: NO, 60 Hz, and 140 Hz DBS. Prolonged movement band beta burst durations differentiated Freezers from Non-Freezers, were a pathological neural feature of FOG and were shortened during DBS which improved gait. Normal gait parameters, accompanied by shorter bursts in Non-Freezers, were unchanged during DBS. The difference between the mean burst duration between hemispheres (STNs) of all individuals strongly correlated with the difference in stride time between their legs but there was no correlation between mean burst duration of each STN and stride time of the contralateral leg, suggesting an interaction between hemispheres influences gait. These results suggest that prolonged STN beta burst durations measured during gait is an important biomarker for FOG and that STN DBS modulated long not short burst durations, thereby acting to restore physiological sensorimotor information processing, while improving gait.
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