Simulating the impact of sensorimotor deficits on reaching performance

Area of Science:

• Neuroscience
• Biomechanics
• Robotics

Background:

• The healthy nervous system achieves robust motor control despite complex dynamics.
• Stroke often leads to impaired motor function, particularly in upper limb reaching.
• Understanding specific sensorimotor deficits post-stroke is crucial for rehabilitation.

Purpose of the Study:

• To model neural control of human upper limb reaching.
• To investigate the impact of specific sensorimotor impairments on reaching performance.
• To identify the primary cause of post-stroke motor impairment.

Main Methods:

• Developed a near-optimal feedback control model of a two-degree-of-freedom human upper limb system.
• Incorporated biologically relevant parameters and introduced three common post-stroke deficits: abnormal joint coupling, increased internal model noise, and muscular weakness.
• Analyzed the effects of these perturbations on reaching trajectories, duration, and accuracy.

Main Results:

• Unmodeled abnormal joint coupling caused significant trajectory perturbations, increased reach duration, and target overshoot.
• Increased internal model noise and muscular weakness had minimal effects on performance unless noise was drastically amplified.
• Simulated reaches with abnormal coupling mimicked features observed in hemiparetic stroke survivors' movements.

Conclusions:

• Abnormal joint coupling, particularly when unmodeled, is a primary driver of motor control deficits after stroke.
• The model's sensitivity to abnormal coupling aligns with experimental evidence suggesting it's a key factor in post-stroke motor impairment.
• Internal model errors related to joint coupling may underlie observed motor control issues in hemiparetic individuals.