How do strength and coordination recovery interact after stroke? A computational model for informing robotic training

Area of Science:

• Neuroscience
• Robotics
• Rehabilitation

Background:

• Robotic devices offer potential for training motor skills like strength and coordination.
• The interplay between strength and coordination recovery after neurological injury, such as stroke, remains unclear.
• Optimizing robotic training requires understanding how focusing on one skill impacts the recovery of the other.

Purpose of the Study:

• To investigate the interaction between strength and coordination recovery following stroke using a computational neurorehabilitation model.
• To explore how different training reward signals influence the balance between strength and coordination.
• To provide a theoretical basis for adaptive robotic movement therapy.

Main Methods:

• Development of a computational neurorehabilitation model simulating motor system recovery.
• The model optimizes corticospinal and reticulospinal cell activity via reinforcement learning.
• Simulations involved finger movement and wheelchair propulsion tasks with varied strength-to-coordination reward weighting.

Main Results:

• The model predicted a nonlinear relationship between strength and coordination recovery, aligning with clinical observations.
• A potential competition between strength and coordination recovery was identified, linked to cell type scarcity post-stroke.
• Varying the reward signal demonstrated its influence on the balance of recovered motor skills.

Conclusions:

• Stroke-induced motor recovery may involve a trade-off between strength and coordination.
• Computational modeling offers insights into complex neurorehabilitation dynamics.
• Adaptive robotic therapy, adjusting the focus on force and coordination, could enhance post-stroke motor recovery.