Role and modulation of various spinal pathways for human upper limb control in different gravity conditions

Abstract

Humans can perform movements in various physical environments and positions (corresponding to different experienced gravity), requiring the interaction of the musculoskeletal system, the neural system and the external environment. The neural system is itself comprised of several interactive components, from the brain mainly conducting motor planning, to the spinal cord (SC) implementing its own motor control centres through sensory reflexes. Nevertheless, it remains unclear whether similar movements in various environmental dynamics necessitate adapting modulation at the brain level, correcting modulation at the spinal level, or both. Here, we addressed this question by focusing on upper limb motor control in various gravity conditions (magnitudes and directions) and using neuromusculoskeletal simulation tools. We integrated supraspinal sinusoidal commands with a modular SC model controlling a musculoskeletal model to reproduce various recorded arm trajectories (kinematics and EMGs) in different contexts. We first studied the role of various spinal pathways (such as stretch reflexes) in movement smoothness and robustness against perturbation. Then, we optimised the supraspinal sinusoidal commands without and with a fixed SC model including stretch reflexes to reproduce a target trajectory in various gravity conditions. Inversely, we fixed the supraspinal commands and optimised the spinal synaptic strengths in the different environments. In the first optimisation context, the presence of SC resulted in easier optimisation of the supraspinal commands (faster convergence, better performance). The main supraspinal commands modulation was found in the flexor sinusoid's amplitude, resp. frequency, to adapt to different gravity magnitudes, resp. directions. In the second optimisation context, the modulation of the spinal synaptic strengths also remarkably reproduced the target trajectory for the mild gravity changes. We highlighted that both strategies of modulation of the supraspinal commands or spinal stretch pathways can be used to control movements in different gravity environments. Our results thus support that the SC can assist gravity compensation.

Fig 1. Modular spinal model in various scenarios.

A) The modular spinal model received supraspinal commands and muscle sensory feedback (length, l_m, velocity, ${\dot{l}}_m$ and force F_m) from the musculoskeletal model from OpenSim [29]. Here the stretch reflex is represented as example. The spinal model then generated the final muscle excitation signals (u_m) actuating the musculoskeletal model. In the first scenario (S1), supraspinal commands reproducing recorded trajectories were sent. In the second scenario (S2) an additional force perturbation was applied to the hand during the movement. Various spinal pathways with increasing spinal synaptic strengths (model 1 to N) were then evaluated in terms of movement smoothness and robustness against perturbation. B) In the third and fourth scenarios (S3 and S4), a “minimal SC” model comprising Ia-MN stretch reflex and Ia-INa reciprocal inhibition was considered. The supraspinal commands and spinal synaptic strengths were then optimised to reproduce a trajectory in various gravity conditions (magnitudes and directions, env 1 to N) to study supraspinal versus spinal modulation. C) Modeled spinal pathways: Ia-MN stretch reflex, Ia-INa reciprocal inhibition, Ia-MNs heteronymous stretch reflex, II stretch reflex, Ib Golgi tendon reflex and RN recurrent inhibition. The red stars indicate the connection strength that we explored in this study (the others were fixed).

Fig 2. Behaviour of the integrated model for various target trajectories.

A) CMA optimisation of the supraspinal sinusoidal commands for the flexion-extension trajectory without SC: from left to right the resulting loss over optimisation iterations, the final flexor and extensor supraspinal commands (cmd), and the resulting shoulder and elbow trajectories compared to the target for three optimisation runs. B) Same with our “minimal SC”, highlighted with a red frame. C) Resulting muscle activation: activation time windows are compared with recorded EMG activation time windows for flexor and extensor muscles, for both scenarios. D) Optimisation of the supraspinal sinusoidal commands for the circular trajectory with our “minimal SC”.

Fig 3. Role of various spinal pathways in voluntary movements.

A) Shoulder and elbow kinematics for the flexion-extension trajectory with the Ia-MN stretch reflex with increasing synaptic strength. B) Resulting flexor and extensor muscle activation for the maximal Ia-MN synaptic strength and the activation time windows comparison with recorded EMG. C) Metrics for the six spinal pathways with increasing synaptic strength: root mean square error (RMSE) to the target trajectory, elbow speed arc length (SAL) as smoothness metrics, and EMG time window overlap. D) Perturbation study for the circular trajectory: an additional force perturbation was applied to the hand during the movement. The resulting elbow kinematic is showed for Ia-MN pathway, and the deviation to the initial trajectory is plotted for the six pathways with increasing synaptic strength. E) Ia-MN—Ia-INa pair analysis: the two pathways are combined to study their interaction.

Fig 4. Modulation of the supraspinal commands in various gravity conditions.

A) Sketch of the 7 gravity environment applied in this study; 4 different magnitudes and 4 different directions. B) Resulting flexion-extension trajectories without optimisation; namely with the supraspinal commands from the scenario with “minimal SC” in normal gravity represented on Fig 2B. C) Optimisation of the supraspinal commands in various gravity magnitudes without SC: from left to right the resulting loss over optimisation iterations, the final flexor and extensor supraspinal commands (cmd), and the resulting shoulder and elbow trajectories compared to the target. D) Same in various gravity directions. E, F) Same for the scenario with our “minimal SC”, highlighted with a red frame.

Fig 5. Modulation of the spinal pathways in various gravity conditions.

A) Optimisation of the spinal synaptic strengths to reproduce the flexion-extension baseline: from left to right the resulting loss over optimisation iterations, the final flexor and extensor spinal synaptic strengths, and the resulting elbow trajectories compared to the target. B) Same for various gravity magnitudes. C) Same for various gravity directions.