How does the CNS control arm reaching movements?Introducing a hierarchical nonlinear predictive control organization based on the idea of muscle synergies.

Sedigheh Dehghani,Fariba Bahrami,Kei Masani

doi:10.1371/journal.pone.0228726

Abstract

In this study, we introduce a hierarchical and modular computational model to explain how the CNS (Central Nervous System) controls arm reaching movement (ARM) in the frontal plane and under different conditions. The proposed hierarchical organization was established at three levels: 1) motor planning, 2) command production, and 3) motor execution. Since in this work we are not discussing motion learning, no learning procedure was considered in the model. Previous models mainly assume that the motor planning level produces the desired trajectories of the joints and feeds it to the next level to be tracked. In the proposed model, the motion control is described based on a regulatory control policy, that is, the output of the motor planning level is a step function defining the initial and final desired position of the hand. For the command production level, a nonlinear predictive model was developed to explain how the time-invariant muscle synergies (MSs) are recruited. We used the same computational model to explain the arm reaching motion for a combined ARM task. The combined ARM is defined as two successive ARM such that it starts from point A and reaches to point C via point B. To develop the model, kinematic and kinetic data from six subjects were recorded and analyzed during ARM task performance. The subjects used a robotic manipulator while moving their hand in the frontal plane. The EMG data of 15 muscles were also recorded. The MSs used in the model were extracted from the recorded EMG data. The proposed model explains two aspects of the motor control system by a novel computational approach: 1) the CNS reduces the dimension of the control space using the notion of MSs and thereby, avoids immense computational loads; 2) at the level of motor planning, the CNS generates the desired position of the hand at the starting, via and the final points, and this amounts to a regulatory and non-tracking structure.

Highlights

It is well-known that every joint is controlled by several muscles, each one having a specified role in motion generation at that joint
Since the implementation of different types of Arm Reaching Movements (ARMs) is considered in this research, it is necessary to evaluate the performance of the proposed model in the execution of these movements
For implementing the disturbance in simulation, we changed the hand position to the perturbed position indicated in Fig 2C with the red arrow as soon as the hand position reaches a distance of 2 cm from the midpoint

Summary

Introduction

It is well-known that every joint is controlled by several muscles, each one having a specified role in motion generation at that joint. Performance of any given movement in the external space is accomplished under several mechanical and anatomical constraints [1]. Bernstein suggested that a hierarchical and modular organization does exist for realizing any movement properly [2]. Based on this picture, some researchers suggested that at the highest level of this hierarchical structure motor planning is performed, and at a lower level, the corresponding motor command is produced, and at the lowest level, according to the musculoskeletal system of the limbs, the movement is executed [3,4]. The key question is whether a computational model for controlling Arm Reaching Movements (ARMs) in the vertical (frontal) plane with the above hierarchical organization can be developed that employs modular structure based on recruitment of Muscle Synergies (MSs)

Results

Discussion

Conclusion