Investigating reduction of dimensionality during single-joint elbow movements: a case study on muscle synergies

Abstract

A long standing hypothesis in the neuroscience community is that the central nervous system (CNS) generates the muscle activities to accomplish movements by combining a relatively small number of stereotyped patterns of muscle activations, often referred to as “muscle synergies.” Different definitions of synergies have been given in the literature. The most well-known are those of synchronous, time-varying and temporal muscle synergies. Each one of them is based on a different mathematical model used to factor some EMG array recordings collected during the execution of variety of motor tasks into a well-determined spatial, temporal or spatio-temporal organization. This plurality of definitions and their separate application to complex tasks have so far complicated the comparison and interpretation of the results obtained across studies, and it has always remained unclear why and when one synergistic decomposition should be preferred to another one. By using well-understood motor tasks such as elbow flexions and extensions, we aimed in this study to clarify better what are the motor features characterized by each kind of decomposition and to assess whether, when and why one of them should be preferred to the others. We found that three temporal synergies, each one of them accounting for specific temporal phases of the movements could account for the majority of the data variation. Similar performances could be achieved by two synchronous synergies, encoding the agonist-antagonist nature of the two muscles considered, and by two time-varying muscle synergies, encoding each one a task-related feature of the elbow movements, specifically their direction. Our findings support the notion that each EMG decomposition provides a set of well-interpretable muscle synergies, identifying reduction of dimensionality in different aspects of the movements. Taken together, our findings suggest that all decompositions are not equivalent and may imply different neurophysiological substrates to be implemented.

Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives

“…The various muscle synergy models can be distinguished based on the mathematical formalization of this combination, and they are described in the following (see Figure 2 for a schematic representation). An empirical comparison of these models is proposed by Chiovetto et al (2013). …”

Evaluation of Functional Correlation of Task-Specific Muscle Synergies with Motor Performance in Patients Poststroke

“…To evaluate the goodness of EMG reconstruction, the criterion of variance account for (VAF) (27, 29, 33, 39, 50) was adopted here in the following equation: $\text{VAF}=1-(||M-D|{|}^2/\left|\right|M-\text{mean }(M)|{|}^2)$…”

A neuromuscular electrical stimulation strategy based on muscle synergy for stroke rehabilitation

“…In recent years a theory that has gained strong acceptance is the concept of muscle synergies where a modular and coordinated activation of muscles is encoded by a control signal from the CNS that eventually will lead to a specific movement [4][5][6]. The extraction of muscle synergies can be reached through different algorithms, in this research work Non-negative Matrix Factorization (NMF) was used since it has been considered a suitable approach according to the literature [7].…”

“…The most commonly used of these approaches are known as, temporal, synchronous and time varying muscle synergies [4][5][6]. This method was used in our studies to obtained patterns of muscle synergies.…”