On the Origin of Muscle Synergies: Invariant Balance in the Co-activation of Agonist and Antagonist Muscle Pairs

Abstract

Investigation of neural representation of movement planning has attracted the attention of neuroscientists, as it may reveal the sensorimotor transformation essential to motor control. The analysis of muscle synergies based on the activity of agonist–antagonist (AA) muscle pairs may provide insight into such transformations, especially for a reference frame in the muscle space. In this study, we examined the AA concept using the following explanatory variables: the AA ratio, which is related to the equilibrium-joint angle, and the AA sum, which is associated with joint stiffness. We formulated muscle synergies as a function of AA sums, positing that muscle synergies are composite units of mechanical impedance. The AA concept can be regarded as another form of the equilibrium-point (EP) hypothesis, and it can be extended to the concept of EP-based synergies. We introduce, here, a novel tool for analyzing the neurological and motor functions underlying human movements and review some initial insights from our results about the relationships between muscle synergies, endpoint stiffness, and virtual trajectories (time series of EP). Our results suggest that (1) muscle synergies reflect an invariant balance in the co-activation of AA muscle pairs; (2) each synergy represents the basis for the radial, tangential, and null movements of the virtual trajectory in the polar coordinates centered on the specific joint at the base of the body; and (3) the alteration of muscle synergies (for example, due to spasticity or rigidity following neurological injury) results in significant distortion of endpoint stiffness and concomitant virtual trajectories. These results indicate that muscle synergies (i.e., the balance of muscle mechanical impedance) are essential for motor control.

Motor primitives are determined in early development and are then robustly conserved into adulthood

“…These were likely learned as the rats transitioned from crawling to parasagittal walking patterns between P14 and P21. The construction of bipedal motor behaviors in humans might conceivably cause synergies expressed in walking and running in ablebodied adults to depart still further from the early default synergies or show more pervasive individual variations and suppressions than in the rats (36)(37)(38)50). Our work here suggests that a core set of synergies in common in all individuals may nonetheless underlie aspects of these variations (27,37,44,49).…”

Muscle coactivation: definitions, mechanisms, and functions

“…Patients with a variety of neurological disorders show increased levels of muscle coactivation. In particular, increased coactivation has been described as typical of Parkinsonian rigidity (Arias et al 2012;Hirai et al 2015), spasticity of both spinal and supraspinal origin (Hammond et al 1988;Hirai et al 2015;Rinaldi et al 2017), cerebral palsy (Richards and Malouin 2013), dystonic disorders (Hughes and McLellan 1985), vestibular disorders (Keshner et al 1987), cerebellar disorders (Mari et al 2014), and stroke (Kitatani et al 2016). In particular, Rinaldi et al (2017) have documented correlation between indices of muscle coactivation and the Ashworth index of spasticity.…”

Toward adaptive deep brain stimulation for dystonia

“…6 However, at present, an AA sum or AA ratio is not yet specific enough to differentiate signals of pathological contractions from voluntary contractions. 23 In the future, evaluation of the predictive value of combined signals through machine learning may lead to greater specificity.…”