Neck muscle biomechanics and neural control

Abstract

The mechanics, morphometry, and geometry of our joints, segments, and muscles are fundamental biomechanical properties intrinsic to human neural control. The goal of our study was to investigate whether the biomechanical actions of individual neck muscles predict their neural control. Specifically, we compared the moment direction and variability produced by electrical stimulation of a neck muscle (biomechanics) to the preferred activation direction and variability (neural control). Subjects sat upright with their head fixed to a six-axis load cell and their torso restrained. Indwelling wire electrodes were placed into the sternocleidomastoid (SCM), splenius capitis (SPL), and semispinalis capitis (SSC) muscles. The electrically stimulated direction was defined as the moment direction produced when a current (2–19 mA) was passed through each muscle’s electrodes. Preferred activation direction was defined as the vector sum of the spatial tuning curve built from root mean squared electromyogram when subjects produced isometric moments at 7.5% and 15% of their maximum voluntary contraction (MVC) in 26 three-dimensional directions. The spatial tuning curves at 15% MVC were well defined (unimodal, P < 0.05), and their preferred directions were 23°, 39°, and 21° different from their electrically stimulated directions for the SCM, SPL, and SSC, respectively ( P < 0.05). Intrasubject variability was smaller in electrically stimulated moment directions compared with voluntary preferred directions, and intrasubject variability decreased with increased activation levels. Our findings show that the neural control of neck muscles is not based solely on optimizing individual muscle biomechanics but, as activation increases, biomechanical constraints in part dictate the activation of synergistic neck muscles. NEW & NOTEWORTHY Biomechanics are an intrinsic part of human neural control. In this study, we found that the biomechanics of individual neck muscles cannot fully predict their neural control. Consequently, physiologically based computational neck muscle controllers cannot calculate muscle activation schemes based on the isolated biomechanics of muscles. Furthermore, by measuring biomechanics we showed that the intrasubject variability of the neural control was lower for electrical vs. voluntary activation of the neck muscles.