The optimal neural strategy for a stable motor task requires a compromise between level of muscle cocontraction and synaptic gain of afferent feedback

Abstract

Dideriksen JL, Negro F, Farina D. The optimal neural strategy for a stable motor task requires a compromise between level of muscle cocontraction and synaptic gain of afferent feedback. J Neurophysiol 114: 1895-1911, 2015. First published July 22, 2015 doi:10.1152/jn.00247.2015.-Increasing joint stiffness by cocontraction of antagonist muscles and compensatory reflexes are neural strategies to minimize the impact of unexpected perturbations on movement. Combining these strategies, however, may compromise steadiness, as elements of the afferent input to motor pools innervating antagonist muscles are inherently negatively correlated. Consequently, a high afferent gain and active contractions of both muscles may imply negatively correlated neural drives to the muscles and thus an unstable limb position. This hypothesis was systematically explored with a novel computational model of the peripheral nervous system and the mechanics of one limb. Two populations of motor neurons received synaptic input from descending drive, spinal interneurons, and afferent feedback. Muscle force, simulated based on motor unit activity, determined limb movement that gave rise to afferent feedback from muscle spindles and Golgi tendon organs. The results indicated that optimal steadiness was achieved with low synaptic gain of the afferent feedback. High afferent gains during cocontraction implied increased levels of common drive in the motor neuron outputs, which were negatively correlated across the two populations, constraining instability of the limb. Increasing the force acting on the joint and the afferent gain both effectively minimized the impact of an external perturbation, and suboptimal adjustment of the afferent gain could be compensated by muscle cocontraction. These observations show that selection of the strategy for a given contraction implies a compromise between steadiness and effectiveness of compensations to perturbations. This indicates that a task-dependent selection of neural strategy for steadiness is necessary when acting in different environments.

Voluntary activation and variability during maximal dynamic contractions with aging

“…A higher level of coactivation limits the potential torque at the joint and may contribute to an age-related difference in strength of agonist muscles (Macaluso et al 2002). Increased coactivation can also increase joint stiffness and thus reduce the impact of perturbations during joint movement (Gribble et al 2003; Dideriksen et al 2015) and this is consistent with old adults increasing the activation of antagonist muscles during dynamic contractions to stabilize the joint during movement.…”

The primary afferent activity cannot capture the dynamical features of muscle activity during reaching movements

“…Altering the sensitivity of muscle spindle to muscle length and its rate of change in simulations was not sufficient to reshape the primary afferent activity to reflect muscle activity features. Altogether, these results suggest that to solve the neuromechanical problem, the CNS controls limb dynamics through dynamics-dependent co-activation of muscles and non-linear modulation of monosynaptic primary afferent feedback (Roberts et al, 2008) (Perez et al, 2007) (Dideriksen et al, 2015).…”

“…This is due in part to the complexity of the sensorimotor control loop. The prevailing theory of motor control is that the CNS embeds complex mechanical limb dynamics in order to shape control signals and incorporate sensory feedback (Kluzik et al, 2008;Kurtzer et al, 2008;Wagner and Smith, 2008;Dideriksen et al, 2015). This embedding at the supra-spinal level is often referred to as internal models (Kawato et al, 1987), which can be observed, for example, as dynamical units in the primary motor cortex (Churchland et al, 2012).…”

Aging Changes the Contribution of Spinal and Corticospinal Pathways to Control Balance

“…The reciprocal changes between Ia presynaptic inhibition and antagonist coactivation may reflect a strategy that consists of decreasing the contribution of the inputs from the muscle spindle afferents and increasing the reliance on coactivation to control the active stiffness of the ankle. This would be mechanically relevant because high reflex gain involves an inherent instability when maintaining a steady contraction, in particular, in the presence of antagonist coactivation (7). This interpretation is supported further by the observation of greater coactivation of agonist and antagonist in deafferented than in healthy subjects, suggesting a strategy based on controlling muscle activity with inputs from descending pathways when proprioceptive inputs are altered (27).…”