Fast Oscillatory Commands from the Motor Cortex Can Be Decoded by the Spinal Cord for Force Control

Abstract

Oscillations in the beta and gamma bands (13-30 Hz; 35-70 Hz) have often been observed in motor cortical outputs that reach the spinal cord, acting on motoneurons and interneurons. However, the frequencies of these oscillations are above the muscle force frequency range. A current view is that the transformation of the motoneuron pool inputs into force is linear. For this reason possible roles for these oscillations are unclear, since if this transformation is linear, the high frequencies in the motoneuron inputs (e.g., 20 Hz from pyramidal tract neurons) would be filtered out by the muscle and have no effect on force control. A biologically inspired mathematical model of the neuromuscular system was used to investigate the impact of high-frequency cortical oscillatory activity on force control. The model simulation results evidenced that a typical motoneuron pool has a nonlinear behavior that enables the decoding of a high-frequency oscillatory input. An input at a single frequency (e.g., beta band) leads to an increase in the steady-state force generated by the muscle. When the input oscillation was amplitude modulated at a given low frequency, the force oscillated at this frequency. In both cases, the mechanism relies on the recruitment and derecruitment of motor units in response to the oscillatory descending drive. Therefore, the results from this study suggest a potential role in force control for cortical oscillations at frequencies at or above the beta band, despite the low-pass behavior of the muscles.

The human central nervous system transmits common synaptic inputs to distinct motor neuron pools during non‐synergistic digit actions

“…Coherence in the delta, alpha and beta band has been linked to both spinal (Vallbo & Wessberg, 1993;Baker, 2002;Williams & Baker, 2009;Farina et al 2014) and supraspinal inputs (Farmer et al 1993;Baker et al 1997;Salenius et al 1997;Watanabe & Kohn, 2015). The commonality in the output of the FDI and thenar muscle motor neurons in the beta band could represent distributed neural drive to both pools of motor neurons from supraspinal circuitries that are sensitive to task requirements (Farmer et al 1993;Baker et al 1997;Salenius et al 1997).…”

“…The primary motor cortex generates activity at frequencies of ß10 and ß20 Hz, as revealed by corticomuscular coherence (Conway et al 1995;Baker et al 1997;Salenius et al 1997). Therefore, these inputs could contribute to common oscillations in motor neuronal activity by modulating interneuronal inputs to motor neurons, and/or by the non-linear conversion of these inputs to coherent motor neuron output at both the delta and the beta frequency (Watanabe & Kohn, 2015). Synchronized motor neuronal discharges, coupled with coherent suppressions of tremor frequencies by spinal loops, may be advantageous for performing accurate, precise force tasks because force variability is reduced with decreased variability in the common synaptic input to motor neurons (Feeney et al 2018), as discussed below.…”

Multiscale modeling of the neuromuscular system: Coupling neurophysiology and skeletal muscle mechanics

“…and the musculotendon unit (proprioception, joint dynamics, etc.). Recent applications of these biophysical neuromuscular models include the analysis of the force variability during steady isometric contractions (Dideriksen et al, ; Farina et al, ; Farina & Negro, ; Negro et al, ; Negro & Farina, ; Watanabe et al, ), postural sway (Elias, Watanabe, & Kohn, ) and nonlinear control of force oscillations (Watanabe & Kohn, , ).…”

High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation

“…Importantly, according to a recent computational investigation based on a biologically-inspired mathematical model of the behavior of a typical motoneuron (MN) pool (Watanabe and Kohn, 2015), high frequency neural oscillations to muscles may recruit a larger number of motoneurons available from a specific muscle pool which leads to a greater or similar muscle force production but at a lower energetic cost. Moreover, stronger high-frequency synchronization at motor unit level during dynamic in comparison to isometric contractions has been recently shown and linked to a neural optimization strategy for the musculoskeletal system during complex tasks (Mohr et al, 2015).…”

“…Thus, in later adaptation, coherent contributions between several muscles (i.e., increased IMC between pairs of muscles) functionally promote performance improvement through an optimal intermuscular coupling whilst maintaining a constant peak force production at a reduced energetic cost (Watanabe and Kohn, 2015). Consequently, performance improves by reducing the trajectory path error not via a further increase of gross EMG activity or force per se , but rather by increasing the “orchestrated” involvement of several upper limb muscles.…”