A Simulation Study to Examine the Effect of Common Motoneuron Inputs on Correlated Patterns of Motor Unit Discharge

Abstract

The influence of common oscillatory inputs to the motoneuron pool on correlated patterns of motor unit discharge was examined using model simulations. Motor unit synchronization, in-phase fluctuations in mean firing rates known as 'common drive', and the coefficient of variation of the muscle force were examined as the frequency and amplitude of common oscillatory inputs to the motoneuron pool were varied. The amount of synchronization, the peak correlation between mean firing rates and the coefficient of variation of the force varied with both the frequency and amplitude of the common input signal. Values for 'common drive' and the force coefficient of variation were highest for oscillatory inputs at frequencies less than 5 Hz, while synchronization reached a maximum when the frequency of the common input was close to the average motor unit firing rate. The frequency of the common input signal for which the highest levels of synchronization were observed increased as motoneuron firing rates increased in response to higher target force levels. The simulation results suggest that common low-frequency oscillations in motor unit firing rates and short-term synchronization result from oscillatory activity in different bands of the frequency spectrum of shared motoneuron inputs. The results also indicate that the amount of synchronization between motor unit discharges depends not only on the amplitude of the shared input signal, but also on its frequency in relation to the present firing rates of the individual motor units.

Jaw tremor as a physiological biomarker of bruxism

“…The larger 8 Hz tremor magnitude observed by Sowman et al (2008) for descending ramps relative to ascending ramps was suggested to stem from increased synchronization of motor units by a tremor-generating synaptic input. Sowman et al (2008) discussed possible mechanisms for this related to changes in motor unit firing rates (Matthews, 1997;Lowery and Erim, 2005) and potential differences in afferent feedback between contraction types (Semmler et al, 2002). For the purposes of the present study, we were particularly interested in the possible influence of afferent feedback, since it may be abnormal in patients with bruxism (Mäntyvaara et al, 1999;Suganuma et al, 2007), and because patients with bruxism appear to have normal masseter motor unit activation properties, when tested under the same task conditions used in the present study (D'Amico et al, 2013).…”

Motor Unit Synchronization Is Increased in Biceps Brachii After Exercise-Induced Damage to Elbow Flexor Muscles

“…We tested a large sample of biceps brachii motor units before eccentric exercise, and at two time-points after eccentric exercise, in an attempt to distinguish between effects associated with fatigue and muscle damage (immediately after) and muscle damage alone (24 h after). Recent computational models of motor unit activity have indicated that motor unit synchronization can increase EMG and force fluctuations (Lowery and Erim 2005;Yao et al 2000;Zhou and Rymer 2004), which may contribute to the increased EMG and force fluctuations that have been observed during low force contractions after eccentric exercise (Leger and Milner 2001a;Semmler et al 2007;Weerakkody et al 2003). We therefore expected to see enhanced motor unit synchronization and coherence immediately after eccentric exercise that returned to baseline levels 24 h later.…”

“…Along with motor unit recruitment and rate modulation, the correlated activity of motor units is now regarded as an important physiological principle that regulates the mechanical output of a muscle, and has been included in many recent computational models of motor unit activity (Lowery and Erim 2005;Yao et al 2000;Zhou and Rymer 2004). The correlated discharge of action potentials by motor neurons is caused by common synaptic input that is delivered through branched presynaptic inputs or by oscillatory drive from supraspinal sources (Farmer et al 1993a,b;Sears and Stagg 1976).…”

Simulation system of spinal cord motor nuclei and associated nerves and muscles, in a Web-based architecture

“…However, some level of customization is required with the intention of performing complex simulations or in the development of a simulation system. On the other hand, more focused approaches have been adopted by research groups interested in answering specific questions in spinal cord investigation, which meant developing their own simulators, without a goal of general usage (Capaday and Stein 1987;Maltenfort et al 1998;Nussbaumer et al 2002;Ivashko et al 2003;Lowery and Erim 2005;Subramanian et al 2005;Stienen et al 2007;Uchiyama and Windhorst 2007). Bashor's (1998) spinal network simulator was based on MacGregor's implementations in Fortran of neuronal, synaptic and network models (MacGregor 1987).…”

“…A very detailed interneuronal network contributes to the modulation of the motoneurons' spike trains. Lowery and Erim (2005) presented a simulation study of the effects of common oscillatory inputs on the correlated discharges of a pool of 100 motor units. The input command was realized by means of current injected in the soma and the outputs were muscle force and the spike trains of the motor-units.…”