Neuromuscular Noise Research Articles

Is there sufficient evidence to explain the cause of sexually dimorphic behaviour in force steadiness?

Neuromuscular noise is a determining factor in the control of isometric force steadiness (FS), quantified as coefficient of variation (CV) of force around a preestablished target output. In this paper we examine sex-related differences of neural, muscular, and tendon influences on neuromuscular noise to understand FS in females and males. We use evidence from the literature to identify that CV of force is higher in females compared with males in the upper and lower body, with sex-related differences becoming less apparent with increasing age. Evaluation of sex-related physiology in tandem with results from FS studies indicate that differences in fibre type, contractile properties, and number of motor units (MUs) are unlikely contributors to differences in FS between females and males. MU type, behaviour of the population (inclusive of number of active MUs from the population), agonist-antagonist activity, maximal strength, and tendon mechanics are probable contributors to sexually dimorphic behaviour in FS. To clearly determine underlying causes of sex-related differences in FS, further study and reporting between females and males is required. Females and males are included in many studies; however, rich data on sexually dimorphic behaviour is lost when data are collapsed across sex or identified as nonsignificant without supporting values. This poses a challenge to identifying the underlying cause of females having higher CV of force than males. This review provides evidence of sexually dimorphic behaviour in FS and suggests that physiological differences between females and males effect neuromuscular noise, and in-turn contribute to sex-related differences in FS.

Age-Related Modifications to the Magnitude and Periodicity of Neuromuscular Noise

BackgroundEvaluation of task related outcomes within geriatric and fall-prone populations is essential not only for identification of neuromuscular deficits, but also for effective implementation of fall prevention strategies. As most tasks and activities of daily living are performed at submaximal force levels, restoration of muscle strength often does not produce the expected benefit in functional capacity. However, it is known that muscular control plays a key role in the performance of functional tasks, but it remains unclear to what degree muscular control and the associated neuromuscular noise (NmN) is age-related, particularly in the lower-extremities.ObjectivesThe aim of this study was to determine the effects of age and fall-pathology on the magnitude as well as the frequency of NmN during lower extremity force production.MethodsSixteen young healthy adults, as well as seventy elderly women (36 healthy, 34 elderly fallers), performed force production tests at moderate levels (15% of maximum voluntary isometric contractions).ResultsElderly fallers exhibited the highest magnitude of NmN, while the highest frequency components of NmN tended to occur in the healthy elderly. Young subjects exhibited significantly more power in the low frequency ranges than either of the elderly groups, and had the lowest levels of NmN.ConclusionThese data suggest increased degeneration of muscular control through greater NmN in elderly fallers compared to healthy elderly or young subjects. This could possibly be associated with muscle atrophy and lower levels of motor unit synchronisation.

Influence of neuromuscular noise and walking speed on fall risk and dynamic stability in a 3D dynamic walking model

Older adults and those with increased fall risk tend to walk slower. They may do this voluntarily to reduce their fall risk. However, both slower and faster walking speeds can predict increased risk of different types of falls. The mechanisms that contribute to fall risk across speeds are not well known. Faster walking requires greater forward propulsion, generated by larger muscle forces. However, greater muscle activation induces increased signal-dependent neuromuscular noise. These speed-related increases in neuromuscular noise may contribute to the increased fall risk observed at faster walking speeds. Using a 3D dynamic walking model, we systematically varied walking speed without and with physiologically-appropriate neuromuscular noise. We quantified how actual fall risk changed with gait speed, how neuromuscular noise affected speed-related changes in fall risk, and how well orbital and local dynamic stability measures predicted changes in fall risk across speeds. When we included physiologically-appropriate noise to the ‘push-off’ force in our model, fall risk increased with increasing walking speed. Changes in kinematic variability, orbital, and local dynamic stability did not predict these speed-related changes in fall risk. Thus, the increased neuromuscular variability that results from increased signal-dependent noise that is necessitated by the greater muscular force requirements of faster walking may contribute to the increased fall risk observed at faster walking speeds. The lower fall risk observed at slower speeds supports experimental evidence that slowing down can be an effective strategy to reduce fall risk. This may help explain the slower walking speeds observed in older adults and others.

Precision control of trunk movement in low back pain patients

Motor control is challenged in tasks with high precision demands. In such tasks, signal-dependent neuromuscular noise causes errors and proprioceptive feedback is required for optimal performance. Pain may affect proprioception, muscle activation patterns and resulting kinematics. Therefore, we investigated precision control of trunk movement in 18 low back pain (LBP) patients and 13 healthy control subjects. The subjects performed a spiral-tracking task requiring precise trunk movements, in conditions with and without disturbance of proprioception by lumbar muscle vibration. Tracking task performance and trunk muscle electromyography were recorded. In conditions without lumbar muscle vibration, tracking errors were 27.1% larger in LBP patients compared to healthy controls. Vibration caused tracking errors to increase by 10.5% in healthy controls, but not in LBP patients. These results suggest that reduced precision in LBP patients might be explained by proprioceptive deficits. Ratios of antagonistic over agonistic muscle activation were similar between groups. Tracking errors increased trunk inclination, but no significant relation between tracking error and agonistic muscle activation was found. Tracking errors did not decrease when antagonistic muscle activation increased, so, neither healthy subjects nor LBP patients appear to counteract trunk movement errors by increasing co-contraction.

Extreme Levels of Noise Constitute a Key Neuromuscular Deficit in the Elderly

Fluctuations during isometric force production tasks occur due to the inability of musculature to generate purely constant submaximal forces and are considered to be an estimation of neuromuscular noise. The human sensori-motor system regulates complex interactions between multiple afferent and efferent systems, which results in variability during functional task performance. Since muscles are the only active component of the motor system, it therefore seems reasonable that neuromuscular noise plays a key role in governing variability during both standing and walking. Seventy elderly women (including 34 fallers) performed multiple repetitions of isometric force production, quiet standing and walking tasks. No relationship between neuromuscular noise and functional task performance was observed in either the faller or the non-faller cohorts. When classified into groups with either nominal (group NOM, 25th –75th percentile) or extreme (either too high or too low, group EXT) levels of neuromuscular noise, group NOM demonstrated a clear association (r2>0.23, p<0.05) between neuromuscular noise and variability during task performance. On the other hand, group EXT demonstrated no such relationship, but also tended to walk slower, and had lower stride lengths, as well as lower isometric strength. These results suggest that neuromuscular noise is related to the quality of both static and dynamic functional task performance, but also that extreme levels of neuromuscular noise constitute a key neuromuscular deficit in the elderly.

Proximal Versus Distal Control of Two-Joint Planar Reaching Movements in the Presence of Neuromuscular Noise

Determining how the human nervous system contends with neuro-motor noise is vital to understanding how humans achieve accurate goal-directed movements. Experimentally, people learning skilled tasks tend to reduce variability in distal joint movements more than in proximal joint movements. This suggests that they might be imposing greater control over distal joints than proximal joints. However, the reasons for this remain unclear, largely because it is not experimentally possible to directly manipulate either the noise or the control at each joint independently. Therefore, this study used a 2 degree-of-freedom torque driven arm model to determine how different combinations of noise and/or control independently applied at each joint affected the reaching accuracy and the total work required to make the movement. Signal-dependent noise was simultaneously and independently added to the shoulder and elbow torques to induce endpoint errors during planar reaching. Feedback control was then applied, independently and jointly, at each joint to reduce endpoint error due to the added neuromuscular noise. Movement direction and the inertia distribution along the arm were varied to quantify how these biomechanical variations affected the system performance. Endpoint error and total net work were computed as dependent measures. When each joint was independently subjected to noise in the absence of control, endpoint errors were more sensitive to distal (elbow) noise than to proximal (shoulder) noise for nearly all combinations of reaching direction and inertia ratio. The effects of distal noise on endpoint errors were more pronounced when inertia was distributed more toward the forearm. In contrast, the total net work decreased as mass was shifted to the upper arm for reaching movements in all directions. When noise was present at both joints and joint control was implemented, controlling the distal joint alone reduced endpoint errors more than controlling the proximal joint alone for nearly all combinations of reaching direction and inertia ratio. Applying control only at the distal joint was more effective at reducing endpoint errors when more of the mass was more proximally distributed. Likewise, controlling the distal joint alone required less total net work than controlling the proximal joint alone for nearly all combinations of reaching distance and inertia ratio. It is more efficient to reduce endpoint error and energetic cost by selectively applying control to reduce variability in the distal joint than the proximal joint. The reasons for this arise from the biomechanical configuration of the arm itself.

Influence of simulated neuromuscular noise on the dynamic stability and fall risk of a 3D dynamic walking model

Measures that can predict risk of falling are essential for enrollment of older adults into fall prevention programs. Local and orbital stability directly quantify responses to very small perturbations and are therefore putative candidates for predicting fall risk. However, research to date is not conclusive on whether and how these measures relate to fall risk. Testing this empirically would be time consuming or may require high risk tripping experiments. Simulation studies therefore provide an important tool to initially explore potential measures to predict fall risk. This study performed simulations with a 3D dynamic walking model to explore if and how dynamic stability measures predict fall risk. The model incorporated a lateral step controller to maintain lateral stability. Neuronal noise of increasing amplitude was added to this controller to manipulate fall risk. Short-term (λS⁎) local instability did predict fall risk, but long-term (λL⁎) local instability and orbital stability (maxFM) did not. Additionally, λS⁎ was an early predictor for fall risk as it started increasing before fall risk increased. Therefore, λS⁎ could be a very useful tool to identify older adults whose fall risk is about to increase, so they can be enrolled in fall prevention programs before they actually fall.

Influence of simulated neuromuscular noise on movement variability and fall risk in a 3D dynamic walking model

People at risk of falling exhibit increased gait variability, which may predict future falls. However, the causal mechanisms underlying these correlations are not well known. Increased neuronal noise associated with aging likely leads to increased gait variability, which could in turn lead to increased fall risk. This paper presents a model of how changes in neuromuscular noise independently affect gait variability and probability of falling, and aims to determine the extent to which changes in gait variability directly predict fall risk. We used a dynamic walking model that incorporates a lateral step controller to maintain lateral stability. Noise was applied to this controller to approximate neuromuscular noise in humans. Noise amplitude was varied between low amplitudes that did not induce falls and high amplitudes for which the model always fell. With increases in noise amplitude, the model fell more often and after fewer steps. Gait variability increased with noise amplitude and predicted increased probability of falling. Importantly, these relationships were not linear. At either low gait variability or very high gait variability, small increases in noise and variability affected probability of falling very little. Conversely, at intermediate noise and/or variability levels, the same small increases resulted in large increases in probability of falling. Our results validate the idea that age-related increases in neuromuscular noise likely play a direct contributing role in increasing fall risk. However, neuromuscular noise remains only one of many important factors that need to be considered. These findings have important implications for fall prevention research and practice.

The curvature and variability of wrist and arm movements

The control of wrist rotations is critical for normal upper limb function, yet has received little attention. In this study, we characterized path shape of wrist rotations in order to better understand the biomechanical and neural factors governing their control. Subjects performed step-tracking wrist rotations in eight directions "at a comfortable speed" and "as fast as possible." For comparison, we also analyzed subjects' arm movement paths in a similar task. We found significant differences between wrist and arm movements. Wrist paths were more curved and more variable than arm paths (p < 0.001). The increased curvature and variability can be explained in part by neuromuscular noise (in actuation and sensing) which is known to increase from proximal to distal in the upper limb. The curvature and variability of wrist paths increased with movement speed (p < 0.001), further implicating (signal-dependent) noise. However, noise cannot explain all of our observations. For example, we found that wrist rotations exhibit a systematic pattern: outbound and inbound paths between the same two targets tend to veer to opposite sides of a straight line. We provide evidence indicating that this type of systematic pattern is not likely caused by noise or other neural causes, but may be explained by the unique biomechanics of the wrist.

Limb Stiffness Is Modulated With Spatial Accuracy Requirements During Movement in the Absence of Destabilizing Forces

The motor system can use a number of mechanisms to increase movement accuracy and compensate for perturbing external forces, interaction torques, and neuromuscular noise. Empirical studies have shown that stiffness modulation is one adaptive mechanism used to control arm movements in the presence of destabilizing external force loads. Other work has shown that arm muscle activity is increased at movement end for reaching movements to small visual targets and that changes in stiffness at movement end are oriented to match changes in visual accuracy requirements such as target shape. In this study, we assess whether limb stiffness is modulated to match spatial accuracy requirements during movement, conveyed using visual stimuli, in the absence of external force loads. Limb stiffness was estimated in the middle of reaching movements to visual targets located at the end of a narrow (8 mm) or wide (8 cm) visual track. When greater movement accuracy was required, we observed modest but reliable increases in limb stiffness in a direction perpendicular to the track. These findings support the notion that the motor system uses stiffness control to augment movement accuracy during movement and does so in the absence of external unstable force loads, in response to changing accuracy requirements conveyed using visual cues.

Neural Control of Motion-to-Force Transitions with the Fingertip

The neural control of tasks such as rapid acquisition of precision pinch remains unknown. Therefore, we investigated the neural control of finger musculature when the index fingertip abruptly transitions from motion to static force production. Nine subjects produced a downward tapping motion followed by vertical fingertip force against a rigid surface. We simultaneously recorded three-dimensional fingertip force, plus the complete muscle coordination pattern using intramuscular electromyograms from all seven index finger muscles. We found that the muscle coordination pattern clearly switched from that for motion to that for isometric force approximately 65 ms before contact (p = 0.0004). Mathematical modeling and analysis revealed that the underlying neural control also switched between mutually incompatible strategies in a time-critical manner. Importantly, this abrupt switch in underlying neural control polluted fingertip force vector direction beyond what is explained by muscle activation-contraction dynamics and neuromuscular noise (p < or = 0.003). We further ruled out an impedance control strategy in a separate test showing no systematic change in initial force magnitude for catch trials where the tapping surface was surreptitiously lowered and raised (p = 0.93). We conclude that the nervous system predictively switches between mutually incompatible neural control strategies to bridge the abrupt transition in mechanical constraints between motion and static force. Moreover because the nervous system cannot switch between control strategies instantaneously or exactly, there arise physical limits to the accuracy of force production on contact. The need for such a neurally demanding and time-critical strategy for routine motion-to-force transitions with the fingertip may explain the existence of specialized neural circuits for the human hand.

A Central Source of Movement Variability

Movements are universally, sometimes frustratingly, variable. When such variability causes error, we typically assume that something went wrong during the movement. The same assumption is made by recent and influential models of motor control. These posit that the principal limit on repeatable performance is neuromuscular noise that corrupts movement as it occurs. An alternative hypothesis is that movement variability arises before movements begin, during motor preparation. We examined this possibility directly by recording the preparatory activity of single cortical neurons during a highly practiced reach task. Small variations in preparatory neural activity were predictive of small variations in the upcoming reach. Effect magnitudes were such that at least half of the observed movement variability likely had its source during motor preparation. Thus, even for a highly practiced task, the ability to repeatedly plan the same movement limits our ability to repeatedly execute the same movement.

Joint impedance attenuates neuro-muscular noise during target tracking

Joint impedance attenuates neuro-muscular noise during target tracking