A review of recent applications of cross-correlation methodologies to human motor unit recording

Synaptic inputs to motor neurons underlying muscle coactivation for functionally different tasks have different spectral characteristics

The central nervous system (CNS) may produce the same endpoint trajectory or torque profile with different muscle activation patterns. What differentiates these patterns is the presence of cocontraction, which does not contribute to effective torque generation but allows to modulate joints' mechanical stiffness. Although it has been suggested that the generation of force and the modulation of stiffness rely on separate pathways, a characterization of the differences between the synaptic inputs to motor neurons (MNs) underlying these tasks is still missing. In this study, participants coactivated the same pair of upper-limb muscles, i.e., the biceps brachii and the triceps brachii, to perform two functionally different tasks: limb stiffness modulation or endpoint force generation. Spike trains of MNs were identified through decomposition of high-density electromyograms (EMGs) collected from the two muscles. Cross-correlogram showed a higher synchronization between MNs recruited to modulate stiffness, whereas cross-muscle coherence analysis revealed peaks in the β-band, which is commonly ascribed to a cortical origin. These peaks did not appear during the coactivation for force generation, thus suggesting separate cortical inputs for stiffness modulation. Moreover, a within-muscle coherence analysis identified two subsets of MNs that were selectively recruited to generate force or regulate stiffness. This study is the first to highlight different characteristics, and probable different neural origins, of the synaptic inputs driving a pair of muscles under different functional conditions. We suggest that stiffness modulation is driven by cortical inputs that project to a separate set of MNs, supporting the existence of a separate pathway underlying the control of stiffness.NEW & NOTEWORTHY The characterization of the pathways underlying force generation or stiffness modulation are still unknown. In this study, we demonstrated that the common input to motor neurons of antagonist muscles shows a high-frequency component when muscles are coactivated to modulate stiffness but not to generate force. Our results provide novel insights on the neural strategies for the recruitment of multiple muscles by identifying specific spectral characteristics of the synaptic inputs underlying functionally different tasks.

Corticospinal drive is associated with temporal walking adaptation in both healthy young and older adults

Healthy aging is associated with reduced corticospinal drive to leg muscles during walking. Older adults also exhibit slower or reduced gait adaptation compared to young adults. The objective of this study was to determine age-related changes in the contribution of corticospinal drive to ankle muscles during walking adaptation. Electromyography (EMG) from the tibialis anterior (TA), soleus (SOL), medial, and lateral gastrocnemius (MGAS, LGAS) were recorded from 20 healthy young adults and 19 healthy older adults while they adapted walking on a split-belt treadmill. We quantified EMG-EMG coherence in the beta-gamma (15-45 Hz) and alpha-band (8-15 Hz) frequencies. Young adults demonstrated higher coherence in both the beta-gamma band coherence and alpha band coherence, although effect sizes were greater in the beta-gamma frequency. The results showed that slow leg TA-TA coherence in the beta-gamma band was the strongest predictor of early adaptation in double support time. In contrast, early adaptation in step length symmetry was predicted by age group alone. These findings suggest an important role of corticospinal drive in adapting interlimb timing during walking in both young and older adults.

Neural Control of Human Locomotor Adaptation: Lessons about Changes with Aging

Walking patterns are adaptable in response to different environmental demands, which requires neural input from spinal and supraspinal structures. With an increase in age, there are changes in walking adaptation and in the neural control of locomotion, but the age-related changes in the neural control of locomotor adaptation is unclear. The purpose of this narrative review is to establish a framework where the age-related changes of neural control of human locomotor adaptation can be understood in terms of reactive feedback and predictive feedforward control driven by sensory feedback during locomotion. We parse out the effects of aging on (a) reactive adaptation to split-belt walking, (b) predictive adaptation to split-belt walking, (c) reactive visuomotor adaptation, and (d) predictive visuomotor adaptation, and hypothesize that specific neural circuits are influenced differentially with age, which influence locomotor adaptation. The differences observed in the age-related changes in walking adaptation across different locomotor adaptation paradigms will be discussed in light of the age-related changes in the neural mechanisms underlying locomotion.

Intermuscular Coherence in the Presence of Electrical Stimulation

The nervous system uses oscillations to convey information efficiently. Inter-muscular coherence in the 15-35 Hz range is thought to represent common cortical drive to muscles, but is also in the frequency band in which electrical stimulation is applied to restore movement following neurological disease or injury. We wished to determine if, when stimulation is applied at the peak frequency of the coherence spectra it was still possible to determine voluntary effort. Using healthy human subjects we stimulated muscles in the arms and legs, separate experiments, while recording EMG activity from pairs of muscles including the stimulated muscles. Offline coherence analysis was performed. When stimulation is greater than motor threshold, and applied at the peak of the coherence spectra a new peak appears in the spectra, presumably representing a new frequency of oscillation within the nervous system. This does not appear at lower stimulation levels, or with lower frequencies. The nervous system is capable of switching oscillatory frequencies to account for noise in the environment.

Intermuscular coherence analysis in older adults reveals that gait-related arm swing drives lower limb muscles via subcortical and cortical pathways

KEY POINTS

Gait-related arm swing in humans supports efficient lower limb muscle activation, indicating a neural coupling between the upper and lower limbs during gait. Intermuscular coherence analyses of gait-related electromyography from upper and lower limbs in 20 healthy participants identified significant coherence in alpha and beta/gamma bands indicating that upper and lower limbs share common subcortical and cortical drivers that coordinate the rhythmic four-limb gait pattern. Additional directed connectivity analyses revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. The results provide a neural underpinning that arm swing may serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases.

ABSTRACT

Human gait benefits from arm swing, as it enhances efficient lower limb muscle activation in healthy participants as well as patients suffering from neurological impairment. The underlying neuronal mechanisms of such coupling between upper and lower limbs remain poorly understood. The aim of the present study was to examine this coupling by intermuscular coherence analysis during gait. Additionally, directed connectivity analysis of this coupling enabled assessment of whether gait-related arm swing indeed drives lower limb muscles. To that end, electromyography recordings were obtained from four lower limb muscles and two upper limb muscles bilaterally, during gait, of 20 healthy participants (mean (SD) age 67 (6.8) years). Intermuscular coherence analysis revealed functional coupling between upper and lower limb muscles in the alpha and beta/gamma band during muscle specific periods of the gait cycle. These effects in the alpha and beta/gamma bands indicate involvement of subcortical and cortical sources, respectively, that commonly drive the rhythmic four-limb gait pattern in an efficiently coordinated fashion. Directed connectivity analysis revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. This indicates that gait-related arm swing reflects the recruitment of neuronal support for optimizing the cyclic movement pattern of the lower limbs. These findings thus provide a neural underpinning for arm swing to potentially serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases.

Motoneurone synchronization for intercostal and abdominal muscles: interneurone influences in two different species

The contribution of branched-axon monosynaptic inputs in the generation of short-term synchronization of motoneurones remains uncertain. Here, synchronization was measured for intercostal and abdominal motoneurones supplying the lower thorax and upper abdomen, mostly showing expiratory discharges. Synchronization in the anaesthetized cat, where the motoneurones receive a strong direct descending drive, is compared with that in anaesthetized or decerebrate rats, where the direct descending drive is much weaker. In the cat, some examples could be explained by branched-axon monosynaptic inputs, but many others could not, by virtue of peaks in cross-correlation histograms whose widths (relatively wide) and timing indicated common inputs with more complex linkages, e.g., disynaptic excitatory. In contrast, in the rat, correlations for pairs of internal intercostal nerves were dominated by very narrow peaks, indicative of branched-axon monosynaptic inputs. However, the presence of activity in both inspiration and expiration in many of the nerves allowed additional synchronization measurements between internal and external intercostal nerves. Time courses of synchronization for these often consisted of combinations of peaks and troughs, which have never been previously described for motoneurone synchronization and which we interpret as indicating combinations of inputs, excitation of one group of motoneurones being common with either excitation or inhibition of the other. Significant species differences in the circuits controlling the motoneurones are indicated, but in both cases, the roles of spinal interneurones are emphasised. The results demonstrate the potential of motoneurone synchronization for investigating inhibition and have important general implications for the interpretation of neural connectivity measurements by cross-correlation.

motoRneuron: an open-source R toolbox for time-domain motor unit analyses

Motor unit synchronization is the tendency of motor neurons and their associated muscle fibers to discharge near-simultaneously. It has been theorized as a control mechanism for force generation by common excitatory inputs to these motor neurons. Magnitude of synchronization is calculated from peaks in cross-correlation histograms between motor unit discharge trains. However, there are many different methods for detecting these peaks and even more indices for calculating synchronization from them. Methodology is diverse, typically laboratory-specific and requires expensive software, like Matlab or LabView. This lack of standardization makes it difficult to draw definitive conclusions about motor unit synchronization. A free, open-source toolbox, "motoRneuron", for the R programming language, has been developed which contains functions for calculating time domain synchronization using different methods found in the literature. The objective of this paper is to detail the toolbox's functionality and present a case study showing how the same synchronization index can differ when different methods are used to compute it. A pair of motor unit action potential trains were collected from the forearm during a isometric finger flexion task using fine wire electromyography. The motoRneuron package was used to analyze the discharge time of the motor units for time-domain synchronization. The primary function "mu_synch" automatically performed the cross-correlation analysis using three different peak detection methods, the cumulative sum method, the z-score method, and a subjective visual method. As function parameters defined by the user, only first order recurrence intervals were calculated and a 1 ms bin width was used to create the cross correlation histogram. Output from the function were six common synchronization indices, the common input strength (CIS), k', k' - 1, E, S, and Synch Index. In general, there was a high degree of synchronization between the two motor units. However, there was a varying degree of synchronization between methods. For example, the widely used CIS index, which represents a rate of synchronized discharges, shows a 45% difference between the visual and z-score methods. This singular example demonstrates how a lack of consensus in motor unit synchronization methodologies may lead to substantially differing results between studies. The motoRneuron toolbox provides researchers with a standard interface and software to examine time-domain motor unit synchronization.

Calcium movement in smooth muscle and evaluation of graded functional intercellular coupling

Spontaneous activity of vascular smooth muscle is present in small arteries and some venous tissues like the hepatic portal vein. Whereas the ability to generate rhythmic membrane potential changes is expressed in a high number of primary oscillators, the generation of physiological tone and phasic activity requires synchronization of specialized pacemaker activity (Interstitial Cajal-like cells) by intercellular propagation and regeneration of excitation or a strong coupling mechanism of smooth muscle cells. The aim of this study was to deduce oscillator coupling by analyzing the spatiotemporal homogeneity of calcium oscillations within a native tissue preparation. Portal vein tissue was loaded with a calcium-sensitive dye (Fluo-3). By combining confocal microscopy and computation of spatial auto- and cross-correlation of the calcium signals, temporal and spatial coupling between cells was characterized. Spontaneous oscillations of calcium signals were measured at different predefined regions of interest. Cross-correlation analysis of these signals revealed that their damping was very similar in all directions of the investigated z-plane. In single experiments, improved cell-to-cell coupling was seen when noradrenaline (1-10 μM) was added to the bath-solution. With the chosen parameters of frame refresh, the velocity of signal propagation was faster than the maximum detectable velocity, but it could be estimated to exceed 0.1 mm/s. Correlative Network Analysis is a new and very useful tool to determine the functional coupling parameters of quasi-homogenous biological networks and their temporal changes. The action and significance of pharmacological modulators can be well studied on cellular and functional aspects with this newly introduced technique in biological sciences.

Altered Motor Unit Discharge Coherence in Paretic Muscles of Stroke Survivors

After a cerebral stroke, a series of changes at the supraspinal and spinal nervous system can alter the control of muscle activation, leading to persistent motor impairment. However, the relative contribution of these different levels of the nervous system to impaired muscle activation is not well understood. The coherence of motor unit (MU) spike trains is considered to partly reflect activities of higher level control, with different frequency band representing different levels of control. Accordingly, the objective of this study was to quantify the different sources of contribution to altered muscle activation. We examined the coherence of MU spike trains decomposed from surface electromyogram (sEMG) of the first dorsal interosseous muscle on both paretic and contralateral sides of 14 hemispheric stroke survivors. sEMG was obtained over a range of force contraction levels at 40, 50, and 60% of maximum voluntary contraction. Our results showed that MU coherence increased significantly in delta (1–4 Hz), alpha (8–12 Hz), and beta (15–30 Hz) bands on the affected side compared with the contralateral side, but was maintained at the same level in the gamma (30–60 Hz) band. In addition, no significant alteration was observed across medium–high force levels (40–60%). These results indicated that the common synaptic input to motor neurons increased on the paretic side, and the increased common input can originate from changes at multiple levels, including spinal and supraspinal levels following a stroke. All these changes can contribute to impaired activation of affected muscles in stroke survivors. Our findings also provide evidence regarding the different origins of impaired muscle activation poststroke.

Beta Band Corticomuscular Drive Reflects Muscle Coordination Strategies

During force production, hand muscle activity is known to be coherent with activity in primary motor cortex, specifically in the beta-band (15–30 Hz) frequency range. It is not clear, however, if this coherence reflects the control strategy selected by the nervous system for a given task, or if it instead reflects an intrinsic property of cortico-spinal communication. Here, we measured corticomuscular and intermuscular coherence between muscles of index finger and thumb while a two-finger pinch grip of identical net force was applied to objects which were either stable (allowing synergistic activation of finger muscles) or unstable (requiring individuated finger control). We found that beta-band corticomuscular coherence with the first dorsal interosseous (FDI) and abductor pollicis brevis (APB) muscles, as well as their beta-band coherence with each other, was significantly reduced when individuated control of the thumb and index finger was required. We interpret these findings to show that beta-band coherence is reflective of a synergistic control strategy in which the cortex binds task-related motor neurons into functional units.

The human motor neuron pools receive a dominant slow-varying common synaptic input

KEY POINTS

Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated. Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non-linearity of motor neurons. We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input (<5 Hz) to motor neurons in humans. We applied the proposed method to three human muscles and determined experimentally that they receive a similar large amount (>60%) of common input, irrespective of their different functional and control properties. These results increase our knowledge about the role of common and independent input to motor neurons in force control.

ABSTRACT

Motor neurons receive both common and independent synaptic inputs. This observation is classically based on the presence of a significant correlation between pairs of motor unit spike trains. The functional significance of different relative proportions of common input across muscles, individuals and conditions is still debated. One of the limitations in our understanding of correlated input to motor neurons is that it has not been possible so far to quantify the absolute proportion of common input with respect to the total synaptic input received by the motor neurons. Indeed, correlation measures of pairs of output spike trains only allow for relative comparisons. In the present study, we report for the first time an approach for measuring the proportion of common input in the low frequency bandwidth (<5 Hz) to a motor neuron pool in humans. This estimate is based on a phenomenological model and the theoretical fitting of the experimental values of coherence between the permutations of groups of motor unit spike trains. We demonstrate the validity of this theoretical estimate with several simulations. Moreover, we applied this method to three human muscles: the abductor digiti minimi, tibialis anterior and vastus medialis. Despite these muscles having different functional roles and control properties, as confirmed by the results of the present study, we estimate that their motor pools receive a similar and large (>60%) proportion of common low frequency oscillations with respect to their total synaptic input. These results suggest that the central nervous system provides a large amount of common input to motor neuron pools, in a similar way to that for muscles with different functional and control properties.

Motor Neuron Pools of Synergistic Thigh Muscles Share Most of Their Synaptic Input

Neural control of synergist muscles is not well understood. Presumably, each muscle in a synergistic group receives some unique neural drive and some drive that is also shared in common with other muscles in the group. In this investigation, we sought to characterize the strength, frequency spectrum, and force dependence of the neural drive to the human vastus lateralis and vastus medialis muscles during the production of isometric knee extension forces at 10 and 30% of maximum voluntary effort. High-density surface electromyography recordings were decomposed into motor unit action potentials to examine the neural drive to each muscle. Motor unit coherence analysis was used to characterize the total neural drive to each muscle and the drive shared between muscles. Using a novel approach based on partial coherence analysis, we were also able to study specifically the neural drive unique to each muscle (not shared). The results showed that the majority of neural drive to the vasti muscles was a cross-muscle drive characterized by a force-dependent strength and bandwidth. Muscle-specific neural drive was at low frequencies (<5 Hz) and relatively weak. Frequencies of neural drive associated with afferent feedback (6-12 Hz) and with descending cortical input (∼20 Hz) were almost entirely shared by the two muscles, whereas low-frequency (<5 Hz) drive comprised shared (primary) and muscle-specific (secondary) components. This study is the first to directly investigate the extent of shared versus independent control of synergist muscles at the motor neuron level.

SIGNIFICANCE STATEMENT

Precisely how the nervous system coordinates the activity of synergist muscles is not well understood. One possibility is that muscles of a synergy share a common neural drive. In this study, we directly compared the relative strength of shared versus independent neural drive to synergistically activated thigh muscles in humans. The results of this analysis support the notion that synergistically activated muscles share most of their neural drive. Scientifically, this study addressed an important gap in our current understanding of how neural drive is delivered to synergist muscles. We have also demonstrated the feasibility of a novel approach to the study of muscle synergies based on partial coherence analysis of motor unit activity.

High-density surface EMG decomposition allows for recording of motor unit discharge from proximal and distal flexion synergy muscles simultaneously in individuals with stroke

Analysis of motor unit discharge can provide insight into the neural control of movement in healthy and pathological states, but it is typically completed in one muscle at a time. For some research investigations, it would be advantageous to study motor unit discharge from multiple muscles simultaneously. One such example is investigation of the flexion synergy, an abnormal muscle co-activation pattern in post-stroke individuals in which activation of shoulder abductors is involuntarily coupled with that of elbow and finger flexors. However, limitations in available technology have hindered the ability to efficiently extract motor unit discharge from multiple muscles simultaneously. In this study, we propose the use of high-density surface EMG decomposition from proximal and distal flexion synergy muscles (deltoid, biceps, wrist/finger flexors) in combination with an isometric joint torque recording device in individuals with chronic stroke. This innovative approach provides the ability to efficiently analyze both motor units and joint torques that have been simultaneously recorded from the shoulder, elbow, and fingers. In preliminary experiments, 3 stroke and 5 control participants generated shoulder abduction, elbow flexion, and finger flexion torques at 10, 20, 30 and 40% of maximum torque. Motor unit spike trains could be extracted from all muscles at each torque level. Mean motor unit firing rates were significantly lower in the stroke group than in the control group for all three muscles. Within the stroke group, wrist/finger flexor motor units had the lowest coefficient of variation. Additionally, modulation of mean firing rates across torque levels was significantly impaired in all three paretic muscles. The implications of these findings and overall impact of this approach are discussed.

Fatigue-related electromyographic coherence and phase synchronization analysis between antagonistic elbow muscles

The aim of this study was to examine coherence and phase synchronization between antagonistic elbow muscles and thus to explore the coupling and common neural inputs of antagonistic elbow muscles during sustained submaximal isometric fatiguing contraction. Fifteen healthy male subjects sustained an isometric elbow flexion at 20 % maximal level until exhaustion, while surface electromyographic signals (sEMG) were collected from biceps brachii (BB) and triceps brachii (TB). sEMG signals were divided into the first half (stage 1 with minimal fatigue) and second half (stage 2 with severe fatigue) of the contraction. Coherence and phase synchronization analysis was conducted between sEMG of BB and TB, and coherence value and phase synchronization index in alpha (8-12 Hz), beta (15-35 Hz) and gamma (35-60 Hz) frequency bands were obtained. Significant increase in EMG-EMG coherence and phase synchronization index in alpha and beta frequency bands between antagonistic elbow flexion muscles was observed all increased in stage 2 compared to stage 1. Coupling of EMG activities between antagonistic muscles increased as a result of fatigue caused by 20 % maximal level sustained isometric elbow flexion, indicating the increased interconnection between synchronized cortical neurons and the motoneuron pool of BB and TB, which may be cortical in origin. This increased coupling may help to maintain coactivation level so as to ensure joint stability on the basis of maintaining the joint force output.

Task-related changes in sensorimotor integration influence the common synaptic input to motor neurones

AIM

The purpose of this investigation was to understand how visual information, when used to guide muscle activity, influences the frequency content of the neural drive to muscles and the gain of afferent feedback.

METHODS

Subjects maintained static, isometric contractions of the tibialis anterior muscle by matching a visual display of their ankle dorsiflexion force to a target set at 10% of their maximum voluntary contraction level. Two visual feedback conditions were studied. The first was a high-sensitivity feedback, in which small changes in force were of large on-screen visual magnitude. The second was a low-sensitivity feedback, in which the on-screen scaling of feedback was reduced by a factor of 10, making small force fluctuations difficult to perceive. Force tremor and Hoffmann reflex (H-reflex) amplitudes were compared between the two conditions, as well as coherence among single motor unit spike trains derived from high-density EMG recordings.

RESULTS

The high-sensitivity feedback condition was associated with lower error, larger force tremor (4-12 Hz) and larger H-reflex amplitudes relative to the low-sensitivity feedback condition. In addition, the use of high-sensitivity feedback was associated with lower 1-5 Hz coherence among pairs of motor units, but larger coherence at high frequencies (6-12, approx. 20, >30 Hz).

CONCLUSION

Alteration of visual feedback influences nearly the entire frequency spectrum of common input to motor neurones, as well the gain of afferent feedback. We speculate that task-related modulation of afferent feedback could be the origin of many of the observed changes in the neural drive to muscles.

Subthalamic nucleus long-range synchronization-an independent hallmark of human Parkinson's disease

Beta-band synchronous oscillations in the dorsolateral region of the subthalamic nucleus (STN) of human patients with Parkinson's disease (PD) have been frequently reported. However, the correlation between STN oscillations and synchronization has not been thoroughly explored. The simultaneous recordings of 2390 multi-unit pairs recorded by two parallel microelectrodes (separated by fixed distance of 2 mm, n = 72 trajectories with two electrode tracks >4 mm STN span) in 57 PD patients undergoing STN deep brain stimulation surgery were analyzed. Automatic procedures were utilized to divide the STN into dorsolateral oscillatory and ventromedial non-oscillatory regions, and to quantify the intensity of STN oscillations and synchronicity. Finally, the synchronicity of simultaneously vs. non-simultaneously recorded pairs were compared using a shuffling procedure. Synchronization was observed predominately in the beta range and only between multi-unit pairs in the dorsolateral oscillatory region (n = 615). In paired recordings between sites in the dorsolateral and ventromedial (n = 548) and ventromedial-ventromedial region pairs (n = 1227), no synchronization was observed. Oscillation and synchronicity intensity decline along the STN dorsolateral-ventromedial axis suggesting a fuzzy border between the STN regions. Synchronization strength was significantly correlated to the oscillation power, but synchronization was no longer observed following shuffling. We conclude that STN long-range beta oscillatory synchronization is due to increased neuronal coupling in the Parkinsonian brain and does not merely reflect the outcome of oscillations at similar frequency. The neural synchronization in the dorsolateral (probably the motor domain) STN probably augments the pathological changes in firing rate and patterns of subthalamic neurons in PD patients.

Neural correlates of task-related changes in physiological tremor

Appropriate control of muscle contraction requires integration of command signals with sensory feedback. Sensorimotor integration is often studied under conditions in which muscle force is controlled with visual feedback. While it is known that alteration of visual feedback can influence task performance, the underlying changes in neural drive to the muscles are not well understood. In this study, we characterize the frequency content of force fluctuations and neural drive when production of muscle force is target guided versus self guided. In the self-guided condition, subjects performed isometric contractions of the first dorsal interosseous (FDI) muscle while slowly and randomly varying their force level. Subjects received visual feedback of their own force in order to keep contractions between 6% and 10% of maximum voluntary contraction (MVC). In the target-guided condition, subjects used a display of their previously generated force as a target to track over time. During target tracking, force tremor increased significantly in the 3–5 and 7–9 Hz ranges, compared with self-guided contractions. The underlying changes in neural drive were assessed by coherence analysis of FDI motor unit activity. During target-guided force production, pairs of simultaneously recorded motor units showed less coherent activity in the 3–5 Hz frequency range but greater coherence in the 7–9 Hz range than in the self-guided contractions. These results show that the frequency content of common synaptic input to motoneurons is altered when force production is visually guided. We propose that a change in stretch-reflex gain could provide a potential mechanism for the observed changes in force tremor and motor unit coherence.

Short-term synchrony in diverse motor nuclei presumed to receive different extents of direct cortical input

Motor units within human muscles usually exhibit a significant degree of short-term synchronization. Such coincident spiking typically has been attributed to last-order projections that provide common synaptic input across motor neurons. The extent of branched input arising directly from cortical neurons has often been suggested as a critical factor determining the magnitude of short-term synchrony. The purpose of this study, therefore, was to quantify motor unit synchrony in a variety of human muscles differing in the presumed extent of cortical input to their respective motor nuclei. Cross-correlation histograms were generated from the firing times of 551 pairs of motor units in 16 human muscles. Motor unit synchrony tended to be weakest for proximal muscles and strongest for more distal muscles. Previous work in monkeys and humans has shown that the strength of cortical inputs to motor neurons also exhibits a similar proximal-to-distal gradient. However, in the present study, proximal-distal location was not an exclusive predictor of synchrony magnitude. The muscle that exhibited the least synchrony was an elbow flexor, whereas the greatest synchrony was most often found in intrinsic foot muscles. Furthermore, the strength of corticospinal inputs to the abductor hallucis muscle, an intrinsic foot muscle, as assessed through transcranial magnetic stimulation, was weaker than that projecting to the tibialis anterior muscle, even though the abductor hallucis muscle had higher synchrony values compared with the tibialis anterior muscle. We argue, therefore, that factors other than the potency of cortical inputs to motor neurons, such as the number of motor neurons innervating a muscle, significantly affects motor unit synchrony.

Neural adaptations to strength training: moving beyond transcranial magnetic stimulation and reflex studies

It has long been believed that training for increased strength not only affects muscle tissue, but also results in adaptive changes in the central nervous system. However, only in the last 10 years has the use of methods to study the neurophysiological details of putative neural adaptations to training become widespread. There are now many published reports that have used single motor unit recordings, electrical stimulation of peripheral nerves, and non-invasive stimulation of the human brain [i.e. transcranial magnetic stimulation (TMS)] to study neural responses to strength training. In this review, we aim to summarize what has been learned from single motor unit, reflex and TMS studies, and identify the most promising avenues to advance our conceptual understanding with these methods. We also consider the few strength training studies that have employed alternative neurophysiological techniques such as functional magnetic resonance imaging and electroencephalography. The nature of the information that these techniques can provide, as well as their major technical and conceptual pitfalls, are briefly described. The overall conclusion of the review is that the current evidence regarding neural adaptations to strength training is inconsistent and incomplete. In order to move forward in our understanding, it will be necessary to design studies that are based on a rigorous consideration of the limitations of the available techniques, and that are specifically targeted to address important conceptual questions.

Synchronization of presynaptic input to motor units of tongue, inspiratory intercostal, and diaphragm muscles

The respiratory central pattern generator distributes rhythmic excitatory input to phrenic, intercostal, and hypoglossal premotor neurons. The degree to which this input shapes motor neuron activity can vary across respiratory muscles and motor neuron pools. We evaluated the extent to which respiratory drive synchronizes the activation of motor unit pairs in tongue (genioglossus, hyoglossus) and chest-wall (diaphragm, external intercostals) muscles using coherence analysis. This is a frequency domain technique, which characterizes the frequency and relative strength of neural inputs that are common to each of the recorded motor units. We also examined coherence across the two tongue muscles, as our previous work shows that, despite being antagonists, they are strongly coactivated during the inspiratory phase, suggesting that excitatory input from the premotor neurons is distributed broadly throughout the hypoglossal motoneuron pool. All motor unit pairs showed highly correlated activity in the low-frequency range (1-8 Hz), reflecting the fundamental respiratory frequency and its harmonics. Coherence of motor unit pairs recorded either within or across the tongue muscles was similar, consistent with broadly distributed premotor input to the hypoglossal motoneuron pool. Interestingly, motor units from diaphragm and external intercostal muscles showed significantly higher coherence across the 10-20-Hz bandwidth than tongue-muscle units. We propose that the lower coherence in tongue-muscle motor units over this range reflects a larger constellation of presynaptic inputs, which collectively lead to a reduction in the coherence between hypoglossal motoneurons in this frequency band. This, in turn, may reflect the relative simplicity of the respiratory drive to the diaphragm and intercostal muscles, compared with the greater diversity of functions fulfilled by muscles of the tongue.

Reliability of EMG determinism to detect changes in motor unit synchrony and coherence during submaximal contraction

The determinism (DET) is a parameter used in nonlinear analysis to quantify the occurrence of recurrent patterns in a signal. Applied to the electromyographic activity (EMG), DET has been proposed as an index of motor unit synchrony in human. We have recently shown that the amount of motor unit synchronous firings above chance level was enhanced with stronger submaximal muscle contraction. Using these data, we aimed at determining if (1) EMG DET and motor unit synchrony varied in the same way and (2) EMG DET was more specifically related to the degree of oscillatory coupling between motor unit discharges. Cross-correlation and coherence analyses were applied to the discharges of 30 motor unit pairs tested at various force levels to assess the amount of synchronous impulses and the strength of oscillatory coupling in the time and frequency domains, respectively. Recurrent quantification analysis was applied to EMG activity to extract its DET. Overall, changes in EMG DET were poorly explained by changes in motor unit synchronous impulse probability (6%) and frequency (5%), and by changes in motor unit coherence in the 6-12Hz (5%) and 25-40Hz (8%) bands. Moreover, the comparison of the data obtained at the weakest and the strongest contraction levels tested with each motor unit pair showed that EMG DET remained unaltered with stronger contraction despite the occurrence of consistent changes in motor unit synchrony in both time and frequency domains. This speaks strongly against the reliability of DET in evaluating changes in motor unit synchronization during submaximal muscle contraction.

Common synaptic input to the human hypoglossal motor nucleus

The tongue plays a key role in various volitional and automatic functions such as swallowing, maintenance of airway patency, and speech. Precisely how hypoglossal motor neurons, which control the tongue, receive and process their often concurrent input drives is a subject of ongoing research. We investigated common synaptic input to the hypoglossal motor nucleus by measuring the coordination of spike timing, firing rate, and oscillatory activity across motor units recorded from unilateral (i.e., within a belly) or bilateral (i.e., across both bellies) locations within the genioglossus (GG), the primary protruder muscle of the tongue. Simultaneously recorded pairs of motor units were obtained from 14 healthy adult volunteers using tungsten microelectrodes inserted percutaneously into the GG while the subjects were engaged in volitional tongue protrusion or rest breathing. Bilateral motor unit pairs showed concurrent low frequency alterations in firing rate (common drive) with no significant difference between tasks. Unilateral motor unit pairs showed significantly stronger common drive in the protrusion task compared with rest breathing, as well as higher indices of synchronous spiking (short-term synchrony). Common oscillatory input was assessed using coherence analysis and was observed in all conditions for frequencies up to ∼ 5 Hz. Coherence at frequencies up to ∼ 10 Hz was strongest in motor unit pairs recorded from the same GG belly in tongue protrusion. Taken together, our results suggest that cortical drive increases motor unit coordination within but not across GG bellies, while input drive during rest breathing is distributed uniformly to both bellies of the muscle.

The alpha-motoneuron pool as transmitter of rhythmicities in cortical motor drive

OBJECTIVE

Investigate the effectiveness and frequency dependence of central drive transmission via the alpha-motoneuron pool to the muscle.

METHODS

We describe a model for the simulation of alpha-motoneuron firing and the EMG signal as response to central drive input. The transfer in the frequency domain is investigated. Coherence between stochastical central input and EMG is also evaluated.

RESULTS

The transmission of central rhythmicities to the EMG signal relates to the spectral content of the latter. Coherence between central input to the alpha-motoneuron pool and the EMG signal is significant whereby the coupling strength hardly depends on the frequency in a range from 1 to 100 Hz. Common central input to pairs of alpha-motoneurons strongly increases the coherence levels. The often-used rectification of the EMG signal introduces a clear frequency dependence.

CONCLUSIONS

Oscillatory phenomena are strongly transmitted via the alpha-motoneuron pool. The motoneuron firing frequencies do play a role in the transmission gain, but do not influence the coherence levels. Rectification of the EMG signal enhances the transmission gain, but lowers coherence and introduces a strong frequency dependency. We think that it should be avoided.

SIGNIFICANCE

Our findings show that rhythmicities are translated into alpha-motoneuron activity without strong non-linearities.

Origins of spontaneous firing of motor units in the spastic-paretic biceps brachii muscle of stroke survivors

One potential expression of altered motoneuron excitability following a hemispheric stroke is the spontaneous unit firing (SUF) of motor units at rest. The elements contributing to this altered excitability could be spinal descending pathways, spinal interneuronal networks, afferent feedback, or intrinsic motoneuron properties. Our purpose was to examine the characteristics of spontaneous discharge in spastic-paretic and contralateral muscles of hemiparetic stroke survivors, to determine which of these mechanisms might contribute. To achieve this objective, we examined the statistics of spontaneous discharge of individual motor units and we conducted a coherence analyses on spontaneously firing motor unit pairs. The presence of significant coherence between units might indicate a common driving source of excitation to multiple motoneurons from descending pathways or regional interneurons, whereas a consistent lack of coherence might favor an intrinsic cellular mechanism of hyperexcitability. Spontaneous firing of motor units (i.e., ongoing discharge in the absence of an ongoing stimulus) was observed to a greater degree in spastic-paretic muscles (following 83.2 ± 16.7% of ramp contractions) than that in contralateral muscles (following just 14.1 ± 10.5% of ramp contractions; P < 0.001) and was not observed at all in healthy control muscle. The average firing rates of the spontaneously firing units were 8.4 ± 1.8 pulses/s (pps) in spastic-paretic muscle and 9.6 ± 2.2 pps in contralateral muscle (P < 0.001). In 37 instances (n = 63 pairs), we observed spontaneous discharge of two or more motor units simultaneously in spastic-paretic muscle. Seventy percent of the dually firing motor unit pairs exhibited significant coherence (P < 0.001) in the 0- to 4-Hz bandwidth (average peak coherence: 0.14 ± 0.13; range: 0.01-0.75) and 22% of pairs exhibited significant coherence (P < 0.001) in the 15- to 30-Hz bandwidth (average peak coherence: 0.07 ± 0.06; range: 0.01-0.31). We suggest that the spontaneous firing was likely not attributable solely to enhanced intrinsic motoneuron activation, but attributable, at least in part, to a low-level excitatory synaptic input to the resting spastic-paretic motoneuron pool, possibly from regional or supraspinal centers.

Impaired transmission in the corticospinal tract and gait disability in spinal cord injured persons

Rehabilitation following spinal cord injury is likely to depend on recovery of corticospinal systems. Here we investigate whether transmission in the corticospinal tract may explain foot drop (inability to dorsiflex ankle) in persons with spinal cord lesion. The study was performed in 24 persons with incomplete spinal cord lesion (C1 to L1) and 15 healthy controls. Coherence in the 10- to 20-Hz frequency band between paired tibialis anterior muscle (TA) electromyographic recordings obtained in the swing phase of walking, which was taken as a measure of motor unit synchronization. It was significantly correlated with the degree of foot drop, as measured by toe elevation and ankle angle excursion in the first part of swing. Transcranial magnetic stimulation was used to elicit motor-evoked potentials (MEPs) in the TA. The amplitude of the MEPs at rest and their latency during contraction were correlated to the degree of foot drop. Spinal cord injured participants who exhibited a large foot drop had little or no MEP at rest in the TA muscle and had little or no coherence in the same muscle during walking. Gait speed was correlated to foot drop, and was the lowest in participants with no MEP at rest. The data confirm that transmission in the corticospinal tract is of importance for lifting the foot during the swing phase of human gait.

Considerations for the use of a startling acoustic stimulus in studies of motor preparation in humans

Recent studies have used a loud (> 120 dB) startle-eliciting acoustic stimulus as a probe to investigate early motor response preparation in humans. The use of a startle in these studies has provided insight into not only the neurophysiological substrates underlying motor preparation, but also into the behavioural response strategies associated with particular stimulus-response sets. However, as the use of startle as a probe for preparation is a relatively new technique, a standard protocol within the context of movement paradigms does not yet exist. Here we review the recent literature using startle as a probe during the preparation phase of movement tasks, with an emphasis on how the experimental parameters affect the results obtained. Additionally, an overview of the literature surrounding the startle stimulus parameters is provided, and factors affecting the startle response are considered. In particular, we provide a review of the factors that should be taken into consideration when using a startling stimulus in human research.

Task failure during standing heel raises is associated with increased power from 13 to 50 Hz in the activation of triceps surae

The goal of this paper was to investigate the amplitude and sub-100 Hz frequency content of surface electromyography (EMG) signals obtained from agonist, antagonist and synergist muscles during a heel-raise task sustained to failure. Twenty-two healthy adults, 14 men and 8 women participated in the study. Surface EMG data from the raising and lowering phases of the movement were studied in the time (EMG amplitude) and frequency (wavelet transform) domains. For the raising phase, we found a significant increase in the EMG amplitude of all muscles studied throughout the task (P < 0.02); however, for the lowering phase, we found a decrease in overall muscle activation for the medial gastrocnemius and tibialis anterior. Additionally, we found higher 13-30 and 30-50 Hz normalized power during the raising phase for the triceps surae prior to task failure and at task failure compared with the beginning and midway of the task (P < 0.05); during the lowering phase, however, we found higher normalized power from 30 to 50 Hz for the triceps surae (P < 0.01) and higher 13-30 Hz normalized power for the tibialis anterior (P < 0.01) at task failure compared with the beginning and midway of the task. Finally, we showed that a dynamic task performed until failure can induce different activation strategies for agonist, antagonist and synergist muscles, and that the frequency content below 100 Hz contains useful information about the neural activation of these muscles in relation to task failure that is not evident from the EMG amplitude.

Rectification of the EMG signal impairs the identification of oscillatory input to the muscle

Rectification of EMG signals is a common processing step used when performing electroencephalographic-electromyographic (EEG-EMG) coherence and EMG-EMG coherence. It is well known, however, that EMG rectification alters the power spectrum of the recorded EMG signal (interference EMG). The purpose of this study was to determine whether rectification of the EMG signal influences the capability of capturing the oscillatory input to a single EMG signal and the common oscillations between two EMG signals. Several EMG signals were reconstructed from experimentally recorded EMG signals from the surface of the first dorsal interosseus muscle and were manipulated to have an oscillatory input or common input (for pairs of reconstructed EMG signals) at various frequency bands (in Hz: 0-12, 12-30, 30-50, 50-100, 100-150, 150-200, 200-250, 250-300, and 300-400), one at a time. The absolute integral and normalized integral of power, peak power, and peak coherence (for pairs of EMG signals) were quantified from each frequency band. The power spectrum of the interference EMG accurately detected the changes to the oscillatory input to the reconstructed EMG signal, whereas the power spectrum of the rectified EMG did not. Similarly, the EMG-EMG coherence between two interference EMG signals accurately detected the common input to the pairs of reconstructed EMG signals, whereas the EMG-EMG coherence between two rectified EMG signals did not. The frequency band from 12 to 30 Hz in the power spectrum of the rectified EMG and the EMG-EMG coherence between two rectified signals was influenced by the input from 100 to 150 Hz but not from the input from 12 to 30 Hz. The study concludes that the power spectrum of the EMG and EMG-EMG coherence should be performed on interference EMG signals and not on rectified EMG signals because rectification impairs the identification of the oscillatory input to a single EMG signal and the common oscillatory input between two EMG signals.

Neural control of hand muscles during prehension

In the past two decades a large number of studies have successfully characterized important features of the kinetics and kinematics of object grasping and manipulation, providing significant insight into how the Central Nervous System (CNS) controls the hand, one of the most complex motor systems, in a variety of behaviors. In this chapter we briefly review studies of hand kinematics and kinetics and highlight their major findings and open questions. The major focus of this chapter is on the neural control of the hand, an objective that has been pursued by studies on electromyography (EMG) of hand muscles. Here we review what has been learned through different yet complementary methodological approaches. In particular, the study of single motor unit activity has revealed how the distribution of common neural input within and across hand muscles might reflect a muscle-pair specific organization. Studies of motor unit population have revealed important synergistic patterns of muscle activity while also revealing muscle-pair specific patterns of neural coupling. We conclude the chapter with the results of recent simulation studies aiming at combining advantages of single and multi-unit recordings to maximize the amount of information that can be extracted from EMG signal analysis.

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

The purpose of this study was to determine the effect of eccentric exercise on correlated motor unit discharge (motor unit synchronization and coherence) during low-force contractions of the human biceps brachii muscle. Eight subjects (age, 25 ± 7 yr) performed three tasks involving isometric contraction of elbow flexors while EMG (surface and intramuscular) records were obtained from biceps brachii. Tasks were 1) maximum voluntary contraction (MVC); 2) constant-force contraction at various submaximal targets; and 3) sustained discharge of pairs of concurrently active motor units for 2–5 min. These tasks were performed before, immediately after, and 24 h after fatiguing eccentric exercise. MVC force declined 46% immediately after eccentric exercise and remained depressed (31%) 24 h later, which is indicative of muscle damage. For the constant-force task, biceps brachii EMG (∼100% greater) and force fluctuations (∼75% greater) increased immediately after exercise, and both recovered by ∼50% 24 h later. Motor unit synchronization, quantified by cross-correlation of motor unit pairs during low-force (1–26% MVC) contractions, was 30% greater immediately after ( n = 105 pairs) and 24 h after exercise ( n = 92 pairs) compared with before exercise ( n = 99 pairs). Similarly, motor unit coherence at low (0–10 Hz) frequencies was 20% greater immediately after exercise and 34% greater 24 h later. These results indicate that the series of events leading to muscle damage from eccentric exercise alters the correlated behavior of human motor units in biceps brachii muscle for ≥24 h after the exercise.

Analysis of the effects of firing rate and synchronization on spike-triggered averaging of multidirectional motor unit torque

Spike-triggered averaging (STA) of muscle force transients has often been used to estimate motor unit contractile properties, using the discharge of a motor unit within the muscle as the triggering events. For motor units that exert torque about multiple degrees-of-freedom, STA has also been used to estimate motor unit pulling direction. It is well known that motor unit firing rate and weak synchronization of motor unit discharges with other motor units in the muscle can distort STA estimates of contractile properties, but the distortion of STA estimates of motor unit pulling direction has not been thoroughly evaluated. Here, we derive exact equations that predict that STA decouples firing rate and synchronization distortion when used to estimate motor unit pulling direction. We derive a framework for analyzing synchronization, consider whether the distortion due to synchronization can be removed from STA estimates of pulling direction, and show that there are distributions of motor unit pulling directions for which STA is insensitive to synchronization. We conclude that STA may give insight into how motoneuronal synchronization is organized with respect to motor unit pulling direction.

The tremor coherence analyzer (TCA): a portable tool to assess instantaneous inter-muscle coupling in tremor

This paper proposes a novel system for pathological tremor study and diagnosis. The system described called TCA (tremor coherence analyzer) is based on a electronic device developed for wireless monitoring of physiological variables. The device uses Bluetooth technology to communicate. The proposed technique for pathological tremor analysis uses surface EMG signals. The EMG sensors are located on forearm muscles to measure muscular activity due to pathological tremor. The coherence function between these signals is calculated. The application of the coherence function allows to determine linear dependencies between two signals.

Discharge rate during low-force isometric contractions influences motor unit coherence below 15 Hz but not motor unit synchronization

The purpose of the study was to determine whether pairs of motor units that discharge action potentials at different rates during isometric contractions exhibit different levels of motor unit synchronization or coherence. Twelve subjects (28.6 +/- 6.1 years) performed isometric contractions at target forces slightly above the recruitment threshold (1.02-20.9%) of an isolated motor unit. Based on audio feedback, subjects maintained a relatively constant discharge rate of the isolated unit for about 80 s. Intramuscular electrodes were used to record the discharge of 47 pairs of motor units at rates that ranged from 8.07 to 13.6 pps. Correlated discharge between pairs of motor units was quantified with the common input strength (CIS) index, k' index, and coherence spectrum. Greater discharge rates across pairs of motor units were predicted (R2 = 0.36, P < 0.001) by higher coherence from 8 to 13 Hz (r = -0.52) and lower coherence from 0 to 4 Hz (r = 0.37). Indexes of motor unit synchronization (CIS and k') were strongly associated with motor unit coherence from 16 to 32 Hz (CIS: R2 = 0.63; k': R2 = 0.4; P = 0.001). The CIS index of motor unit synchronization and the motor unit coherence from 16 to 32 Hz did not vary with discharge rate. In contrast, the k' index of motor unit synchronization declined with discharge rate (r2 = 0.20, P = 0.001). Furthermore, greater discharge rates across pairs of motor units were accompanied by higher motor unit coherence in the 8-13 Hz band and lower motor unit coherence in the 0-4 Hz band. These results demonstrate that differences in discharge rate between pairs of motor units in first dorsal interosseus during low-force, isometric contractions were associated with modulation of the correlation in the discharge times of the two motor units at frequencies less than 15 Hz.

Motor unit synchronization measured by cross-correlation is not influenced by short-term strength training of a hand muscle

The purpose of the study was to quantify the strength of motor unit synchronization and coherence from pairs of concurrently active motor units before and after short-term (4-8 weeks) strength training of the left first dorsal interosseous (FDI) muscle. Five subjects (age 24.8 +/- 4.3 years) performed a training protocol three times/week that consisted of six sets of ten maximal isometric index finger abductions, whereas three subjects (age 27.3 +/- 6.7 years) acted as controls. Motor unit activity was recorded from pairs of intramuscular electrodes in the FDI muscle with two separate motor unit recording sessions obtained before and after strength training (trained group) or after 4 weeks of normal daily activities that did not involve training (control group). The training intervention resulted in a 54% (45.2 +/- 8.3 to 69.5 +/- 13.8 N, P = 0.001) increase in maximal index finger abduction force, whereas there was no change in strength in the control group. A total of 163 motor unit pairs (198 single motor units) were examined in both subject groups, with 52 motor unit pairs obtained from 10 recording sessions before training and 51 motor unit pairs from 10 recording sessions after training. Using the cross-correlation procedure, there was no change in the strength of motor unit synchronization following strength training (common input strength index; 0.71 +/- 0.41 to 0.67 +/- 0.43 pulses/s). Furthermore, motor unit coherence z scores at low (0-10 Hz; 3.9 +/- 0.3 before to 4.4 +/- 0.4 after) or high (10-30 Hz; 1.7 +/- 0.1 before to 1.9 +/- 0.1 after) frequencies were not influenced by strength training. These motor unit data indicate that increases in strength following several weeks of training a hand muscle are not accompanied by changes in motor unit synchronization or coherence, suggesting that these features of correlated motor unit activity are not important in the expression of muscle strength.

Transcranial direct current stimulation of the primary motor cortex affects cortical drive to human musculature as assessed by intermuscular coherence

Intermuscular coherence analysis can be used to assess the common drive to muscles. Coherence in the beta-frequency band (15-35 Hz) is thought to arise from common cortical sources. Intermuscular coherence analysis is a potentially attractive tool for the investigation of motor cortical excitability changes because it is non-invasive and can be done relatively quickly. We carried out this study to test the hypothesis that intermuscular coherence analysis was able to detect cortical excitability changes in healthy subjects following transcranial direct current stimulation (tDCS). tDCS has been shown to increase (anodal stimulation) or decrease (cathodal stimulation) the size of the muscle potential evoked by TMS. We found that anodal tDCS caused an increase in motor evoked potential (MEP) size that was paralleled by an increase in beta-band intermuscular coherence. Similarly, the reduction in MEP size produced by cathodal tDCS was paralleled by a reduction in beta-band intermuscular coherence, while sham stimulation did not result in any change in either MEP amplitude or beta-band intermuscular coherence. The similar pattern of change observed for MEP and intermuscular coherence may indicate similar mechanisms of action, although this cannot be assumed without further investigation. These changes do suggest that at least some of the action of tDCS is on cortical networks, and that combined tDCS and intermuscular coherence analysis may be useful in the diagnosis of pathologies affecting motor cortical excitability.

Influence of tactile afferents on the coordination of muscles during a simulated precision grip

The mechanisms by which the nervous system coordinates multiple muscles for the control of finger movements are not well understood. One possibility is that groups of muscles may be enlisted into synergies by last-order inputs that project across multiple motor nuclei. In this study we investigated the role that tactile input might play in coupling together the activities of motor units in two muscles involved in generating the precision grip. Cross-correlation analysis was used to assess the degree of synchrony in the discharge times of pairs of motor units recorded from index-finger and thumb flexor muscles while human subjects performed an isometric task that mimicked a precision grip. The magnitude of synchrony is thought to reflect the extent to which divergent last order inputs provide common synaptic input across motor neurons. Synchrony was evaluated under two simulated-gripping conditions: gripping with normal tactile input and gripping when tactile input from the digit pads was eliminated by applying flexion forces to fittings glued to the finger nails. Synchrony between motor units of index finger flexor and thumb flexor muscles, while substantial, was not significantly different across the two tactile-input conditions. These findings suggest that tactile input is not required to activate the divergent last-order inputs that couple together the activities of the index finger and thumb flexor muscles during the precision grip.

Organisation of common inputs to motoneuron pools of human masticatory muscles

OBJECTIVE

To determine the pattern of organization of common inputs to the motoneuron pools of individual muscles in the masticatory system.

METHODS

Six subjects bit on a rubber-coated wooden splint placed between the upper and lower incisor teeth. We recorded the surface electromyogram (EMG) of co-contracting masseter, temporalis and digastric muscles bilaterally during isometric jaw closing at 5%, 10%, 20% and 40% of maximal voluntary masseter EMG.

RESULTS

The cross-correlograms of the EMGs of homologous muscle pairs indicate that there are common synaptic inputs to the motoneuron pools of the left and right masseter, and left and right digastric muscles, but not to left and right temporalis. The amplitude of the central peak in masseter and digastric correlograms increased with bite force. When the activity of ipsilateral muscle pairs was cross-correlated, central peaks were prominent for masseter-digastric and masseter-temporalis muscle pairs, and the peak amplitudes increased significantly with bite force. In contrast, no significant central peak was observed for temporalis-digastric muscle pairs at any level of voluntary biting.

CONCLUSIONS

We conclude that there is synchronous modulation of input bilaterally to the masseter muscles and to the digastric muscles but not to the temporalis muscles. There is synchronous modulation of input to ipsilateral masseter-digastric and masseter-temporalis muscle pairs but not to temporalis and digastric muscles.

SIGNIFICANCE

The extent of common input to motoneuron pools of muscles acting around a common joint varies for different muscle pairs, and is not simply a function of whether the muscles of the pair are synergists or antagonists.

Signal-dependent wavelets for electromyogram classification

In the study, an efficient method to perform supervised classification of surface electromyogram (EMG) signals is proposed. The method is based on the choice of a relevant representation space and its optimisation with respect to a training set. As EMG signals are the summation of compact-support waveforms (the motor unit action potentials), a natural tool for their representation is the discrete dyadic wavelet transform. The feature space was thus built from the marginals of a discrete wavelet decomposition. The mother wavelet was designed to minimise the probability of classification error estimated on the learning set (supervised classification). As a representative example, the method was applied to simulate surface EMG signals generated by motor units with different degrees of short-term synchronisation. The proposed approach was able to distinguish surface EMG signals with degrees of synchronisation that differed by 10%, with a misclassification rate of 8%. The performance of a spectral-based classification (error rate approximately 33%) and of the classification with Daubechies wavelet (21%) was significantly poorer than with the proposed wavelet optimisation. The method can be used for a number of different application fields of surface EMG classification, as the feature space is adapted to the characteristics of the signal that discriminate between classes.

Changes in corticospinal drive to spinal motoneurones following visuo-motor skill learning in humans

We have previously demonstrated an increase in the excitability of the leg motor cortical area in relation to acquisition of a visuo-motor task in healthy humans. It remains unknown whether the interaction between corticospinal drive and spinal motoneurones is also modulated following motor skill learning. Here we investigated the effect of visuo-motor skill training involving the ankle muscles on the coupling between electroencephalographic (EEG) activity recorded from the motor cortex (Cz) and electromyographic (EMG) activity recorded from the left tibialis anterior (TA) muscle in 11 volunteers. Coupling in the time (cumulant density function) and frequency domains (coherence) between EEG-EMG and EMG-EMG activity were calculated during tonic isometric dorsiflexion before and after 32 min of training a visuo-motor tracking task involving the ankle muscles or performing alternating dorsi- and plantarflexion movements without visual feedback. A significant increase in EEG-EMG coherence around 15-35 Hz was observed following the visuo-motor skill session in nine subjects and in only one subject after the control task. Changes in coherence were specific to the trained muscle as coherence for the untrained contralateral TA muscle was unchanged. EEG and EMG power were unchanged following the training. Our results suggest that visuo-motor skill training is associated with changes in the corticospinal drive to spinal motorneurones. Possibly these changes reflect sensorimotor integration processes between cortex and muscle as part of the motor learning process.

Diminished task-related adjustments of common inputs to hand muscle motor neurons in older adults

The purpose of this study was to quantify correlated motor unit activity during isometric, shortening and lengthening contractions of a hand muscle in older adults. Thirteen old subjects (69.6+/-5.9 years, six women) lifted and lowered a light load with abduction-adduction movements of the index finger over 10 degrees using 6-s shortening and lengthening contractions of the first dorsal interosseus muscle. The task was repeated 10-20 times while activity in 23 pairs of motor units was recorded with intramuscular electrodes. The data were compared with 23 motor-unit pairs in 15 young (25.9+/-4.6 years, five women) subjects obtained using a similar protocol in a previous study. Correlated motor unit activity was quantified using time-domain (synchronization index; Common Input Strength) and frequency-domain (coherence) analyses for the same motor-unit pairs. For all contractions, there was no difference with age for the strength of motor-unit synchronization, although age-related differences were observed for synchronous peak widths (young, 17.6+/-7.4 ms; old, 13.7+/-4.9 ms) and motor-unit coherence at 6-9 Hz (z score for young, 3.0+/-1.8; old, 2.2+/-1.5). Despite increased synchrony during lengthening contractions and narrower peak widths for shortening contractions in young subjects, there was no difference in the strength of motor unit synchronization (CIS approximately 0.8 imp/s), or the width of the synchronous peak (approximately 14 ms) during the three tasks in old subjects. Furthermore, no significant differences in motor-unit coherence were observed between tasks at any frequency for old adults. These data suggest that the strategy used by the central nervous system to control isometric, shortening, and lengthening contractions varies in young adults, but not old adults. The diminished task-related adjustments of common inputs to motor neurons are a likely consequence of the neural adaptations that occur with advancing age.

Coherence at 16-32 Hz Can Be Caused by Short-Term Synchrony of Motor Units

Time- and frequency-domain measures of discharge times for pairs of motor units are used to infer the proportion of common synaptic input received by motor neurons. The physiological mechanisms that can produce the experimentally observed peaks in the cross-correlation histogram and the coherence spectrum are uncertain. The present study used a computational model to impose synchronization on the discharge times of motor units. Randomly selected discharge times of a unit that was being synchronized to a reference unit were aligned with some of the discharge times of the reference unit, provided the original discharge time was within 30 ms of the discharge by the reference unit. All time-domain measures (indexes CIS, E, and k′) were sensitive to changes in the level of imposed motor-unit synchronization ( P < 0.01). In addition, synchronization caused a peak between 16 and 32 Hz in the coherence spectrum. The shape of the cross-correlogram determined the frequency at which the peak occurred in the coherence spectrum. Further, the magnitude of the coherence peak was highly correlated with the time-domain measures of motor-unit synchronization ( r2 > 0.80), with the highest correlation occurring for index E ( r2 = 0.98). Thus the peak in the 16- to 32-Hz band of the coherence spectrum can be caused by the time that individual discharges are advanced or delayed to produce synchrony. Although the in vivo processes that adjust the timing of motor-unit discharges are not fully understood, these results suggest that they may not depend entirely on an oscillatory drive by the CNS.

Effects of Aging on the Regularity of Physiological Tremor

The purpose of this investigation was to determine the effects of healthy aging on the regularity of physiological tremor under rest and postural conditions. Additionally, we examined the contribution of mechanical reflex factors to age-related changes in postural physiological tremor. Tremor regularity, tremor–electromyographic (EMG) coherence, tremor amplitude, and tremor modal frequency were calculated for 4 age groups (young: 20–30 yr, young-old: 60–69 yr, old: 70–79 yr, and old-old: 80–94 yr) under resting and loaded postural conditions. There were 6 important findings from this study: 1) there were no differences between the young and elderly subjects for any of the dependent variables measured under the rest condition; 2) postural physiological tremor regularity was increased in the elderly; 3) postural physiological tremor-EMG coherence was also increased in the elderly, and there was a strong linear relation between peak tremor-EMG coherence in the 1- to 8-Hz frequency band and regularity of tremor. This relation was primarily driven by the increased magnitude of tremor-EMG coherence at 5.85 and 6.83 Hz; 4) enhanced mechanical reflex properties were not responsible for the increased magnitude of tremor-EMG coherence in the elderly subjects; 5) tremor amplitude was not different between the 4 age groups, but there was a slight decline in tremor modal frequency in the oldest age group in the unloaded condition; and 6) despite the increases in postural physiological tremor regularity and the magnitude of low frequency tremor-EMG coherence with age, there was a clear demarcation between healthy aging and previously published findings related to tremor pathology.