Synchronization of motor unit activity during voluntary contraction in man

Evolution, biomechanics, and neurobiology converge to explain selective finger motor control

Humans use their fingers to perform a variety of tasks, from simple grasping to manipulating objects, to typing and playing musical instruments, a variety wider than any other species. The more sophisticated the task, the more it involves individuated finger movements, those in which one or more selected fingers perform an intended action while the motion of other digits is constrained. Here we review the neurobiology of such individuated finger movements. We consider their evolutionary origins, the extent to which finger movements are in fact individuated, and the evolved features of neuromuscular control that both enable and limit individuation. We go on to discuss other features of motor control that combine with individuation to create dexterity, the impairment of individuation by disease, and the broad extent of capabilities that individuation confers on humans. We comment on the challenges facing the development of a truly dexterous bionic hand. We conclude by identifying topics for future investigation that will advance our understanding of how neural networks interact across multiple regions of the central nervous system to create individuated movements for the skills humans use to express their cognitive activity.

Muscle contractile properties directly influence shared synaptic inputs to spinal motor neurons

Alpha band oscillations in shared synaptic inputs to the alpha motor neuron pool can be considered an involuntary source of noise that hinders precise voluntary force production. This study investigated the impact of changing muscle length on the shared synaptic oscillations to spinal motor neurons, particularly in the physiological tremor band. Fourteen healthy individuals performed low-level dorsiflexion contractions at ankle joint angles of 90° and 130°, while high-density surface electromyography (HDsEMG) was recorded from the tibialis anterior (TA). We decomposed the HDsEMG into motor units spike trains and calculated the motor units' coherence within the delta (1-5 Hz), alpha (5-15 Hz), and beta (15-35 Hz) bands. Additionally, force steadiness and force spectral power within the tremor band were quantified. Results showed no significant differences in force steadiness between 90° and 130°. In contrast, alpha band oscillations in both synaptic inputs and force output decreased as the length of the TA was moved from shorter (90°) to longer (130°), with no changes in delta and beta bands. In a second set of experiments (10 participants), evoked twitches were recorded with the ankle joint at 90° and 130°, revealing longer twitch durations in the longer TA muscle length condition compared to the shorter. These experimental results, supported by a simple computational simulation, suggest that increasing muscle length enhances the muscle's low-pass filtering properties, influencing the oscillations generated by the Ia afferent feedback loop. Therefore, this study provides valuable insights into the interplay between muscle biomechanics and neural oscillations. KEY POINTS: We investigated whether changes in muscle length, achieved by changing joint position, could influence common synaptic oscillations to spinal motor neurons, particularly in the tremor band (5-15 Hz). Our results demonstrate that changing muscle length from shorter to longer induces reductions in the magnitude of alpha band oscillations in common synaptic inputs. Importantly, these reductions were reflected in the oscillations of muscle force output within the alpha band. Longer twitch durations were observed in the longer muscle length condition compared to the shorter, suggesting that increasing muscle length enhances the muscle's low-pass filtering properties. Changes in the peripheral contractile properties of motor units due to changes in muscle length significantly influence the transmission of shared synaptic inputs into muscle force output. These findings prove the interplay between muscle mechanics and neural adaptations.

Comparison of the activation level in the sensorimotor cortex between motor point and proximal nerve bundle electrical stimulation

Objective.Neuromuscular electrical stimulation (NMES) is widely used for motor function rehabilitation in stroke survivors. Compared with the conventional motor point (MP) stimulation, the stimulation at the proximal segment of the peripheral nerve (PN) bundles has been demonstrated to have multiple advantages. However, it is not known yet whether the PN stimulation can increase the cortical activation level, which is crucial for motor function rehabilitation.Approach.The current stimuli were delivered transcutaneously at the muscle belly of the finger flexors and the proximal segment of the median and ulnar nerves, respectively for the MP and PN stimulation. The stimulation intensity was determined to elicit the same contraction levels between the two stimulation methods in 18 healthy individuals and a stroke patient. The functional near-infrared spectroscopy and the electromyogram were recorded to compare the activation pattern of the sensorimotor regions and the target muscles.Main Results.For the healthy subjects, the PN stimulation induced significantly increased concentration of the oxygenated hemoglobin in the contralateral sensorimotor areas, and enhanced the functional connectivity between brain regions compared with the MP stimulation. Meanwhile, the compound action potentials had a smaller amplitude and the H-reflex became stronger under the PN stimulation, indicating that more sensory axons were activated in the PN stimulation. For the stroke patient, the PN stimulation can elicit finger forces and induce activation of both the contralateral and ipsilateral motor cortex.Conclusions. Compared with the MP stimulation, the PN stimulation can induce more cortical activation in the contralateral sensorimotor areas possibly via involving more activities in the central pathway.Significance.This study demonstrated the potential of the PN stimulation to facilitate functional recovery via increasing the cortical activation level, which may help to improve the outcome of the NMES-based rehabilitation for motor function recovery after stroke.

The neural control of movement: a century of in vivo motor unit recordings is the legacy of Adrian and Bronk

In two papers dated 1928 to 1929 in The Journal of Physiology, Edgar Adrian and Detlev Bronk described recordings from motor nerve and muscle fibres. The recordings from motor nerve fibres required progressive dissection of the nerve until a few fibres remained, from which isolated single fibre activity could be detected. The muscle fibre recordings were performed in humans during voluntary contractions with an intramuscular electrode - the concentric needle electrode - that they describe for the first time in the second paper. They recognised that muscle fibres would respond to each impulse sent by the innervating motor neurone and that therefore muscle fibre recordings provided information on the times of activation of the motor nerve fibres which were as accurate as a direct record from the nerve. These observations and the description of the concentric needle electrode opened the era of motor unit recordings in humans, which have continued for almost a century and have provided a comprehensive view of the neural control of movement at the motor unit level. Despite important advances in technology, many of the principles of motor unit behaviour that would be investigated in the subsequent decades were canvassed in the two papers by Adrian and Bronk. For example, they described the concomitant motor neurones' recruitment and rate coding for force modulation, synchronisation of motor unit discharges, and the dependence of discharge rate on motor unit recruitment threshold. Here, we summarise their observations and discuss the impact of their work. We highlight the advent of the concentric needle, and its subsequent influence on motor control research.

Post-contraction potentiation can react inversely to post-activation potentiation depending on the test contraction force

The surface electromyographic (EMG) activity of the biceps brachii during weak elbow flexion reportedly increases immediately after strong elbow flexion, even during the exertion of a given force. This phenomenon is called post-contraction potentiation (EMG-PCP). However, the effects of test contraction intensity (TCI) on EMG-PCP remain unclear. This study evaluated PCP levels at various TCI values. Sixteen healthy participants were asked to perform a force matching task (2%, 10%, or 20% of the maximum voluntary contraction [MVC]) before (Test 1) and after (Test 2) a conditioning contraction (50% of MVC). With a 2% TCI, the EMG amplitude was higher in Test 2 than in Test 1. With a 20% TCI, the EMG amplitude was lower in Test 2 than in Test 1. Furthermore, EMG spectral analyses showed that the α- and β-band power ratios in Test 2 were enhanced by 2% TCI compared with Test 1. These findings suggest that TCI is crucial in determining the EMG-force relationship immediately after a brief intensive contraction.

Altered neuromuscular control in the vastus medialis following anterior cruciate ligament injury: A recurrence quantification analysis of electromyogram recruitment

BACKGROUND

Neuromuscular deficits exist following anterior cruciate ligament (ACL) injury. To observe these deficits, we examined nonlinear characteristics of vastus medialis electromyography (EMG) signals during submaximal isometric knee extensor contractions. Our purpose was to examine if determinism and entropy in EMG signals reflected neuromuscular control deficits in individuals with ACL-deficient limbs.

METHODS

24 participants (12 male, 12 female, mean age = 18.8 ± 3.1 years) with unilaterally injured ACLs and 25 age-similar healthy controls (11 male, 14 female, mean age = 18.8 ± 3.1 years) volunteered. Isometric knee extensions were tested at 10%, 25%, 35%, and 50% maximum voluntary contractions. Surface electrodes adhered over the vastus medialis captured EMG signals. EMG data were processed with recurrence quantification analyses. Specifically, determinism (an index of system predictability) and entropy (an index of system disorder) were calculated from recurrence plots.

FINDINGS

Determinism and entropy in EMG signals were lower in the injured than uninjured limb, and lower than that from healthy controls (P < .05).

INTERPRETATION

Vastus medialis EMG signals from the injured limb were less predictable and less complex than those from healthy limbs. The findings reflect impaired neuromuscular control in the injured limb's quadriceps and are consistent with a 'loss of complexity' hypothesis in physiologic signals emanating from pathologic states. Determinism and entropy in EMG signals may represent biomarkers of one's neuromuscular control system.

Handedness is associated with less common input to spinal motor neurons innervating different hand muscles

Whether the neural control of manual behaviours differs between the dominant and non-dominant hand is poorly understood. This study aimed to determine whether the level of common synaptic input to motor neurons innervating the same or different muscles differs between the dominant and the non-dominant hand. Seventeen participants performed two motor tasks with distinct mechanical requirements: an isometric pinch and an isometric rotation of a pinched dial. Each task was performed at 30% of maximum effort and was repeated with the dominant and non-dominant hand. Motor units were identified from two intrinsic (flexor digitorum interosseous and thenar) and one extrinsic muscle (flexor digitorum superficialis) from high-density surface electromyography recordings. Two complementary approaches were used to estimate common synaptic inputs. First, we calculated the coherence between groups of motor neurons from the same and from different muscles. Then, we estimated the common input for all pairs of motor neurons by correlating the low-frequency oscillations of their discharge rate. Both analyses led to the same conclusion, indicating less common synaptic input between motor neurons innervating different muscles in the dominant hand than in the non-dominant hand, which was only observed during the isometric rotation task. No between-side differences in common input were observed between motor neurons of the same muscle. This lower level of common input could confer higher flexibility in the recruitment of motor units, and therefore, in mechanical outputs. Whether this difference between the dominant and non-dominant arm is the cause or the consequence of handedness remains to be determined.

Effect of synchronization of firings of different motor unit types on the force variability in a model of the rat medial gastrocnemius muscle

The synchronized firings of active motor units (MUs) increase the oscillations of muscle force, observed as physiological tremor. This study aimed to investigate the effects of synchronizing the firings within three types of MUs (slow—S, fast resistant to fatigue–FR, and fast fatigable–FF) on the muscle force production using a mathematical model of the rat medial gastrocnemius muscle. The model was designed based on the actual proportion and physiological properties of MUs and motoneurons innervating the muscle. The isometric muscle and MU forces were simulated by a model predicting non-synchronized firing of a pool of 57 MUs (including 8 S, 23 FR, and 26 FF) to ascertain a maximum excitatory signal when all MUs were recruited into the contraction. The mean firing frequency of each MU depended upon the twitch contraction time, whereas the recruitment order was determined according to increasing forces (the size principle). The synchronization of firings of individual MUs was simulated using four different modes and inducing the synchronization of firings within three time windows (± 2, ± 4, and ± 6 ms) for four different combinations of MUs. The synchronization was estimated using two parameters, the correlation coefficient and the cross-interval synchronization index. The four scenarios of synchronization increased the values of the root-mean-square, range, and maximum force in correlation with the increase of the time window. Greater synchronization index values resulted in higher root-mean-square, range, and maximum of force outcomes for all MU types as well as for the whole muscle output; however, the mean spectral frequency of the forces decreased, whereas the mean force remained nearly unchanged. The range of variability and the root-mean-square of forces were higher for fast MUs than for slow MUs; meanwhile, the relative values of these parameters were highest for slow MUs, indicating their important contribution to muscle tremor, especially during weak contractions.

The synchronization of firings of motor units (MUs), the smallest functional elements of skeletal muscle increases fluctuations in muscle force, known as physiological tremor, which can disturb high-precision movements. In this study, we adopted a recently proposed muscle model consisting of MUs of three different types (fast fatigable, fast resistant to fatigue, and slow) to study four different scenarios of MU synchronization during a steady level of excitatory input to motoneurons. The discharge patterns were synchronized between pairs of MUs by shifting in time individual pulses, which occurred within a short time interval, and a degree of synchronization was then estimated. The increased synchronization index resulted in increased force variability for all MU types as well as for the whole muscle output; however, the mean force levels remained nearly unchanged, whereas the frequencies of the force oscillations were decreased. The absolute range of force variability was higher for fast than for slow MUs, indicating their dominant influence on muscle tremor at strong contractions, but the highest relative increase in force variability was observed for synchronized slow MUs, indicating their significant contribution to tremor during weak contractions, in which only slow MUs are active.

Rigorous performance assessment of the algorithms for resolving motor unit action potential superpositions

It is necessary to decompose the intra-muscular EMG signal to extract motor unit action potential (MUAP) waveforms and firing times. Some algorithms were proposed in the literature to resolve superimposed MUAPs, including Peel-Off (PO), branch and bound (BB), genetic algorithm (GA), and particle swarm optimization (PSO). This study aimed to compare these algorithms in terms of overall accuracy and running time. Two sets of two-to-five MUAP templates (set1: a wide range of energies, and set2: a high degree of similarity) were used. Such templates were time-shifted, and white Gaussian noise was added. A total of 1000 superpositions were simulated for each template and were resolved using PO (also, POI: interpolated PO), BB, GA, and PSO algorithms. The generalized estimating equation was used to identify which method significantly outperformed, while the overall rank product was used for overall ranking. The rankings were PSO, BB, GA, PO, and POI in the first, and BB, PSO, GA, PO, POI in the second set. The overall ranking was BB, PSO, GA, PO, and POI in the entire dataset. Although the BB algorithm is generally fast, there are cases where the BB algorithm is too slow and it is thus not suitable for real-time applications.

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.

Maturation of feedforward toe walking motor program is impaired in children with cerebral palsy

Voluntary toe walking in adults is characterized by feedforward control of ankle muscles in order to ensure optimal stability of the ankle joint at ground impact. Toe walking is frequently observed in children with cerebral palsy, but the mechanisms involved have not been clarified. Here, we investigated maturation of voluntary toe walking in typically-developing children and typically-developed adults and compared it to involuntary toe walking in children with cerebral palsy. Twenty-eight children with cerebral palsy (age 3-14 years), 24 typically-developing children (age 2-14 years) and 15 adults (mean age 30.7 years) participated in the study. EMG activity was measured from the tibialis anterior and soleus muscles together with knee and ankle joint position during treadmill walking. In typically-developed adults, low step-to-step variability of the drop of the heel after ground impact was correlated with low tibialis anterior and high soleus EMG with no significant coupling between the antagonist muscle EMGs. Typically-developing children showed a significant age-related decline in EMG amplitude reaching an adult level at 10-12 years of age. The youngest typically-developing children showed a broad peak EMG-EMG synchronization (>100 ms) associated with large 5-15 Hz coherence between antagonist muscle activities. EMG coherence declined with age and at the age of 10-12 years no correlation was observed similar to adults. This reduction in coherence was closely related to improved step-to-step stability of the ankle joint position. Children with cerebral palsy generally showed lower EMG levels than typically-developing children and larger step-to-step variability in ankle joint position. In contrast to typically-developing children, children with cerebral palsy showed no age-related decline in tibialis anterior EMG amplitude. Motor unit synchronization and 5-15 Hz coherence between antagonist EMGs was observed more frequently in children with cerebral palsy when compared to typically-developing children and in contrast to typically-developing participants there was no age-related decline. We conclude that typically-developing children develop mature feedforward control of ankle muscle activity as they age, such that at age 10-12 years there is little agonist-antagonist muscle co-contraction around the time of foot-ground contact during toe walking. Children with cerebral palsy, in contrast, continue to co-contract agonist and antagonist ankle muscles when toe walking. We speculate that children with cerebral palsy maintain a co-contraction activation pattern when toe walking due to weak muscles and insufficient motor and sensory signalling necessary for optimization of feedforward motor programs. These findings are important for understanding of the pathophysiology and treatment of toe walking.

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.

Sustained involuntary muscle activity in cerebral palsy and stroke: same symptom, diverse mechanisms

Individuals with lesions of central motor pathways frequently suffer from sustained involuntary muscle activity. This symptom shares clinical characteristics with dystonia but is observable in individuals classified as spastic. The term spastic dystonia has been introduced, although the underlying mechanisms of involuntary activity are not clarified and vary between individuals depending on the disorder. This study aimed to investigate the nature and pathophysiology of sustained involuntary muscle activity in adults with cerebral palsy and stroke. Seventeen adults with cerebral palsy (Gross Motor Function Classification System I–V), 8 adults with chronic stroke and 14 control individuals participated in the study. All individuals with cerebral palsy or stroke showed increased resistance to passive movement with Modified Ashworth Scale >1. Two-minute surface EMG recordings were obtained from the biceps muscle during attempted rest in three positions of the elbow joint; a maximally flexed position, a 90-degree position and a maximally extended position. Cross-correlation analysis of sustained involuntary muscle activity from individuals with cerebral palsy and stroke, and recordings of voluntary isometric contractions from control individuals were performed to examine common synaptic drive. In total, 13 out of 17 individuals with cerebral palsy and all 8 individuals with stroke contained sustained involuntary muscle activity. In individuals with cerebral palsy, the level of muscle activity was not affected by the joint position. In individuals with stroke, the level of muscle activity significantly (P < 0.05) increased from the flexed position to the 90 degree and extended position. Cumulant density function indicated significant short-term synchronization of motor unit activities in all recordings. All groups exhibited significant coherence in the alpha (6–15 Hz), beta (16–35 Hz) and early gamma band (36–60 Hz). The cerebral palsy group had lower alpha band coherence estimates, but higher gamma band coherence estimates compared with the stroke group. Individuals with increased resistance to passive movement due to cerebral palsy or stroke frequently suffer sustained involuntary muscle activity, which cannot exclusively be described by spasticity. The sustained involuntary muscle activity in both groups originated from a common synaptic input to the motor neuron pool, but the generating mechanisms could differ between groups. In cerebral palsy it seemed to originate more from central mechanisms, whereas peripheral mechanisms likely play a larger role in stroke. The sustained involuntary muscle activity should not be treated simply like the spinal stretch reflex mediated symptom of spasticity and should not either be treated identically in both groups.

Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force

Motor unit firing times are weakly coupled across a range of frequencies during voluntary contractions. Coherent activity within the beta-band (15-35 Hz) has been linked to oscillatory cortical processes, providing evidence of functional connectivity between the motoneuron pool and motor cortex. The aim of this study was to investigate whether beta-band motor unit coherence is altered with increasing abduction force in the first dorsal interosseous muscle. Coherence between motor unit firing times, extracted from decomposed surface electromyography (EMG) signals, was investigated in 17 subjects at 10, 20, 30, and 40% of maximum voluntary contraction. Corresponding changes in nonlinear surface EMG features (specifically sample entropy and determinism, which are sensitive to motor unit synchronization) were also examined. A reduction in beta-band and alpha-band coherence was observed as force increased [F(3, 151) = 32, P < 0.001 and F(3, 151) = 27, P < 0.001, respectively], accompanied by corresponding changes in nonlinear surface EMG features. A significant relationship between the nonlinear features and motor unit coherence was also detected (r = -0.43 ± 0.1 and r = 0.45 ± 0.1 for sample entropy and determinism, respectively; both P < 0.001). The reduction in beta-band coherence suggests a change in the relative contribution of correlated and uncorrelated presynaptic inputs to the motoneuron pool, and/or a decrease in the responsiveness of the motoneuron pool to synchronous inputs at higher forces. The study highlights the importance of considering muscle activation when investigating changes in motor unit coherence or nonlinear EMG features and examines other factors that can influence coherence estimation.NEW & NOTEWORTHY Intramuscular alpha- and beta-band coherence decreased as muscle contraction force increased. Beta-band coherence was higher in groups of high-threshold motor units than in simultaneously active lower threshold units. Alterations in motor unit coherence with increases or decreases in force and with the onset of fatigue were accompanied by corresponding changes in surface electromyography sample entropy and determinism. Mixed-model analysis indicated mean firing rate and number of motor units also influenced the coherence estimate.

Highly Heterogeneous Excitatory Connections Require Less Amount of Noise to Sustain Firing Activities in Cortical Networks

Cortical networks both in vivo and in vitro sustain asynchronous irregular firings with extremely low frequency. To realize such self-sustained activity in neural network models, balance between excitatory and inhibitory activities is known to be one of the keys. In addition, recent theoretical studies have revealed that another feature commonly observed in cortical networks, i.e., sparse but strong connections and dense weak connections, plays an essential role. The previous studies, however, have not thoroughly considered the cooperative dynamics between a network of such heterogeneous synaptic connections and intrinsic noise. The noise stimuli, representing inherent nature of the neuronal activities, e.g., variability of presynaptic discharges, should be also of significant importance for sustaining the irregular firings in cortical networks. Here, we numerically demonstrate that highly heterogeneous distribution, typically a lognormal type, of excitatory-to-excitatory connections, reduces the amount of noise required to sustain the network firing activities. In the sense that noise consumes an energy resource, the heterogeneous network receiving less amount of noise stimuli is considered to realize an efficient dynamics in cortex. A noise-driven network of bi-modally distributed synapses further shows that many weak and a few very strong synapses are the key feature of the synaptic heterogeneity, supporting the network firing activity.

Impaired Ability to Suppress Excitability of Antagonist Motoneurons at Onset of Dorsiflexion in Adults with Cerebral Palsy

We recently showed that impaired gait function in adults with cerebral palsy (CP) is associated with reduced rate of force development in ankle dorsiflexors. Here, we explore potential mechanisms. We investigated the suppression of antagonist excitability, calculated as the amount of soleus H-reflex depression at the onset of ankle dorsiflexion compared to rest, in 24 adults with CP (34.3 years, range 18–57; GMFCS 1.95, range 1–3) and 15 healthy, age-matched controls. Furthermore, the central common drive to dorsiflexor motoneurons during a static contraction in the two groups was examined by coherence analyses. The H-reflex was significantly reduced by 37% at the onset of dorsiflexion compared to rest in healthy adults (P < 0.001) but unchanged in adults with CP (P = 0.91). Also, the adults with CP had significantly less coherence. These findings suggest that the ability to suppress antagonist motoneuronal excitability at movement onset is impaired and that the central common drive during static contractions is reduced in adults with CP.

Decrease in force steadiness with aging is associated with increased power of the common but not independent input to motor neurons

Declines in motor function with advancing age have been attributed to changes occurring at all levels of the neuromuscular system. However, the impact of aging on the control of muscle force by spinal motor neurons is not yet understood. In this study on 20 individuals aged between 24 and 75 yr (13 men, 7 women), we investigated the common synaptic input to motor neurons of the tibialis anterior muscle and its impact on force control. Motor unit discharge times were identified from high-density surface EMG recordings during isometric contractions at forces of 20% of maximal voluntary effort. Coherence analysis between motor unit spike trains was used to characterize the input to motor neurons. The decrease in force steadiness with age ( R² = 0.6, P < 0.01) was associated with an increase in the amplitude of low-frequency oscillations of functional common synaptic input to motor neurons ( R² = 0.59; P < 0.01). The relative proportion of common input to independent noise at low frequencies increased with variability (power) in common synaptic input. Moreover, variability in interspike interval did not change and strength of the common input in the gamma band decreased with age ( R² = 0.22; P < 0.01). The findings indicate that age-related reduction in the accuracy of force control is associated with increased common fluctuations to motor neurons at low frequencies and not with an increase in independent synaptic input. NEW & NOTEWORTHY The influence of aging on the role of spinal motor neurons in accurate force control is not yet understood. We demonstrate that aging is associated with increased oscillations in common input to motor neurons at low frequencies and with a decrease in the relative strength of gamma oscillations. These results demonstrate that the synaptic inputs to motor neurons change across the life span and contribute to a decline in force control.

Improved muscle activation using proximal nerve stimulation with subthreshold current pulses at kilohertz-frequency

OBJECTIVE

Transcutaneous electrical nerve stimulation can help individuals with neurological disorders to regain their motor function by activating muscles externally. However, conventional stimulation technique often induces near-simultaneous recruitment of muscle fibers, leading to twitch forces time-locked to the stimulation.

APPROACH

To induce less synchronized activation of finger flexor muscles, we delivered clustered narrower pulses to the proximal segment of the median and ulnar nerves at a carrier frequency of either 10 kHz (with an 80 µs pulse width) or 7.14 kHz (with a 120 µs pulse width) (high-frequency mode, HF), and different clustered pulses were delivered at a frequency of 30 or 40 Hz. Conventional stimulation with pulse frequency of 30 or 40 Hz (low-frequency mode, LF) was used for comparison. With matched elicited muscle forces between the HF and LF modes, the force variation, the high-density electromyogram (EMG) signals recorded at the finger flexor muscles and stimulation-induced-pain levels were compared.

MAIN RESULTS

The compound action potentials in the 10 kHz HF mode revealed a significant difference (i.e. a lower amplitude and area, and a wider duration) compared with the LF mode, indicating cancellations of asynchronized action potentials. A smaller fluctuation in the elicited forces in the 10 kHz mode further demonstrated the less synchronized activation of different motor units. These effects tended to be weaker in the 7.14 kHz HF condition. However, the levels of pain sensation was not reduced in the HF mode potentially due to the high charge density used in the HF mode. Our findings indicated that different nerve fibers were recruited asynchronously through summations of different numbers of subthreshold depolarizations in the HF mode.

SIGNIFICANCE

Compared with the LF mode, the HF mode stimulation was capable of activating the nerve fibers in a less synchronized way, which is more similar to the physiological activation pattern.

Characterization of corticospinal activation of finger motor neurons during precision and power grip in humans

Direct and indirect corticospinal pathways to finger muscles may play a different role in control of the upper extremity. We used transcranial magnetic stimulation (TMS) and coherence analysis to characterize the corticospinal drive to the first dorsal interosseous (FDI) and abductor pollicis brevis (APB) when active during a precision and power grip task. In experiment 1, single motor units were recorded during precision grip and power grip in 20 adults (25.2 ± 7.1 years). Post-stimulus time histograms (PSTH) were obtained following TMS. In experiment 2, coherence and cross-correlation analysis of the FDI and APB surface EMG were used to investigate the temporal organization of corticospinal drive during precision grip and power grip in 15 adults (27.4 ± 8.1 years). We found no significant differences in PSTH peak onset (26.6 ± 1.9 vs. 26.7 ± 2.0 ms, p = 0.75), maximal peak (27.4 ± 1.9 vs. 27.4 ± 1.9 ms, p = 1.0) or peak duration (2.3 ± 1.1 vs. 2.3 ± 1.0 ms, p = 0.75) for the 11 recovered motor units during precision grip and power grip. Also, no significant difference in coherence or the width of the synchronization peaks during precision grip (7.2 ± 3.7 ms) and power grip (7.9 ± 3.1 ms) could be observed (p = 0.59). The short duration of peaks elicited in the PSTH of single motor units following TMS and central synchronization peaks of voluntarily activated motor units during precision and power grip suggests that the direct corticospinal pathway (the corticomotoneuronal system) is equally involved in the control of both tasks. The data do not support that indirect pathways would make a larger contribution to power grip.

A critical period of corticomuscular and EMG-EMG coherence detection in healthy infants aged 9-25 weeks

KEY POINTS

The early postnatal development of functional corticospinal connections in human infants is not fully clarified. Corticospinal drive to upper and lower limb muscle shows developmental changes with an increased functional coupling in infants between 9 and 25 weeks in the beta frequency band. The changes in functional coupling coincide with the developmental period where fidgety movements are present in healthy infants. Data support a possible sensitive period where functional connections between corticospinal tract fibres and spinal motoneurones undergo activity-dependent reorganization.

ABSTRACT

The early postnatal development of functional corticospinal connections in human infants is not fully clarified. We used EEG and EMG to investigate the development of corticomuscular and intramuscular coherence as indicators of functional corticospinal connectivity in healthy infants aged 1-66 weeks. EEG was recorded over leg and hand area of motor cortex. EMG recordings were made from right ankle dorsiflexor and right wrist extensor muscles. Quantification of the amount of corticomuscular coherence in the 20-40 Hz frequency band showed a significantly larger coherence for infants aged 9-25 weeks compared to younger and older infants. Coherence between paired EMG recordings from tibialis anterior muscle in the 20-40 Hz frequency band was also significantly larger for the 9-25 week age group. A low-amplitude, broad-duration (40-50 ms) central peak of EMG-EMG synchronization was observed for infants younger than 9 weeks, whereas a short-lasting (10-20 ms) central peak was observed for EMG-EMG synchronization in older infants. This peak was largest for infants aged 9-25 weeks. These data suggest that the corticospinal drive to lower and upper limb muscles shows significant developmental changes with an increase in functional coupling in infants aged 9-25 weeks, a period which coincides partly with the developmental period of normal fidgety movements. We propose that these neurophysiological findings may reflect the existence of a sensitive period where the functional connections between corticospinal tract fibres and spinal motoneurones undergo activity-dependent reorganization. This may be relevant for the timing of early therapy interventions in infants with pre- and perinatal brain injury.

A Real-Time Method for Decoding the Neural Drive to Muscles Using Single-Channel Intra-Muscular EMG Recordings

The neural command from motor neurons to muscles - sometimes referred to as the neural drive to muscle - can be identified by decomposition of electromyographic (EMG) signals. This approach can be used for inferring the voluntary commands in neural interfaces in patients with limb amputations. This paper proposes for the first time an innovative method for fully automatic and real-time intramuscular EMG (iEMG) decomposition. The method is based on online single-pass density-based clustering and adaptive classification of bivariate features, using the concept of potential measure. No attempt was made to resolve superimposed motor unit action potentials. The proposed algorithm was validated on sets of simulated and experimental iEMG signals. Signals were recorded from the biceps femoris long-head, vastus medialis and lateralis and tibialis anterior muscles during low-to-moderate isometric constant-force and linearly-varying force contractions. The average number of missed, duplicated and erroneous clusters for the examined signals was [Formula: see text], [Formula: see text], and [Formula: see text], respectively. The average decomposition accuracy (defined similar to signal detection theory but without using True Negatives in the denominator) and coefficient of determination (variance accounted for) for the cumulative discharge rate estimation were [Formula: see text], and [Formula: see text], respectively. The time cost for processing each 200[Formula: see text]ms iEMG interval was [Formula: see text] (21-97)[Formula: see text]ms. However, computational time generally increases over time as a function of frames/signal epochs. Meanwhile, the incremental accuracy defined as the accuracy of real-time analysis of each signal epoch, was [Formula: see text]% for epochs recorded after initial one second. The proposed algorithm is thus a promising new tool for neural decoding in the next-generation of prosthetic control.

Correlation between discharge timings of pairs of motor units reveals the presence but not the proportion of common synaptic input to motor neurons

We investigated whether correlation measures derived from pairs of motor unit (MU) spike trains are reliable indicators of the degree of common synaptic input to motor neurons. Several 50-s isometric contractions of the biceps brachii muscle were performed at different target forces ranging from 10 to 30% of the maximal voluntary contraction relying on force feedback. Forty-eight pairs of MUs were examined at various force levels. Motor unit synchrony was assessed by cross-correlation analysis using three indexes: the output correlation as the peak of the cross-histogram (ρ) and the number of synchronous spikes per second (CIS) and per trigger (E). Individual analysis of MU pairs revealed that ρ, CIS, and E were most often positively associated with discharge rate (87, 85, and 76% of the MU pairs, respectively) and negatively with interspike interval variability (69, 65, and 62% of the MU pairs, respectively). Moreover, the behavior of synchronization indexes with discharge rate (and interspike interval variability) varied greatly among the MU pairs. These results were consistent with theoretical predictions, which showed that the output correlation between pairs of spike trains depends on the statistics of the input current and motor neuron intrinsic properties that differ for different motor neuron pairs. In conclusion, the synchronization between MU firing trains is necessarily caused by the (functional) common input to motor neurons, but it is not possible to infer the degree of shared common input to a pair of motor neurons on the basis of correlation measures of their output spike trains.NEW & NOTEWORTHY The strength of correlation between output spike trains is only poorly associated with the degree of common input to the population of motor neurons. The synchronization between motor unit firing trains is necessarily caused by the (functional) common input to motor neurons, but it is not possible to infer the degree of shared common input to a pair of motor neurons on the basis of correlation measures of their output spike trains.

Characteristics of the Motor Units during Sternocleidomastoid Isometric Flexion among Patients with Mechanical Neck Disorder and Asymptomatic Individuals

Mechanical neck disorder is a widespread and non-neurological musculoskeletal condition resulting from modern lifestyles. Presently, the fundamental electrophysiological properties of the motor units of the sternocleidomastoid muscles and the characteristics of the short-term synchronization of the motor unit in patients with neck pain are ambiguous. This study therefore aims to clarify the fundamental electrophysiological properties of the motor units of the sternocleidomastoid muscles in patients with mechanical neck disorder and in asymptomatic individuals. We further investigated whether alterations in the degree of motor unit short-term synchronization occur. The surface electrophysiological signals of the bilateral sternal heads of the sternocleidomastoid muscles of twelve patients with mechanical neck disorder and asymptomatic individuals were detected at 25% of the maximum voluntary contraction during cervical isometric flexion and then decomposed into individual motor unit action potential trains. We found that the patients with mechanical neck disorder showed significantly higher initial and mean firing rates of the sternocleidomastoid muscles and displayed substantially lower motor unit short-term synchronization values compared with the asymptomatic subjects. Consequently, these convincing findings support the assertion that patients with mechanical neck disorder display altered neuromuscular control strategies, such as the reinforcement of motor unit recruitment firing rates in the sternocleidomastoid muscles. The motor units of these patients also revealed neural recruitment strategies with relatively poor efficiency when executing the required motor tasks.

How we Walk: Central Control of Muscle Activity during Human Walking

Recent advances in noninvasive electrophysiological and brain imaging techniques have made investigation of the central control of human walking possible. We are thus now able to ask in what way the motor control circuitries in the human brain and spinal cord have been modified in order to control bipedal walking. This information is of importance not only for our understanding of basic control strategies and paradigms but also for future attempts at rehabilitating the gait ability of patients after lesions of the brain and spinal cord.

Synchronization of motor unit firings: an epiphenomenon of firing rate characteristics not common inputs

Synchronous motor unit firing instances have been attributed to anatomical inputs shared by motoneurons. Yet, there is a lack of empirical evidence confirming the notion that common inputs elicit synchronization under voluntary conditions. We tested this notion by measuring synchronization between motor unit action potential trains (MUAPTs) as their firing rates progressed within a contraction from a relatively low force level to a higher one. On average, the degree of synchronization decreased as the force increased. The common input notion provides no empirically supported explanation for the observed synchronization behavior. Therefore, we investigated a more probable explanation for synchronization. Our data set of 17,546 paired MUAPTs revealed that the degree of synchronization varies as a function of two characteristics of the motor unit firing rate: the similarity and the slope as a function of force. Both are measures of the excitation of the motoneurons. As the force generated by the muscle increases, the firing rate slope decreases, and the synchronization correspondingly decreases. Different muscles have motor units with different firing rate characteristics and display different amounts of synchronization. Although this association is not proof of causality, it consistently explains our observations and strongly suggests further investigation. So viewed, synchronization is likely an epiphenomenon, subject to countless unknown neural interactions. As such, synchronous firing instances may not be the product of a specific design and may not serve a specific physiological purpose. Our explanation for synchronization has the advantage of being supported by empirical evidence, whereas the common input does not.

A Novel Framework Based on FastICA for High Density Surface EMG Decomposition

This study presents a progressive FastICA peel-off (PFP) framework for high-density surface electromyogram (EMG) decomposition. The novel framework is based on a shift-invariant model for describing surface EMG. The decomposition process can be viewed as progressively expanding the set of motor unit spike trains, which is primarily based on FastICA. To overcome the local convergence of FastICA, a peel-off strategy, i.e., removal of the estimated motor unit action potential trains from the previous step, is used to mitigate the effects of the already identified motor units, so more motor units can be extracted. A constrained FastICA is applied to assess the extracted spike trains and correct possible erroneous or missed spikes. These procedures work together to improve decomposition performance. The proposed framework was validated using simulated surface EMG signals with different motor unit numbers (30, 70, 91) and SNRs (20, 10, and 0 dB). The results demonstrated relatively large numbers of extracted motor units and high accuracies (high F1-scores). The framework was tested with 111 trials of 64-channel electrode array experimental surface EMG signals during the first dorsal interosseous muscle contraction at different intensities. On average 14.1 ±5.0 motor units were identified from each trial of experimental surface EMG signals.

Phase resetting for a network of oscillators via phase response curve approach

The problem of phase regulation for a population of oscillating systems is considered. The proposed control strategy is based on a phase response curve (PRC) model of an oscillator (the first-order reduced model obtained for linearized system and inputs with infinitesimal amplitude). It is proven that the control provides phase resetting for the original nonlinear system. Next, the problem of phase resetting for a network of oscillators is considered when applying a common control input. Performance of the obtained solutions is demonstrated via computer simulation for three different models of circadian/neural oscillators.

Motor unit firing pattern, synchrony and coherence in a deafferented patient

The firing of spinal motoneurons (MNs) is controlled continuously by inputs from muscle, joint and skin receptors. Besides altering MN synaptic drive, the removal of these inputs is liable to alter the synaptic noise and, thus, the variability of their tonic activity. Sensory afferents, which are a major source of common and/or synchronized inputs shared by several MNs, may also contribute to the coupling in the time and frequency domains (synchrony and coherence, respectively) observed when cross-correlation and coherence analyses are applied to the discharges of MN pairs. Surprisingly, no consistent changes in firing frequency, nor in synchrony and coherence were reported to affect the activity of 3 pairs of motor units (MUs) tested in a case of sensory polyradiculoneuropathy (SPRNP), leading to an irreversible loss of large diameter sensory afferents (Farmer et al., 1993). Such a limited sample, however, precludes a definite conclusion about the actual impact that a chronic loss of muscle and cutaneous afferents may have on the firing properties of human MUs. To address this issue, the firing pattern of 92 MU pairs was analyzed at low contraction force in a case of SPRNP leading similarly to a permanent loss of proprioceptive inputs. Compared with 8 control subjects, MNs in this patient tended to discharge with slightly shorter inter-spike intervals but with greater variability. Synchronous firing tended to occur more frequently with a tighter coupling in the patient. There was no consistent change in coherence in the 15–30 Hz frequency range attributed to the MN corticospinal drive, but a greater coherence was observed below 5 Hz and between 30 and 60 Hz in the patient. The possible origins of the greater irregularity in MN tonic discharges, the tighter coupling of the synchronous firing and the changes in coherence observed in the absence of proprioceptive inputs are discussed.

Synchronization among neuronal pools without common inputs: in vivo study

Periodic synchronization of activity among neuronal pools has been related to substantial neural processes and information throughput in the neocortical network. However, the mechanisms of generating such periodic synchronization among distributed pools of neurons remain unclear. We hypothesize that to a large extent there is interplay between the topology of the neocortical networks and their reverberating modes of activity. The firing synchronization is governed by a nonlocal mechanism, the network delay loops, such that distant neuronal pools without common drives can be synchronized. This theoretical interplay between network topology and the synchronized mode is verified using an iterative procedure of a single intracellularly recorded neuron in vivo, imitating the dynamics of the entire network. The input is injected to the neuron via the recording electrode as current and computed from the filtered, evoked spikes of its pre-synaptic sources, previously emulated by the same neuron. In this manner we approximate subthreshold synaptic inputs from afferent neuronal pools to the neuron. Embedding the activity of these recurrent motifs in the intact brain allows us to measure the effects of connection probability, synaptic strength, and ongoing activity on the neuronal synchrony. Our in vivo experiments indicate that an initial stimulus given to a single pool is dynamically evolving into the formations of zero-lag and cluster synchronization. By applying results from theoretical models and in vitro experiments to in vivo activity in the intact brain, we support the notion that this mechanism may account for the binding activity across distributed brain areas.

Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings

Over the past four decades, various methods have been implemented to measure synchronization of motor-unit firings. In this work, we provide evidence that prior reports of the existence of universal common inputs to all motoneurons and the presence of long-term synchronization are misleading, because they did not use sufficiently rigorous statistical tests to detect synchronization. We developed a statistically based method (SigMax) for computing synchronization and tested it with data from 17,736 motor-unit pairs containing 1,035,225 firing instances from the first dorsal interosseous and vastus lateralis muscles--a data set one order of magnitude greater than that reported in previous studies. Only firing data, obtained from surface electromyographic signal decomposition with >95% accuracy, were used in the study. The data were not subjectively selected in any manner. Because of the size of our data set and the statistical rigor inherent to SigMax, we have confidence that the synchronization values that we calculated provide an improved estimate of physiologically driven synchronization. Compared with three other commonly used techniques, ours revealed three types of discrepancies that result from failing to use sufficient statistical tests necessary to detect synchronization. 1) On average, the z-score method falsely detected synchronization at 16 separate latencies in each motor-unit pair. 2) The cumulative sum method missed one out of every four synchronization identifications found by SigMax. 3) The common input assumption method identified synchronization from 100% of motor-unit pairs studied. SigMax revealed that only 50% of motor-unit pairs actually manifested synchronization.

Limitations of the spike-triggered averaging for estimating motor unit twitch force: a theoretical analysis

Contractile properties of human motor units provide information on the force capacity and fatigability of muscles. The spike-triggered averaging technique (STA) is a conventional method used to estimate the twitch waveform of single motor units in vivo by averaging the joint force signal. Several limitations of this technique have been previously discussed in an empirical way, using simulated and experimental data. In this study, we provide a theoretical analysis of this technique in the frequency domain and describe its intrinsic limitations. By analyzing the analytical expression of STA, first we show that a certain degree of correlation between the motor unit activities prevents an accurate estimation of the twitch force, even from relatively long recordings. Second, we show that the quality of the twitch estimates by STA is highly related to the relative variability of the inter-spike intervals of motor unit action potentials. Interestingly, if this variability is extremely high, correct estimates could be obtained even for high discharge rates. However, for physiological inter-spike interval variability and discharge rate, the technique performs with relatively low estimation accuracy and high estimation variance. Finally, we show that the selection of the triggers that are most distant from the previous and next, which is often suggested, is not an effective way for improving STA estimates and in some cases can even be detrimental. These results show the intrinsic limitations of the STA technique and provide a theoretical framework for the design of new methods for the measurement of motor unit force twitch.

Synchronization of low- and high-threshold motor units

INTRODUCTION

We examined the degree of synchronization for both low- and high-threshold motor unit (MU) pairs at high force levels.

METHODS

MU spike trains were recorded from the quadriceps during high-force isometric leg extensions. Short-term synchronization (between -6 and 6 ms) was calculated for every unique MU pair for each contraction.

RESULTS

At high force levels, earlier recruited motor unit pairs (low-threshold) demonstrated relatively low levels of short-term synchronization (approximately 7.3% extra firings than would have been expected by chance). However, the magnitude of synchronization increased significantly and linearly with mean recruitment threshold (reaching 22.1% extra firings for motor unit pairs recruited above 70% MVC).

CONCLUSIONS

Three potential mechanisms that could explain the observed differences in synchronization across motor unit types are proposed and discussed.

Reliability of spike triggered averaging of the surface electromyogram for motor unit action potential estimation

INTRODUCTION

The reliability of estimated motor unit parameters using spike triggered averaging (STA) of the surface electromyogram (sEMG) has not been tested thoroughly. We investigated factors that may induce amplitude bias in estimated motor unit action potentials (MUAPs) and shape variations.

METHODS

An sEMG record was simulated. MUAPs were then estimated from the STA of the simulated EMG.

RESULTS

Variations in MUAP duration led to under-estimation of real MUAP amplitude, while synchronized firing led to over-estimation of amplitude. Spurious firing resulted in over-estimation of the amplitude of small motor units but under-estimation of the amplitude of large ones. Variability in amplitude and high firing rates had minimal influence on amplitude estimation. High firing rates and variation in MUAP duration led to large variations in MUAP shape. Estimation errors also correlated with shape variations.

CONCLUSIONS

Recommendations to enhance the accuracy of the STA estimates have been proposed.

Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band

Rectification of surface EMG before spectral analysis is a well-established preprocessing method used in the detection of motor unit firing patterns. A number of recent studies have called into question the need for rectification before spectral analysis, pointing out that there is no supporting experimental evidence to justify rectification. We present an analysis of 190 records from 13 subjects consisting of simultaneous recordings of paired single motor units and surface EMG from the extensor digitorum longus muscle during middle finger extension against gravity (unloaded condition) and against gravity plus inertial loading (loaded condition). We directly examine the hypothesis that rectified surface EMG is a better predictor of the frequency components of motor unit synchronization than the unrectified (or raw) EMG in the beta-frequency band (15-32 Hz). We use multivariate analysis and estimate the partial coherence between the paired single units using both rectified and unrectified surface EMG as a predictor. We use a residual partial correlation measure to quantify the difference between raw and rectified EMG as predictor and analyze unloaded and loaded conditions separately. The residual correlation for the unloaded condition is 22% with raw EMG and 3.5% with rectified EMG and for the loaded condition it is 5.2% with raw EMG and 1.4% with rectified EMG. We interpret these results as strong supporting experimental evidence in favor of using the preprocessing step of surface EMG rectification before spectral analysis.

Distinguishing synchronous and time-varying synergies using point process interval statistics: motor primitives in frog and rat

We present and apply a method that uses point process statistics to discriminate the forms of synergies in motor pattern data, prior to explicit synergy extraction. The method uses electromyogram (EMG) pulse peak timing or onset timing. Peak timing is preferable in complex patterns where pulse onsets may be overlapping. An interval statistic derived from the point processes of EMG peak timings distinguishes time-varying synergies from synchronous synergies (SS). Model data shows that the statistic is robust for most conditions. Its application to both frog hindlimb EMG and rat locomotion hindlimb EMG show data from these preparations is clearly most consistent with synchronous synergy models (p < 0.001). Additional direct tests of pulse and interval relations in frog data further bolster the support for synchronous synergy mechanisms in these data. Our method and analyses support separated control of rhythm and pattern of motor primitives, with the low level execution primitives comprising pulsed SS in both frog and rat, and both episodic and rhythmic behaviors.

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.

Factors influencing the estimates of correlation between motor unit activities in humans

Background

Alpha motoneurons receive common synaptic inputs from spinal and supraspinal pathways. As a result, a certain degree of correlation can be observed between motoneuron spike trains during voluntary contractions. This has been studied by using correlation measures in the time and frequency domains. These measures are interpreted as reflecting different types of connectivity in the spinal networks, although the relation between the degree of correlation of the output motoneuron spike trains and of their synaptic inputs is unclear.

Methodology/Principal Findings

In this study, we analyze theoretically this relation and we complete this analysis by simulations and experimental data on the abductor digiti minimi muscle. The results demonstrate that correlation measures between motoneuron output spike trains are inherently influenced by the discharge rate and that this influence cannot be compensated by normalization. Because of the influence of discharge rate, frequency domain measures of correlation (coherence) do not identify the full frequency content of the common input signal when computed from pairs of motoneurons. Rather, an increase in sampling rate is needed by using cumulative spike trains of several motoneurons. Moreover, the application of averaging filters to the spike trains influences the magnitude of the estimated correlation levels calculated in the time, but not in the frequency domain (coherence).

Conclusions

It is concluded that the analysis of coherence in different frequency bands between cumulative spike trains of a sufficient number of motoneurons provides information on the spectrum of the common synaptic input. Nonetheless, the absolute values of coherent peaks cannot be compared across conditions with different cumulative discharge rates.

A novel, jitter-based method for detecting and measuring spike synchrony and quantifying temporal firing precision

BACKGROUND

Precise spike synchrony, at the millisecond or even sub-millisecond time scale, has been reported in different brain areas, but its neurobiological meaning and its underlying mechanisms remain unknown or controversial. Studying these questions is complicated by the lack of a validated, well-normalized and robust index for quantifying synchrony. Previously used measures of synchrony are often improperly normalized and thereby are not comparable between different experimental conditions, are sensitive to variations in firing rate or to the firing rate differential between the two neurons, and/or rely on untenable assumptions of firing rate stationarity and Poisson statistics. I describe here a novel measure, the Jitter-Based Synchrony Index (JBSI), that overcomes these issues.

RESULTS AND DISCUSSION

The JBSI method is based on the introduction of virtual spike jitter. While previous implementations of the jitter method used it only to detect synchrony, the JBSI method also quantifies synchrony. Previous implementations of the jitter method used computationally intensive Monte Carlo simulations to generate surrogate spike trains, whereas the JBSI is computed analytically. The JBSI method does not assume any specific firing model, and does not require that the spike trains be locked to a repeating external stimulus. The JBSI can assume values from 1 (maximal possible synchrony) to -1 (minimal possible synchrony) and is therefore properly normalized. Using simulated Poisson spike trains with introduced controlled spike coincidences, I demonstrate that the JBSI is a linear measure of the spike coincidence rate, is independent of the mean firing frequency or the firing frequency differential between the two neurons, and is not sensitive to co-modulations in the firing rates of the two neurons. In contrast, several commonly used synchrony indices fail under one or more of these scenarios. I also demonstrate how the JBSI can be used to estimate the spike timing precision in the system.

CONCLUSIONS

The JBSI is a conceptually simple and computationally efficient method that can be used to compute the statistical significance of firing synchrony, to quantify synchrony as a well-normalized index, and to estimate the degree of temporal precision in the system.

A simulation-based analysis of motor unit number index (MUNIX) technique using motoneuron pool and surface electromyogram models

Motor unit number index (MUNIX) measurement has recently achieved increasing attention as a tool to evaluate the progression of motoneuron diseases. In our current study, the sensitivity of the MUNIX technique to changes in motoneuron and muscle properties was explored by a simulation approach utilizing variations on published motoneuron pool and surface electromyogram (EMG) models. Our simulation results indicate that, when keeping motoneuron pool and muscle parameters unchanged and varying the input motor unit numbers to the model, then MUNIX estimates can appropriately characterize changes in motor unit numbers. Such MUNIX estimates are not sensitive to different motor unit recruitment and rate coding strategies used in the model. Furthermore, alterations in motor unit control properties do not have a significant effect on the MUNIX estimates. Neither adjustment of the motor unit recruitment range nor reduction of the motor unit firing rates jeopardizes the MUNIX estimates. The MUNIX estimates closely correlate with the maximum M-wave amplitude. However, if we reduce the amplitude of each motor unit action potential rather than simply reduce motor unit number, then MUNIX estimates substantially underestimate the motor unit numbers in the muscle. These findings suggest that the current MUNIX definition is most suitable for motoneuron diseases that demonstrate secondary evidence of muscle fiber reinnervation. In this regard, when MUNIX is applied, it is of much importance to examine a parallel measurement of motor unit size index (MUSIX), defined as the ratio of the maximum M-wave amplitude to the MUNIX. However, there are potential limitations in the application of the MUNIX methods in atrophied muscle, where it is unclear whether the atrophy is accompanied by loss of motor units or loss of muscle fiber size.

Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness

Motoneurons receive synaptic inputs from tens of thousands of connections that cause membrane potential to fluctuate continuously (synaptic noise), which introduces variability in discharge times of action potentials. We hypothesized that the influence of synaptic noise on force steadiness during voluntary contractions is limited to low muscle forces. The hypothesis was examined with an analytical description of transduction of motor unit spike trains into muscle force, a computational model of motor unit recruitment and rate coding, and experimental analysis of interspike interval variability during steady contractions with the abductor digiti minimi muscle. Simulations varied contraction force, level of synaptic noise, size of motor unit population, recruitment range, twitch contraction times, and level of motor unit short-term synchronization. Consistent with the analytical derivations, simulations and experimental data showed that force variability at target forces above a threshold was primarily due to low-frequency oscillations in neural drive, whereas the influence of synaptic noise was almost completely attenuated by two low-pass filters, one related to convolution of motoneuron spike trains with motor unit twitches (temporal summation) and the other attributable to summation of single motor unit forces (spatial summation). The threshold force above which synaptic noise ceased to influence force steadiness depended on recruitment range, size of motor unit population, and muscle contractile properties. This threshold was low (<10% of maximal force) for typical values of these parameters. Results indicate that motor unit recruitment and muscle properties of a typical muscle are tuned to limit the influence of synaptic noise on force steadiness to low forces and that the inability to produce a constant force during stronger contractions is mainly attributable to the common low-frequency oscillations in motoneuron discharge rates.

Adaptations in biceps brachii motor unit activity after repeated bouts of eccentric exercise in elbow flexor muscles

The purpose of this study was to examine changes in motor unit activity in the biceps brachii muscle after an initial ( Bout 1) and repeated ( Bout 2) session of eccentric exercise separated by 1 wk. Eight subjects (aged 22 ± 2 yr) participated in experimental assessments of neuromuscular function obtained before, immediately after, 24 h after, and 7 days after each exercise bout. Each experimental session involved assessments of elbow-flexor force and biceps and triceps brachii electromyography during maximum voluntary isometric contractions (MVCs) and constant-force isometric contractions at five contraction intensities (5–50% MVC), along with indicators of muscle damage (muscle pain and passive tension). In addition, motor unit recordings were obtained before exercise, 7 days after Bout 1, and 24 h after Bout 2 to assess motor unit synchronization and recruitment thresholds. Following a single eccentric exercise session that elicited significant indicators of muscle damage, we found a 57% increase in motor unit synchronization 7 days later compared with before exercise, despite the recovery of maximal strength, soreness, and relaxed elbow-joint angle at this time. Furthermore, a second bout of the same eccentric exercise resulted in reduced indicators of muscle damage and a decline in the strength of motor unit synchronization (24 h after Bout 2) toward levels observed before both exercise sessions. In contrast, no changes in motor unit recruitment thresholds were observed 7 days after Bout 1 or 24 h after Bout 2 compared with before exercise. The increased motor unit synchronization 7 days after a single eccentric exercise session provides new evidence of changes in motor unit activity during the putative repair and regeneration phase following eccentric muscle damage.

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.