scholarly journals Common Input to Motor Neurons Innervating the Same and Different Compartments of the Human Extensor Digitorum Muscle

2004 ◽  
Vol 91 (1) ◽  
pp. 57-62 ◽  
Author(s):  
Douglas A. Keen ◽  
Andrew J. Fuglevand
Keyword(s):  
Motor Unit ◽  
Motor Neurons ◽  
Cross Correlation ◽  
Motor Units ◽  
Extensor Digitorum ◽  
Short Term ◽  
Common Input ◽  
Active Motor ◽  
Voluntary Contractions ◽  
Input Strength

Short-term synchronization of active motor units has been attributed in part to last-order divergent projections that provide common synaptic input across motor neurons. The extent of synchrony thus allows insight as to how the inputs to motor neurons are distributed. Our particular interest relates to the organization of extrinsic finger muscles that give rise distally to multiple tendons, which insert onto all the fingers. For example, extensor digitorum (ED) is a multi-compartment muscle that extends digits 2–5. Given the unique architecture of ED, it is unclear if synaptic inputs are broadly distributed across the entire pool of motor neurons innervating ED or segregated to supply subsets of motor neurons innervating different compartments. Therefore the purpose of this study was to evaluate the degree of motor-unit synchrony both within and across compartments of ED. One hundred and forty-five different motor-unit pairs were recorded in the human ED of nine subjects during weak voluntary contractions. Cross-correlation histograms were generated for all of the motor-unit pairs and the degree of synchronization between two units was assessed using the index of common input strength (CIS). The degree of synchrony for motor-unit pairs within the same compartment (CIS = 0.7 ± 0.3; mean ± SD) was significantly greater than for motor-unit pairs in different compartments (CIS = 0.4 ± 0.22). Consequently, last-order synaptic projections are not distributed uniformly across the entire pool of motor neurons innervating ED but are segregated to supply subsets of motor neurons innervating different compartments.

Discharge Properties of Motor Units of the Abductor Hallucis Muscle During Cramp Contractions

2009 ◽  
Vol 102 (3) ◽  
pp. 1890-1901 ◽  
Author(s):  
Marco A. Minetto ◽  
Aleš Holobar ◽  
Alberto Botter ◽  
Dario Farina
Keyword(s):  
Motor Unit ◽  
Discharge Rate ◽  
Motor Units ◽  
Abductor Hallucis ◽  
Significant Peak ◽  
Discharge Rates ◽  
Abductor Hallucis Muscle ◽  
Active Motor ◽  
Number Of Discharges ◽  
Voluntary Contractions

We analyzed individual motor units during electrically elicited cramp contractions with the aim of characterizing the variability and degree of common oscillations in their discharges. Intramuscular and surface electromyographic (EMG) signals were detected from the abductor hallucis muscle of 11 healthy subjects (age 27.0 ± 3.7 yr) during electrically elicited cramps. In all, 48 motor units were identified from the intramuscular EMG. These motor units were active for 23.6 ± 16.2 s, during which their average discharge rate was 14.5 ± 5.1 pulses/s (pps) and their minimum and maximum rates were, respectively, 6.0 ± 0.8 and 25.0 ± 8.0 pps ( P < 0.001). The coefficient of variation for the interspike interval (ISI) was 44.6 ± 9.7% and doublet discharges constituted 4.1 ± 4.7% of the total number of discharges. In 38 motor units, the SD of the ISI was positively correlated to the mean ISI ( R2 = 0.37, P < 0.05). The coherence spectrum between smoothed discharge rates of pairs of motor units showed one significant peak at 1.4 ± 0.4 Hz for 29 of the 96 motor unit pairs and two significant peaks at 1.3 ± 0.5 and 1.5 ± 0.5 Hz for 8 motor unit pairs. The cross-correlation function between pairs of discharge rates showed a significant peak (0.52 ± 0.11) in 26 motor unit pairs. In conclusion, motor units active during cramps showed a range of discharge rates similar to that observed during voluntary contractions but larger ISI variability, probably due to large synaptic noise. Moreover, the discharge rates of the active motor units showed common oscillations.

Motor-Unit Synchrony Within and Across Compartments of the Human Flexor Digitorum Superficialis

2007 ◽  
Vol 97 (1) ◽  
pp. 550-556 ◽  
Author(s):  
Tara L. McIsaac ◽  
Andrew J. Fuglevand
Keyword(s):  
Motor Unit ◽  
Motor Neurons ◽  
Motor Units ◽  
Flexor Digitorum Profundus ◽  
Human Hand ◽  
Flexor Digitorum Superficialis ◽  
Short Term ◽  
Synaptic Inputs ◽  
Muscles Of The Hand ◽  
Flexor Digitorum

An interesting feature of the muscular organization of the human hand is that the main flexors and extensors of the fingers are compartmentalized and give rise to multiple parallel tendons that insert onto all the fingers. Previous studies of motor-unit synchrony in extensor digitorum and flexor digitorum profundus indicated that synaptic input to motor neurons supplying these multitendoned muscles is not uniformly distributed across the entire pool of motor neurons but instead appears to be partially segregated to supply subsets of motor neurons that innervate different muscular compartments. Little is known, however, about the organization of the synaptic inputs to the motor neurons supplying another multitendoned finger muscle, the flexor digitorum superficialis (FDS). Therefore in this study, we estimated the extent of divergence of last-order inputs to FDS motor neurons by measuring the degree of short-term synchrony among motor units within and across compartments of FDS. The degree of synchrony for motor-unit pairs within the same digit compartment was nearly twofold that of pairs of motor units in adjacent compartments and more than fourfold that of pairs in nonadjacent compartments. Therefore like other multitendoned muscles of the hand, last-order synaptic inputs to motor neurons supplying the FDS appear to primarily supply subsets of motor neurons innervating specific finger compartments. Such an organization presumably enables differential activation of separate compartments to facilitate independent movements of the fingers.

scholarly journals Recruitment of motor units in two fascicles of the semispinalis cervicis muscle

2012 ◽  
Vol 107 (11) ◽  
pp. 3078-3085 ◽  
Author(s):  
Jochen Schomacher ◽  
Jakob Lund Dideriksen ◽  
Dario Farina ◽  
Deborah Falla
Keyword(s):  
Motor Unit ◽  
Discharge Rate ◽  
Maximum Voluntary Contraction ◽  
Motor Units ◽  
Voluntary Contraction ◽  
Common Input ◽  
Motor Unit Synchronization ◽  
Motor Unit Action ◽  
Input Strength ◽  
Individual Motor

This study investigated the behavior of motor units in the semispinalis cervicis muscle. Intramuscular EMG recordings were obtained unilaterally at levels C2 and C5 in 15 healthy volunteers (8 men, 7 women) who performed isometric neck extensions at 5%, 10%, and 20% of the maximal force [maximum voluntary contraction (MVC)] for 2 min each and linearly increasing force contractions from 0 to 30% MVC over 3 s. Individual motor unit action potentials were identified. The discharge rate and interspike interval variability of the motor units in the two locations did not differ. However, the recruitment threshold of motor units detected at C2 ( n = 16, mean ± SD: 10.3 ± 6.0% MVC) was greater than that of motor units detected at C5 ( n = 92, 6.9 ± 4.3% MVC) ( P < 0.01). A significant level of short-term synchronization was identified in 246 of 307 motor unit pairs when computed within one spinal level but only in 28 of 110 pairs of motor units between the two levels. The common input strength, which quantifies motor unit synchronization, was greater for pairs within one level (0.47 ± 0.32) compared with pairs between levels (0.09 ± 0.07) ( P < 0.05). In a second experiment on eight healthy subjects, interference EMG was recorded from the same locations during a linearly increasing force contraction from 0 to 40% MVC and showed significantly greater EMG amplitude at C5 than at C2. In conclusion, synaptic input is distributed partly independently and nonuniformly to different fascicles of the semispinalis cervicis muscle.

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

2019 ◽  
Author(s):  
Andrew J Tweedell ◽  
Matthew S Tenan
Keyword(s):  
Open Source ◽  
Motor Unit ◽  
Motor Neurons ◽  
Time Domain ◽  
Cross Correlation ◽  
Visual Analysis ◽  
Detection Methods ◽  
Common Input ◽  
Cross Correlation Analysis ◽  
Motor Unit Synchronization

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 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. To combat this, we have developed a freely available, open-source toolbox, “motoRneuron”, for the R programming language. This toolbox contains functions for calculating time domain synchronization using different methods found in the literature. Our objective is to detail the program’s functionality and provide a clear use-case for implementation. The programs primary function “mu_synch” automatically performs the cross-correlation analysis based on user input. Automated peak detection methods such as the cumulative sum method and the z-score method, as well as subjective, visual analysis are available. Users can also define other parameters like the number of recurrence intervals to be used and histogram bin size. The function outputs six common synchronization indices, the common input strength (CIS), k’, k’-1, E, S, and Synch Index. This toolbox allows for better standardization of techniques and for more comprehensive data mining in the motor control community.

Discharge Rate of Sternohyoid Motor Units Activated With Surface EMG Feedback

2009 ◽  
Vol 101 (2) ◽  
pp. 624-632 ◽  
Author(s):  
Dario Farina ◽  
Deborah Falla
Keyword(s):  
Motor Unit ◽  
Motor Neurons ◽  
Discharge Rate ◽  
Maximum Level ◽  
Motor Units ◽  
Surface Emg ◽  
Discharge Rates ◽  
Average Maximum ◽  
Motor Unit Discharge ◽  
Voluntary Contractions

We analyzed individual motor units of the sternohyoid muscle with the aim of characterizing their minimum and maximum discharge rates and their variability in discharge during voluntary contractions. Surface EMG signals were recorded with an array of eight electrodes from the sternohyoid muscle of seven healthy men (age: 30.2 ± 3.5 yr). The multichannel surface EMG signals were displayed as feedback for the subjects who identified and modulated the activity of one target motor unit in 30-s contractions during which the discharge rate was increased from minimum to maximum (ramp contraction), sustained at maximum level (sustained), or increased in brief bursts (burst). During the ramp contractions, the minimum average discharge rate over epochs of 1 s was 11.6 ± 1.5 pulses per second (pps) and the maximum 57.0 ± 5.7 pps ( P < 0.001). During the sustained contractions, the motor unit discharge rate decreased from 65.5 ± 8.4 pps at the beginning to 52.9 ± 7.6 pps at the end of the contraction ( P < 0.05). The coefficient of variation for the interspike interval during the sustained contractions was 40.2 ± 9.8% and a large percentage of discharges had instantaneous rates >50 pps (52.2 ± 12.5%) and >100 pps (8.0 ± 1.2%), with peak values >150 pps. During the burst contractions, the instantaneous discharge rate reached average maximum values of 97.6 ± 36.8 pps. The observed discharge rates and their variability are higher than those reported for limb muscles, which may be due to large synaptic input and noise received by these motor neurons.

Synchronization of motor-unit firings in several human muscles

1993 ◽  
Vol 70 (5) ◽  
pp. 2010-2023 ◽  
Author(s):  
C. J. De Luca ◽  
A. M. Roy ◽  
Z. Erim
Keyword(s):  
Motor Unit ◽  
Motor Units ◽  
Motor Unit Action Potential ◽  
Short Term ◽  
Active Motor ◽  
Motor Unit Action ◽  
Human Muscles ◽  
Unit Action ◽  
Interval Histogram

1. Synchronization of concurrently active motor-unit firings was studied in six human muscles performing isometric constant-force contractions at 30% of the maximal level. The myoelectric signal was detected with a quadrifilar needle electrode and was decomposed into its constituent motor-unit action-potential trains with the Precision Decomposition technique, whose accuracy has been proven previously. 2. Synchronization was considered as the tendency of two motor units to fire at fixed time intervals with respect to each other more often than would be expected if the motor units fired independently. A rigorous statistical technique was used to measure the presence of peaks in the cross-interval histogram of pairs of motor-unit action-potential trains. The location of the center of peak as well as their width and amplitude were measured. A synch index was developed to measure the percentage of firings that were synchronized. The percentage of concurrently active motor-unit pairs that contained synchronized firings was measured. 3. Synchronization of motor-unit firings was observed to occur in two modalities. The short-term modality was seen as a peak in the cross-interval histogram centered about zero-time delay (0.5 +/- 2.9 ms, mean +/- SD) and with an average width of 4.5 +/- 2.5 ms. The long-term modality was seen as a peak centered at latencies ranging from 8 to 76 ms. On the average, the peaks of the long-term synchronization were 36% lower but had approximately the same width as the peaks for the short-term synchronization. Short-term synchronization was seen in 60% of the motor-unit paris, whereas long-term synchronization was seen in 10% of the pairs. 4. Short-term synchronization occurred in bursts of consecutive firings, ranging in number from 1 to 10, with 91% of all synchronized firing occurring in groups of 1 or 2; and the bursts of discharges appeared at sporadic times during the contraction. 5. The amount of synchronization in motor-unit pairs was found to be low. In the six muscles that were tested, an average of 8.0% of all the firings were short-term synchronized, and an average of 1.0% were long-term synchronized. The synch index was statistically indistinguishable (P = 0.07-0.89) among the different muscles and among 9 of the 11 subjects tested. 6. Sixty percent of concurrently active motor-unit pairs displayed short-term synchronization, 10% of the pairs displayed long-term synchronization, and 8% displayed both modalities.(ABSTRACT TRUNCATED AT 400 WORDS)

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

2019 ◽  
Author(s):  
Andrew J Tweedell ◽  
Matthew S Tenan
Keyword(s):  
Open Source ◽  
Motor Unit ◽  
Motor Neurons ◽  
Time Domain ◽  
Cross Correlation ◽  
Visual Analysis ◽  
Detection Methods ◽  
Common Input ◽  
Cross Correlation Analysis ◽  
Motor Unit Synchronization

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 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. To combat this, we have developed a freely available, open-source toolbox, “motoRneuron”, for the R programming language. This toolbox contains functions for calculating time domain synchronization using different methods found in the literature. Our objective is to detail the program’s functionality and provide a clear use-case for implementation. The programs primary function “mu_synch” automatically performs the cross-correlation analysis based on user input. Automated peak detection methods such as the cumulative sum method and the z-score method, as well as subjective, visual analysis are available. Users can also define other parameters like the number of recurrence intervals to be used and histogram bin size. The function outputs six common synchronization indices, the common input strength (CIS), k’, k’-1, E, S, and Synch Index. This toolbox allows for better standardization of techniques and for more comprehensive data mining in the motor control community.

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

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7907
Author(s):  
Andrew J. Tweedell ◽  
Matthew S. Tenan
Keyword(s):  
Open Source ◽  
Motor Unit ◽  
Motor Neurons ◽  
Time Domain ◽  
Cross Correlation ◽  
Motor Units ◽  
Motor Unit Action Potential ◽  
Cross Correlation Analysis ◽  
Motor Unit Synchronization ◽  
The Cross

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.

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

2012 ◽  
Vol 108 (12) ◽  
pp. 3264-3275 ◽  
Author(s):  
Douglas A. Keen ◽  
Li-Wei Chou ◽  
Michael A. Nordstrom ◽  
Andrew J. Fuglevand
Keyword(s):  
Motor Unit ◽  
Motor Neurons ◽  
Tibialis Anterior Muscle ◽  
Motor Units ◽  
Short Term ◽  
Abductor Hallucis ◽  
Cortical Input ◽  
Abductor Hallucis Muscle ◽  
Human Muscles ◽  
Cortical Inputs

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.

Reduction of Common Synaptic Drive to Ankle Dorsiflexor Motoneurons During Walking in Patients With Spinal Cord Lesion

2005 ◽  
Vol 94 (2) ◽  
pp. 934-942 ◽  
Author(s):  
N. L. Hansen ◽  
B. A. Conway ◽  
D. M. Halliday ◽  
S. Hansen ◽  
H. S. Pyndt ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Motor Unit ◽  
Healthy Subjects ◽  
Motor Units ◽  
Central Peak ◽  
Spinal Cord Lesion ◽  
Short Term ◽  
Physiological Markers ◽  
Synaptic Drive ◽  
Cord Lesion

It is possible to obtain information about the synaptic drive to motoneurons during walking by analyzing motor-unit coupling in the time and frequency domains. The purpose of the present study was to compare motor-unit coupling during walking in healthy subjects and patients with incomplete spinal cord lesion to obtain evidence of differences in the motoneuronal drive that result from the lesion. Such information is of importance for development of new strategies for gait restoration. Twenty patients with incomplete spinal cord lesion (SCL) participated in the study. Control experiments were performed in 11 healthy subjects. In all healthy subjects, short-term synchronization was evident in the discharge of tibialis anterior (TA) motor units during the swing phase of treadmill walking. This was identified from the presence of a narrow central peak in cumulant densities constructed from paired EMG recordings and from the presence of significant coherence between these signals in the 10- to 20-Hz band. Such indicators of short-term synchrony were either absent or very small in the patient group. The relationship between the amount of short-term synchrony and the magnitude of the 10- to 20-Hz coherence in the patients is discussed in relation to gait ability. It is suggested that supraspinal drive to the spinal cord is responsible for short-term synchrony and coherence in the 10- to 20-Hz frequency band during walking in healthy subjects. Absence or reduction of these features may serve as physiological markers of impaired supraspinal control of gait in SCL patients. Such markers could have diagnostic and prognostic value in relation to the recovery of locomotion in patients with central motor lesions.

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