scholarly journals A Simulation-Based Analysis of Motor Unit Number Index (MUNIX) Technique Using Motoneuron Pool and Surface Electromyogram Models

2012 ◽  
Vol 20 (3) ◽  
pp. 297-304 ◽  
Author(s):  
Xiaoyan Li ◽  
W. Z. Rymer ◽  
Ping Zhou
Keyword(s):  
Motor Unit ◽  
Surface Electromyogram ◽  
Motoneuron Pool ◽  
Simulation Based

Computer simulation of the steady-state input-output function of the cat medial gastrocnemius motoneuron pool

1991 ◽  
Vol 65 (4) ◽  
pp. 952-967 ◽  
Author(s):  
C. J. Heckman ◽  
M. D. Binder
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Motor Unit ◽  
Frequency Modulation ◽  
Motor Units ◽  
Medial Gastrocnemius ◽  
Output Function ◽  
Input Output ◽  
Motoneuron Pool ◽  
Random Variance

1. A pool of 100 simulated motor units was constructed in which the steady-state neural and mechanical properties of the units were very closely matched to the available experimental data for the cat medial gastrocnemius motoneuron pool and muscle. The resulting neural network generated quantitative predictions of whole system input-output functions based on the single unit data. The results of the simulations were compared with experimental data on normal motor system behavior in humans and animals. 2. We considered only steady-state, isometric conditions. All motoneurons received equal proportions of the synaptic input, and no feedback loops were operative. Thus the intrinsic properties of the motor unit population alone determined the form of the system input-output function. Expressing the synaptic input in terms of effective synaptic current allowed the simulated motoneuron input-output functions to be specified by well-known firing rate-injected current relations. The motor unit forces were determined from standard motor unit force-frequency relations, and the system output at any input level was assumed to be the linear sum of the forces of the active motor units. 3. The steady-state input-output function of the simulated motoneuron pool had a roughly sigmoidal shape that was quite different from those derived from previous recruitment models, which did not incorporate frequency modulation. Frequency modulation in combination with the skewed distribution of thresholds (low values much more frequent than high) restricted upward curvature to low input levels, whereas frequency modulation alone was responsible for the final gradual approach to the maximum force output. 4. Sensitivity analyses were performed to assess the importance of several assumptions that were required to deal with gaps and uncertainties in the available experimental data. The shape of the input-output function was not critically dependent on any of these assumptions, including those specifying linear summation of inputs and outputs. 5. A key assumption of the model was that systematic variance in motor unit properties was much more important than random variance for determining the input-output function. Addition of random variance via Monte Carlo techniques showed that this assumption was correct. These results suggest that the output of a motoneuron pool should be quite tolerant of random variance in the distribution of synaptic inputs and yet substantially altered by any systematic differences, such as unequal distribution of inputs among different motor unit types.(ABSTRACT TRUNCATED AT 400 WORDS)

Firing patterns of human flexor carpi radialis motor units during the stretch reflex

1985 ◽  
Vol 53 (5) ◽  
pp. 1179-1193 ◽  
Author(s):  
B. Calancie ◽  
P. Bawa
Keyword(s):  
Motor Unit ◽  
Stretch Reflex ◽  
Latency Period ◽  
Response Probability ◽  
Short Latency ◽  
Single Motor Unit ◽  
Single Motor ◽  
Motoneuron Pool ◽  
Long Latency ◽  
Long Latency Reflex

Single motor unit and gross surface electromyographic responses to torque motor-produced wrist extensions were studied in human flexor carpi radialis muscle. Surface EMG typically showed two "periods" of reflex activity, at a short and long latency following stretch, but both periods occurring before a subject's voluntary reaction to the stretch. The amplitude of EMG activity in both reflex periods increased monotonically with an increase in the torque load. The amplitude of the short-latency reflex response was very dependent on the motoneuron pool excitability, or preload. The amplitude of the long-latency reflex response also varied with the preload, but could, in addition, be modulated by the subject's preparatory set for a voluntary response to the imposed displacement. When a single motor unit that was not tonically active began to fire during the stretch reflex, it did so primarily during the long-latency period. When caused to fire repetitively by voluntary facilitation of the motoneuron pool, that same unit now showed activity during both periods of the stretch reflex. Further increases in either motoneuron pool facilitation or in perturbation strength resulted in a monotonic increase in response probability of a single motor unit during the short-latency period. However, the response probability of a single unit during the long-latency reflex period did not always vary in a monotonic way with increases in either torque load or motoneuron pool facilitation. For an additional series of experiments, the subject was instructed on how to respond voluntarily to the upcoming wrist perturbation. The three instructions to the subject had no effect on the response probability of a single motor unit during either the background or short-latency periods of the stretch reflex. However, prior instruction clearly affected a unit's response probability during the long-latency reflex period. Changes in the firing rate of motor units, and in the recruitment or derecruitment of nontonic units, contributed to this modulation of reflex activity during the long-latency period.

Motor unit recruitment and bursts of activity in the surface electromyogram during a sustained contraction

2008 ◽  
Vol 37 (6) ◽  
pp. 745-753 ◽  
Author(s):  
Zachary A. Riley ◽  
Mary E. Terry ◽  
Alberto Mendez-Villanueva ◽  
Jane C. Litsey ◽  
Roger M. Enoka
Keyword(s):  
Motor Unit ◽  
Motor Unit Recruitment ◽  
Surface Electromyogram ◽  
Sustained Contraction

Motor Unit Synchronization as a Measure of Localized Muscle Fatigue

2013 ◽  
Vol 2 (1) ◽  
pp. 39-49
Author(s):  
Sridhar P. Arjunan ◽  
Dinesh K. Kumar
Keyword(s):  
Independent Component Analysis ◽  
Muscle Fatigue ◽  
Motor Unit ◽  
Independent Component ◽  
Surface Electromyogram ◽  
Localized Muscle Fatigue ◽  
Motor Unit Synchronization ◽  
Spectral Compression ◽  
High Degree ◽  
Post Onset

There is spectral compression of the surface Electromyogram (sEMG) towards lower frequencies and corresponding increase in amplitude of sEMG associated with muscle fatigue. While it is possible to use these features to compare pre and post onset of muscle fatigue, it is not possible to use these features alone to identify fatigued muscles due to the large inter-subject and inter-experimental variations. This is further compounded when the contraction is not isometric but cyclic because there is large variation of sEMG within each cycle. This research has developed and demonstrated a technique that measures motor unit synchronization within a muscle which can be used to determine if the associated muscle is fatigued or non-fatigued. This technique measures the level of independence between two channel sEMG recorded from the muscles measured by determinant of the Global matrix generated by performing independent component analysis. When the muscle is non-fatigued, the two channels have a high degree of independence with a high value of the determinant (0.35 to 0.98), while the channels become dependent when the muscles get fatigued and the determinant is close to zero (0.0007 to 0.0018). This is irrespective of the contraction being isometric or cyclic, and is valid for all subjects.

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

2011 ◽  
Vol 105 (5) ◽  
pp. 2330-2336 ◽  
Author(s):  
Amber Rice ◽  
Andrew J. Fuglevand ◽  
Christopher M. Laine ◽  
Ralph F. Fregosi
Keyword(s):  
Motor Neuron ◽  
Motor Unit ◽  
Motor Units ◽  
Excitatory Input ◽  
Respiratory Drive ◽  
Tongue Muscle ◽  
Motoneuron Pool ◽  
Hypoglossal Motoneuron ◽  
Tongue Muscles ◽  
Premotor Neurons

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

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