Journal of Nature and Science (JNSCI), Vol.3, No.8, e426, 2017

Neuroscience

 

Time Course of Changes in Neuromuscular Parameters from the Quadriceps During Maximal Isokinetic Muscle Actions

 

Cory M. Smith*, Terry J. Housh, Ethan C. Hill, Joshua L. Keller, Glen O. Johnson, and Richard J. Schmidt

 

Department of Nutrition and Health Sciences, University of Nebraska-Lincoln, Lincoln, NE, USA


Purpose: The purposes of the present study were to identify the time course of changes in neuromuscular responses and to infer about the motor unit control strategies used to maintain force from the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) during a fatiguing maximal concentric isokinetic leg extension workbout.

 

Methods: Thirteen men performed 25 maximal concentric isokinetic leg extension muscle actions at 120s-1. Electromyography, (EMG), mechanomyography (MMG), and force were simultaneously collected from the VL, VM, and RF during each of the 25 repetitions. A combined regression and mean comparisons analysis was used to examine the time course of changes in maximal isokinetic peak force as well as EMG amplitude (RMS), EMG mean power frequency (MPF), MMG RMS, and MMG MPF from the VL, VM, and RF.

 

Results: Maximal isokinetic peak force decreased 21% and was accompanied by changes in neuromuscular responses from all muscles. The VL exhibited increases in EMG RMS and MMG RMS, decreases in EMG MPF, but no changes in MMG MPF. The VM only exhibited increases in EMG RMS. The RF, however, exhibited increases in EMG RMS, but decreases in EMG MPF.

 

Discussion: The time course of changes in neuromuscular responses allowed for the identification of the potential motor unit control strategies used to maintain and optimize force production. The motor unit control strategy utilized to maintain and optimize force production could not be explained by the After-Hyperpolarization or Muscle Wisdom theory, but could be explained by the Onion Skin Scheme.

 

Motor Unit Activation Strategies | Motor Unit Control Strategy | Newman-Keuls | Dynamic Fatigue

 

1. Introduction

Surface electromyography (EMG) and mechanomyography (MMG) have been used to examine neuromuscular responses and make inferences regarding motor unit control strategies during fatiguing workbouts (1-5). For example, it has been suggested that a fatigue-induced increase in the amplitude of the EMG signal reflects greater muscle activation (6), while a decrease in the frequency content reflects a slowing of motor unit action potential conduction velocity (MUAP CV) (6). The MMG signal, however, has been described as the mechanical counterpart of the motor unit electrical activity as measured by EMG and quantifies the low-frequency oscillations of activated skeletal muscle fibers (7). Furthermore, it has been suggested that under some conditions, the amplitude of the MMG signal reflects motor unit recruitment (7) and the frequency content is qualitatively related to the global motor unit firing rate of unfused, activated motor units (7). Therefore, it has been suggested that a fatigue-induced increase in MMG amplitude indicates greater motor unit recruitment, while a decrease in MMG frequency is associated with a decrease in firing rate (8). Thus, simultaneous assessments of the time and frequency domain parameters of EMG and MMG signals can provide information regarding the characteristics of the motor unit control strategies, such as the After-Hyperpolarization (AHP) theory (9), Muscle Wisdom theory (10), and the Onion Skin Scheme (1, 11, 12), that control force production during fatiguing workbouts.

The AHP theory was based on stimulation studies by Eccles, Eccles (9) and Kernell (13), (14) and is primarily characterized by fatigue-induced increases motor unit firing rates and then increases in muscle activation and motor unit recruitment. According to the AHP theory, a fatigue-induced buildup of metabolic byproducts causes a gradient shift from intracellular to extracellular potassium [K+] which decreases the membrane potential below resting levels following depolarization which has been termed after-hyperpolarization (9, 13, 14). The metabolite shift which results in greater after-hyperpolzariation then signals the central nervous system to increase motor unit recruitment and motor unit firing rates to maintain the required force production (15). Therefore based on the AHP theory, the process of fatigue should be characterized by increases in EMG amplitude, MMG amplitude, and MMG frequency due to the increases in motor unit recruitment and motor unit firing rate.

The Muscle Wisdom theory was based on a stimulation study by Marsden, Meadows (10) and is characterized by fatigue-induced increases in muscle activation and motor unit recruitment, but decreases in firing rate. Specifically, during a fatiguing task the Muscle Wisdom theory (10) describes a progressive prolongation of relaxation time and a decrease in motor unit firing rate which, theoretically, allow for greater fusion of motor unit twitches and optimal force production. These findings were supported by Marsden, Meadows (10) and Bigland-Ritchie, Johansson (16) who demonstrated that stimulated motor units maintained the greatest force production during a sustained contraction when the frequency of the stimulation was progressively decreased. Therefore, according to the Muscle Wisdom theory, during a fatiguing task there would be increases in EMG amplitude, MMG amplitude due to increases in motor unit recruitment, but decreases in MMG frequency as a result of decreased motor unit firing rates.

The Onion Skin Scheme was based on a model created by De Luca and Erim (11) and is characterized by fatigue-induced increases in muscle activation and motor unit recruitment, but decreased or sustained motor unit firing rates (12, 17). The Onion Skin Scheme suggests that at any time or force level, earlier recruited motor units have higher firing rates than later recruited motor units. This theory results in an orderly nesting of firing rate curves, which resembles the skin of an onion. Thus, higher threshold motor units require lower firing rates to produce their maximal force than do lower threshold motor units. It has been hypothesized (11) that the lower firing rates observed in high threshold motor units may be due to their greater fatigability compared to low threshold motor units. For example, Trevino, Herda (18) reported that individuals with greater type II myosin heavy chain of the vastus lateralis (VL) had lower firing rates of the higher threshold motor units compared to those with greater type I myosin heavy chain. Therefore, theoretically, the neuromuscular system activates high threshold motor units at lower firing rates to balance maximal force production with the duration that the force can be sustained. Thus, the Onion Skin Scheme would predict increases in EMG amplitude and MMG amplitude, but decreases or no change in MMG frequency during a fatiguing task.  

Enoka and Stuart (19) suggested that delineating the differences between motor unit control strategies may allow for identification of the mechanisms that result in task failure. In the current study, three motor unit control strategies (AHP theory, Muscle Wisdom theory, and Onion Skin Scheme) are being considered, however, each has limitations (1, 20, 21). For example, Fuglevand and Keen (20) suggested that the Muscle Wisdom theory may not be an overall activation strategy during fatigue and that decreases in the frequency of stimulations may not optimize the duration of a fatiguing muscle action. In addition, De Luca and Contessa (1) suggested that the AHP theory does not always explain the process of fatigue because there is often, but not always, a decrease in firing rate. The Onion Skin Scheme, however, may have limitations due to the loss of data when analyzing the signal and the proprietary nature of the decomposition algorithm (1, 12, 22). These studies used either stimulation (20) or simulation (1) models which have their own limitations and, therefore, no one theory can be disregarded based on stimulation or simulation studies alone.

Few studies (3-5) have examined the time course of changes in neuromuscular responses during a fatiguing task and identified which of the 3 primary motor unit control strategies may explain the maintenance of force production. The unique combination of regression and mean comparisons proposed by Smith, Housh (5) was the first method designed to identify the global time course of changes in neuromuscular response during a fatiguing task and to infer on the motor unit control strategies used to maintain force production. This methodology (5) allows for the ability to simultaneously identify the general patterns of change in neuromuscular responses, magnitude of these changes, and make inferences regarding the motor unit control strategies utilized during the fatiguing task. It has been suggested (23), however, that motor unit control strategies used during a fatiguing task may be intensity-, mode-, and muscle-specific. The combination of regression and mean comparisons has previously been applied to submaximal isometric and dynamic constant external resistance (DCER) fatiguing tasks (3-5), but no previous studies have used this combination of statistical procedures to examine fatiguing maximal muscle actions. Therefore, the purposes of the present study were to identify the time course of changes in neuromuscular responses and isokinetic peak forces as well as to infer about the motor unit control strategies used to maintain isokinetic peak force from the VL, vastus medialis (VM), and rectus femoris (RF) during a fatiguing maximal concentric isokinetic leg extension workbout.

 

2. Material & Methods

 

2.1 Subjects

Thirteen men (mean SD age 24 3.8 yr; body mass 79.8 9.7 kg; height 172.8 8.6 cm) volunteered to participate in this study. The subjects were recreationally trained (greater than 6-months of resistance training 3 times per week), and free from any musculoskeletal injuries or neuromuscular disorders. This study was approved by the Institutional Review Board, and all subjects signed a written informed consent and completed a health history questionnaire prior to participation.

 

2.2 Protocol

A warmup consisting of 5 to 7 concentric isokinetic leg extension muscle actions was performed at approximately 50 to 70% of their maximal effort. Following the warmup, each subject performed 25 maximal concentric isokinetic leg extension muscle actions at 120s-1. Electromyography, MMG, and force were simultaneously collected from the VL, VM, ad RF during each of the 25 repetitions.

 

2.3 Electromyographic, Mechanomyographic, and Force Signal Acquisition

Bipolar surface electrode arrangements (Ag/AgCl, AccuSensor, Lynn Medical, Wixom, MI, USA) were placed on the VL, VM, and RF of the dominant leg (based on kicking preference) with an interelectrode distance of 30 mm. The skin was dry shaven, abraded, and cleaned with isopropyl alcohol prior to placing the electrodes. For the VL, the bipolar electrode arrangements were placed 66% of the distance between the anterior superior iliac spine (ASIS) and the lateral border of the patella and orientated at a 20 angle to approximate the pennation angle of the muscle fibers (24, 25). For the VM, the bipolar electrode arrangements were placed 80% of the distance between the ASIS and the joint space in front of the anterior border of the medial collateral ligament and orientated at a 53 angle to approximate the pennation angle of the muscle fibers (25, 26). For the RF, the bipolar electrode arrangements were placed 50% the distance between the ASIS and the superior border of the patella (25). A reference electrode was placed over the ASIS. A reference electrode was placed over the ASIS. The EMG signals were zero-meaned and bandpass filtered (fourth-order Butterworth) at 10-500 Hz. The MMG signal was measured using triaxial accelerometers (EGAS-FT-10/V05, Measurement Specialties Inc., Hampton, VA) placed between the bipolar electrode arrangements on the VL, VM, and RF. The MMG signals were zero-meaned and bandpass filtered (fourth-order Butterworth) at 5-100 Hz. Force was measured using a low-profile pancake load cell (Honeywell Model 41, Morris Plains, NJ) attached to the lever arm and was filtered at 5 Hz. All signals were simultaneously collected through a BioPac MP150 (BioPac System Inc., Goleta, CA) at a sampling frequency of 10,000 Hz. The EMG root mean square (RMS), EMG mean power frequency (MPF), MMG RMS, and MMG MPF from the MVIC muscle actions were calculated from the middle 33% of each of the 25 repetitions. All signal processing and EMD measurements were performed using custom programs written with LabVIEW software (Version 15.0, National Instruments, Austin TX).

 

2.4 Statistical Analysis

The time course of changes in neuromuscular responses and isokinetic peak force involved combining polynomial regression analyses with ANOVA and post-hoc Student Newman-Keuls comparisons to identify the patterns of responses and time-points at which these values became different than the initial values (5).


 

Figure 1. Maximal isokinetic peak force during 25 maximal isokinetic leg extension muscle actions at 120s-1. There was a linear decrease (r2 = 0.88) in maximal isokinetic peak force that began to decrease from the initial repetitions from 9 to 25 of the total repetitions.

 

 


Polynomial regression analyses were used to determine the patterns (linear, quadratic, or cubic) for the mean, normalized (% of initial repetition) EMG RMS, EMG MPF, MMG RMS, and MMG MPF versus repetition relationships for the VL, VM, and RF as well as isokinetic peak force. Time course of changes in normalized EMG RMS, EMG MPF, MMG RMS, MMG MPF, and isokinetic peak force from the initial repetition were identified by separate 1 (neuromuscular parameters [EMG RMS, MMG RMS, EMG MPF, and MMG MPF] or isokinetic peak force) x 25 (repetitions: 1 to 25) repeated measures ANOVAs with post-hoc Student Newman-Keuls tests. The Student Newman-Keuls test was chosen for the post-hoc analyses because it is designed to analyze the time course of changes in repeated measure variables (5, 27). An alpha of p 0.05 was considered statistically significant for all statistical analyses (SPSS Version 22.0).

 

 

3. Results

 

3.1 Maximal Isokinetic Peak Force during the Fatiguing Protocol

Figure 1 shows the results of the polynomial regression analyses and 1-way repeated measures ANOVAs with post-hoc Student Newman-Keuls tests for the maximal isokinetic peak force measurements versus repetition relationship during the 25 maximal isokinetic leg extension muscle actions at 120ºs-1. There was a significant 1-way repeated measures ANOVA (p < 0.01,  = 0.48) and negative linear relationship for maximal isokinetic peak force (r2 = 0.88) versus repetition during the 25 maximal isokinetic leg extension muscle actions at 120ºs-1 which began to decrease from the initial repetition from 9 to 25 of the total repetitions (Figure 1).

 

3.2 Time Course of Changes from the Vastus Lateralis

Figure 2 shows the results of the polynomial regression analyses and 1-way repeated measures ANOVAs with post-hoc Student Newman-Keuls tests for the normalized EMG RMS, EMG MPF, MMG RMS, and MMG MPF versus repetition relationships from the VL during 25 maximal isokinetic leg extensions at 120ºs-1. There was a significant 1-way repeated measure ANOVA (p = 0.02,  = 0.42) and positive quadratic relationship for EMG RMS (R2 = 0.82) versus repetition from the VL that increased from the initial repetition from 9 to 25 of the total repetitions (Figure 2). There was a significant 1-way repeated measure ANOVA (p < 0.01,  = 0.37) and negative quadratic relationship for EMG MPF (R2 = 0.76) versus repetition from the VL that decreased from the initial repetition from 6 to 25 of the total repetitions (Figure 2). There was a significant 1-way repeated measure ANOVA (p < 0.01,  = 0.43) and positive cubic relationship for MMG RMS (R2 = 0.96) versus repetition from the VL that increased from the initial repetition from 15 to 25 of the total repetitions (Figure 2). There was no significant 1-way repeated measure ANOVA (p = 0.23,  = 0.11) or relationship for MMG MPF (r2 = 0.14) versus repetition during the 25 maximal isokinetic leg extension muscle actions at 120ºs-1.

 

3.3 Time Course of Changes from the Vastus Medialis

Figure 3 shows the results of the polynomial regression analyses and 1-way repeated measures ANOVAs with post-hoc Student Newman-Keuls tests for the normalized EMG RMS, EMG MPF, MMG RMS, and MMG MPF versus repetition relationships from the VM during 25 maximal isokinetic leg extensions at 120ºs-1. There was a significant 1-way repeated measure ANOVA (p < 0.01,  = 0.39) and positive linear relationship for EMG RMS (r2 = 0.67) versus repetition from the VM that began to increase from the initial repetition from 4 to 25 of the total repetitions (Figure 3). There were no significant 1-way repeated measure ANOVA or polynomial regression relationship for EMG MPF (p = 0.18,  = 0.12; r2 = 0.13), MMG MPF  (p = 0.56,  = 0.09; r2 = 0.09), or MMG RMS (p = 0.11,  = 0.21; r2 = 0.21)  during the 25 maximal isokinetic leg extension muscle actions at 120ºs-1.

 

 


Figure 2. Indicates the results from the vastus lateralis for the combined regression and mean comparisons analysis of the time course of changes in the electromyographic (EMG) amplitude (RMS), EMG mean power frequency (MPF), mechanomyographic RMS, and MMG MPF normalized to the value of the initial repetition during 25 maximal isokinetic leg extension muscle actions at 120s-1. For the vastus lateralis, EMG RMS had a positive quadratic relationship (R2 = 0.82) that began to increase from the initial repetition from 9 to 25 of the total repetitions. The EMG MPF had a negative quadratic relationship (R2 = 0.76) that began to decrease from the initial repetition from 6 to 25 of the total repetitions. The MMG RMS exhibited a cubic relationship (R2 = 0.96) that began to increase from the initial repetition from 15 to 25 of the total repetitions. There was not a significant relationship for MMG MPF (r2 = 0.14). In addition, MMG MPF did not have a significant increase from the initial repetition during the 25 maximal isokinetic leg extension muscle actions.

 

Figure 3. Indicates the results from the vastus medialis for the combined regression and mean comparisons analysis of the time course of changes in the electromyographic (EMG) amplitude (RMS), EMG mean power frequency (MPF), mechanomyographic RMS, and MMG MPF normalized to the value of the initial repetition during 25 maximal isokinetic leg extension muscle actions at 120s-1. For the vastus medialis, EMG RMS had a positive linear relationship (R2 = 0.67) that that began to increase from the initial repetition from 4 to 25 of the total repetitions. There were no significant relationships for EMG MPF (r2 = 0.13), MMG RMS (r2 = 0.21), or MMG MPF (r2 = 0.09). In addition, EMG MPF, MMG RMS, or MMG MPF did not significantly change from the initial repetition during the 25 maximal isokinetic leg extension muscle actions.

 

Figure 4. Indicates the results from the rectus femoris for the combined regression and mean comparisons analysis of the time course of changes in the electromyographic (EMG) amplitude (RMS), EMG mean power frequency (MPF), mechanomyographic RMS, and MMG MPF normalized to the value of the initial repetition during 25 maximal isokinetic leg extension muscle actions at 120s-1. For the rectus femoris, EMG RMS had a positive quadratic relationship (R2 = 0.82) that began to increase from the initial repetition from 4 to 25 of the total repetitions. The EMG MPF had a negative linear relationship (r2 = 0.87) that began to decrease from the initial repetition from 9 to 25 of the total repetitions. There were no significant relationships for MMG RMS (r2 = 0.14) or MMG MPF (r2 = 0.19). In addition, MMG RMS or MMG MPF did not significantly change from the initial repetition during the 25 maximal isokinetic leg extension muscle actions.

 

 


3.4 Time Course of Changes from the Rectus Femoris

Figure 4 shows the results of the polynomial regression analyses and 1-way repeated measures ANOVAs with post-hoc Student Newman-Keuls tests for the normalized EMG RMS, EMG MPF, MMG RMS, and MMG MPF versus repetition relationships from the RF during 25 maximal isokinetic leg extensions at 120ºs-1. There was a significant 1-way repeated measure ANOVA (p = 0.02,  = 0.38) and positive quadratic relationship for EMG RMS (R2 = 0.76) versus repetition from the RF that began to increase from the initial repetition from 4 to 25 of the total repetitions (Figure 4). There was a significant 1-way repeated measure ANOVA (p < 0.01,  = 0.54) and negative linear relationship for EMG MPF (r2 = 0.87) versus repetition from the RF that began to decrease from the initial repetition from 9 to 25 of the total repetitions (Figure 4). There were no significant 1-way repeated measure ANOVA or polynomial regression relationship for MMG RMS (p = 0.18,  = 0.11; r2 = 0.14) or MMG MPF  (p = 0.14,  = 0.12; r2 = 0.19) versus repetition during the 25 maximal isokinetic leg extension muscle actions at 120ºs-1.

 

4. Discussion

 

4.1 Time Course of Changes in Maximal Isokinetic Peak Force

In the current study, there was a 21% decrease in maximal isokinetic peak force during the 25 maximal isokinetic leg extension at 120ºs-1. The maximal isokinetic peak force remained unchanged from the initial value during repetitions 1 to 9, and then decreased from the initial value from repetitions 9 to 25. These findings were similar to those of Camic, Housh (28) who reported an approximate 23% decrease in maximal isokinetic peak torque during 30 maximal isokinetic leg extensions at 30ºs-1. These findings also were similar to those of Cramer, Housh (29) who indicated minimal changes in maximal isokinetic peak torque during approximately the first 10 repetitions of maximal isokinetic leg extensions at 60, 180, and 300ºs-1. In addition, Cramer, Housh (29) reported after 25 and 50 maximal isokinetic leg extension at various velocities (60, 180, and 300 ºs-1), maximal isokinetic peak torque decreased between 30 C 45 and 50 C 75%, respectively. Therefore, these findings were similar to previous studies (28, 29) which reported minimal changes in maximal isokinetic force during the initial 9 repetitions and then began to decrease from the initial value for the remainder of the fatiguing task.  

 

4.2 Time Course of Changes in Neuromuscular Parameters

The force response to repeated isokinetic muscle contractions can be described by 5 unique phases of neuromuscular parameters from the VL, VM and RF. During the first phase, repetitions 1 to 4, there were no changes in maximal isokinetic peak force or any of the neuromuscular parameters (EMG RMS, EMG MPF, MMG RMS, and MMG MPF) from any of the muscles (VL, VM, and RF) (Figure 1). These findings were similar to those of Camic, Housh (28) who reported little to no changes for any of the neuromuscular parameters (EMG RMS, EMG MPF, MMG RMS, and MMG MPF) from the VL during the first 4 repetitions of maximal, concentric, isokinetic leg extensions at 30ºs-1 . In addition, Smith, Housh (4) reported no changes in EMG RMS, EMG MPF, MMG RMS, or MMG MPF for the first 10% of the time to exhaustion during a sustained isometric muscle action at 50% MVIC. The lack of changes in neuromuscular parameters during the initial phase of the fatiguing protocol suggested that there was no change in the motor unit control strategy used to maintain force production. Thus, from repetitions 1 to 4, there were no force or neuromuscular indicators of fatigue.

The second phase, repetitions 4 to 6, indicated no significant changes in maximal isokinetic peak force, but increases in EMG RMS from the VM and RF (Figure 1). This suggested that the VM and RF expressed the first signs of fatigue based on increased muscle activation (EMG RMS) to optimize force production between repetitions 4 and 6. These findings were similar to those of Smith (3) who reported greater increases in EMG RMS from the VM and RF compared to the VL during the first 10% of repetitions to failure during DCER leg extensions to failure at 30% 1-RM. Thus, during the second phase, there were fatigue-induced increases in muscle activation (EMG RMS) from the VM and RF, but not the VL. These findings suggested that during the initial 2 phases (repetitions 1 to 6) the VM and RF were more sensitive to the neuromuscular effects of fatigue than the VL.

During the third phase (repetitions 6 to 9), there were no changes in isokinetic peak force, but there were increases in muscle activation (EMG RMS) for the VM and RF as well as decreases in MUAP CV (EMG MPF) for the VL (Figure 1). These neuromuscular responses suggested that by repetition 6, the VL began to be affected by the fatigue-related buildup of metabolic byproducts which slowed the MUAPs propagation. These subtle changes in the motor unit control strategies during phases 2 and 3 enabled force production to be maintained (Figure 1).

From repetitions 9 to 15 (phase 4) there was a significant decrease in maximal isokinetic peak force accompanied by increases in EMG RMS from the VL, VM, and RF as well as decreases in EMG MPF from the VL and RF (Figure 1). These findings indicated increased muscle activation (EMG RMS) from all 3 muscles accompanied by fatigue-induced decreases in MUAP CV (EMG MPF) from the VL and RF. Thus, despite greater magnitude of changes in neuromuscular parameters, maximal isokinetic peak force decreased. Therefore, the changes in motor unit control strategies were not able to maintain a force level equal to the initial repetition.

During the final phase (repetitions 15 to 25), maximal isokinetic peak force continued to decrease and was accompanied by fatigue-induced changes in neuromuscular parameters from the VL, VM, and RF. The VL exhibited increases in MMG RMS, decreases in EMG MPF, and a plateau in EMG RMS. For the RF, there was a plateau in EMG RMS and decreases in EMG MPF from the RF. The VM, however, exhibited only fatigue-induced increases in EMG RMS. Thus, at the end of the fatiguing protocol, there were increases in muscle activation from all three muscles, however, only the VL and RF exhibited decreases in MUAP CV. In addition, the VL was the only muscle which had increases in MMG RMS. No muscle, at any repetition, exhibited significant changes in the global motor unit firing rates (MMG MPF).

 

4.3 Motor Unit Control Strategies

In the current study, there was a 21% decrease in maximal isokinetic peak force that decreased from repetitions 9 to 25 which was accompanied by unique neuromuscular responses from the VL, VM, and RF (Figure 1). These neuromuscular responses have been associated with motor unit control strategies used to maintain and optimize force production during a fatiguing task (3-5). Simultaneously examining the muscles within a muscle group allowed for the identification of muscle-specific motor unit control strategies used to maintain/optimize force production during the process of fatigue. The time course of changes in neuromuscular responses in the current study could not be explained by the AHP theory (9) which would predict an initial increase followed by a decrease in global motor unit firing rate (MMG MPF). According to the AHP theory (9), the maintenance and optimization of force production is primarily based upon changes in motor unit firing rate (MMG MPF), with less emphasis on changes in muscle activation (EMG RMS) or motor unit recruitment (MMG RMS). Thus, the lack of changes in global motor unit firing rate (MMG MPF), with increases in muscle activation and motor unit recruitment suggested that the AHP theory could not explain the motor unit control strategies used to maintain/optimize force production during 25 maximal isokinetic leg extension muscle actions at 120ºs-1.

According to the Muscle Wisdom theory (10) fatigue should be characterized by increases in motor unit recruitment (MMG RMS) and muscle activation (EMG RMS), but decreases in global motor unit firing rates (MMG MPF). The neuromuscular responses in the current study were in partial agreement with the Muscle Wisdom theory, however, there was no detectable change in the global motor unit firing rate (MMG MPF) from any of the muscles. The lack of changes in global motor unit firing rate (MMG MPF) from the VL, VM, and RF suggested that there was not an elongation of the twitch responses from the fatiguing motor units during the dynamic muscle actions. The Muscle Wisdom theory can explain the increases in muscle activation (EMG RMS) and motor unit recruitment (MMG RMS), however, without the expected decrease in global motor unit firing rates (MMG MPF) it is unlikely that the Muscle Wisdom theory could explain the motor unit control strategy employed to maintain or optimize force production during the fatiguing protocol.

Of the three primary motor unit control strategies examined in the present study (AHP theory, Muscle Wisdom theory, and the Onion Skin Scheme), the Onion Skin Scheme (1, 12) best explains the fatigue-induced neuromuscular responses from the VL, VM, and RF. Specifically, the Onion Skin Scheme (12) predicts increases in muscle activation (EMG RMS) and motor unit recruitment (MMG RMS), but no change or a decrease in motor unit firing rate. Similar to the AHP theory (9), the Onion Skin Scheme (1, 12) primarily focuses on motor unit firing rate to explain motor unit control strategies. That is, the Onion Skin Scheme (5, 12) suggests that motor unit firing rate is influenced by competing factors which include an increase in the firing rates of already recruited motor units and the addition of newly recruited motor units having lower firing rates than previously recruited ones. Therefore, depending on the level of fatigue and intensity of the muscle action, there should be unique patterns of responses for the global motor unit firing rate as reflected by MMG MPF within a muscle (1, 3, 12). Previous studies (3-5) examined submaximal muscle actions and reported decreases in global motor unit firing rates (MMG MPF), however, during maximal isokinetic muscle action there are fewer motor units available to activate during the fatiguing task. The fewer available non-recruited motor units in maximal versus submaximal muscle actions may result in less pronounced changes in global motor unit firing rates and, therefore, exhibit no changes in global motor unit firing rates (MMG MPF) (1, 12). In addition, during maximal muscle actions it is likely that all available motor units are activated, and, therefore, there should be no changes in EMG RMS or MMG RMS. The Onion Skin Scheme (1), however, suggests that there is an inherent protection mechanism which holds up to 10% of motor units in reserve during maximal muscle actions. It has been suggested (1) that this motor unit reserve can be utilized under conditions of extreme stress or fatigue. Thus, as fatigue progresses the previously unavailable motor units could explain the increases in EMG RMS and MMG RMS observed in the current study. Therefore, the neuromuscular responses from the VL, VM, and RF suggested that the Onion Skin Scheme provides the most compelling explanation for the patterns of fatigue-related force and neuromuscular responses in the present study.

 

4.4 Perspective

In the current study, maximal isokinetic peak force decreased from repetitions 9 to 25 and could be described by the 5 unique phases identified during the time course of changes in neuromuscular responses for the VL, VM, and RF. In general, the VL exhibited greater fatigue-induced changes than the VM and RF. In addition, the VL and RF demonstrated greater neuromuscular responses than the VM. Generally, there were increases in EMG RMS and MMG RMS, decreases in EMG MPF, but no changes in MMG MPF from the superficial muscles of the quadriceps femoris (VL, VM, and RF). The motor unit control strategies utilized to maintain and optimize force production could not be explained by the AHP or the Muscle Wisdom theory. These neuromuscular patterns of responses during maximal isokinetic leg extension muscle actions at 120ºs-1, however, could best be explained by the Onion Skin Scheme. Therefore, these findings indicated that examining the time course of changes can be used to infer on the motor unit control strategy employed to maintain force production and offset the effects of fatigue.  


 

 


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Conflict of Interest: No conflicts declared.

* Corresponding Author: Cory M. Smith. Department of Nutrition and Health Sciences, 110 Ruth Leverton Hall, University of Nebraska-Lincoln, Lincoln, NE 68583-0806, USA.

Phone: 402-472-2690. Email: CSmith@unl.edu.

© 2017 by the Authors | Journal of Nature and Science (JNSCI).