The current recommendations of the National Strength and Conditioning Association (NSCA) (43) and American College of Sports Medicine (ACSM) (25) are that resistance exercise loads of 60–85% of the 1 repetition maximum (1RM) are optimal for maximizing muscle hypertrophy. However, these recommendations have been challenged by recent experimental results indicating that low-load resistance exercise can elicit muscle hypertrophy to the same degree as heavier loads (9,41,44,52). For example, Burd et al. (9) demonstrated that resistance exercise performed to failure at 30% 1RM was able to elicit similar, and potentially greater, muscle protein synthesis and anabolic signaling compared with resistance exercise at 90% 1RM. In a follow-up study, Mitchell et al. (41) showed that 12 weeks of leg extension resistance training to failure at 30% 1RM was equally effective for producing muscle hypertrophy as 80% 1RM. Similarly, Ogasawara et al. (44) observed comparable muscle hypertrophy in response to 30 and 80% 1RM resistance training to failure in the pectoralis major and triceps brachii. Consequently, this evidence has sparked a debate regarding the optimal resistance training load to prescribe for muscle hypertrophy (8,47).
Despite the similar hypertrophic adaptations, several studies show that high-load training is superior for enhancing muscle strength (41,44,52). Mitchell et al. (41) demonstrated that 10 weeks of training at 80% 1RM increased 1RM strength to a greater degree than training at 30% 1RM, although both loads increased maximal isometric strength to a similar degree. Ogasawara et al. (44), however, observed greater improvements in both 1RM and maximal isometric strength after training at 80 vs. 30% 1RM. Van Roie et al. (52) also demonstrated that training at 80% 1RM was more beneficial for increasing 1RM and maximal isometric strength than training at 20–40% of 1RM. Despite the evidence showing similar hypertrophic adaptations, but greater strength adaptations after high-load vs. low-load resistance training, little is known about the neuromuscular adaptations that may facilitate the improvements in strength following high-load, but not low-load training.
Several studies have examined the acute neuromuscular mechanisms underlying a single session of high-load vs. low-load resistance training (15,32,46). However, to our knowledge, no previous studies have sought to examine the chronic neuromuscular adaptations to high-load vs. low-load resistance training. The surface electromyographic (EMG) signal is commonly used to examine neural adaptations to resistance training (20,27,37,42,50), whereas the mechanomyographic (MMG) signal is believed to reflect the mechanical counterpart of the motor unit electrical activity described by EMG (5,26). Voluntary activation (VA) has been used to describe the ability of individuals to recruit all available motor units driven to their maximal firing rates (24,36,39). Thus, the surface EMG and MMG signals, together with estimates of percent VA (%VA), may provide complimentary information regarding training-induced neural adaptations and/or changes in motor unit activation strategies after resistance training.
The first 4 weeks of a resistance training program in young, healthy, novice individuals often elicits strength gains that are believed to reflect neural adaptations that cannot be fully explained by hypertrophy (24,42). To examine these early phase neuromuscular adaptations after high-load vs. low-load resistance exercise, we chose to investigate untrained men after 2 and 4 weeks of resistance exercise. Therefore, the purpose of this study was to investigate the hypertrophic, strength, and neuromuscular adaptations to 2 and 4 weeks of resistance training at 80% vs. 30% 1RM in untrained men. We hypothesized that (a) resistance training at 80 and 30% 1RM would elicit limited, but similar muscle hypertrophy, (b) that muscle strength would increase to a greater extent after training at 80 than 30% 1RM, and (c) that there would be greater changes in EMG amplitude (AMP), EMG mean power frequency (MPF), MMG AMP, MMG MPF, and %VA for the 80 than 30% 1RM group.
Experimental Approach to the Problem
A randomized, repeated-measures, between-group, parallel design was used for this study. Subjects were randomly assigned to either a high-load (80% of 1RM; n = 8) or low-load (30% of 1RM; n = 7) resistance training group and were familiarized with the testing procedures. Subjects completed forearm flexion resistance training to failure 3 times per week for 4 weeks. Testing was completed at baseline, 2, and 4 weeks of training. All subjects completed a total of 14 visits, and each visit was separated by 48–72 hours at the same time of day (±2 hours). During each testing session, ultrasound (US), muscle strength, EMG, MMG, and VA were measured. The subjects were asked to refrain from any outside resistance exercise for the duration of the study. Figure 1 provides a detailed illustration of the testing and training schedule.
Eighteen men enrolled in this study; however, 3 men did not complete this study for the following reasons: 1 participant did not wish to continue the study because of discomfort during the testing sessions, 1 participant did not wish to continue the study because of the time commitment, and 1 participant withdrew to begin a resistance training program outside the study. Therefore, only the data from 15 men (mean ± SD; age = 21.7 ± 2.4 years; height = 181.6 ± 7.5 cm; weight = 84.7 ± 23.5 kg) were analyzed and reported in this article. This study was approved by the university's Institutional Review Board for the protection of human subjects (IRB Approval #: 20140314046FB) on March 14, 2014. Before any data collection, all subjects signed an informed consent form and completed a health history questionnaire. To be eligible, each participant must have been between the ages of 19 and 29, free from any current or ongoing musculoskeletal injuries or neuromuscular disorders involving the shoulders, elbows, or wrists, and could not have completed any regular or formal resistance training for at least 6 months before the start of the study.
Muscle thickness (MT) and echo intensity (EI) were assessed by US before any exercise testing. Transverse US images of the right forearm flexors were obtained using a portable brightness mode (B-mode) US-imaging device (GE Logiq e, USA) and a multifrequency linear-array probe (12L-RS; 5–13 MHz; 38.4 mm field-of-view). Images were obtained while the subjects were lying in the supine position with the right arm abducted, relaxed, and supported on the table with the forearm extended. Great care was taken to ensure that consistent, minimal pressure was applied with the probe to limit compression of the muscle. To enhance acoustic coupling and reduce near field artifacts, a generous amount of water-soluble transmission gel was applied to the skin. All MT and EI measurements were taken on the anterior surface of the arm at 33% of the distance between the cubital fossa and the acromion process of the scapula (33) (MTMid; EIMid), 3 cm proximal (MTProx; EIProx), and 3 cm distal (MTDist; EIDist). These locations were marked in permanent ink and kept throughout the duration of the study.
One investigator (N.D.M.J.) performed all US scans. The equipment settings for MT and EI measurements were optimized for image quality using the musculoskeletal mode before all testing and included a gain of 58 dB, a depth of 6 cm, and a frequency of 10 MHz. The equipment settings were held constant between visits and across subjects. The MT of the forearm flexors (i.e., biceps brachii [BB] and brachialis) was measured as the distance (cm) from the adipose tissue-muscle interface to the muscle-bone interface (33). All US imaging analyses were performed using Image-J Software (version 1.47v, National Institutes of Health, Bethesda, MD, USA). Before all analyses, each image was scaled from pixels to cm using the straight-line function in Image-J. The MT was determined using the straight-line function in the Image-J software. The EI was determined from the maximal rectangular region of interest using the rectangle function in Image-J that included as much of the BB muscle as possible without including any surrounding fascia (33). The mean EI value was calculated as a value between 0 (black) and 255 (white) arbitrary units (au).
Muscle Strength and Voluntary Activation Measurements
For isometric testing, the subjects were seated with straps securing the trunk and pelvis on a calibrated isokinetic dynamometer (Biodex System 3; Biodex Medical Systems, Inc., Shirley, NY, USA) with a custom-built apparatus (model LC402, range 0–500 lbs; Omegadyne, Stamford, CT, USA). The subjects' wrists were secured with a velcro strap, the axis of rotation of the dynamometer head was aligned with the axis of rotation of the elbow joint, and the arm was positioned in 10° of abduction to better expose the musculocutaneous nerve for transcutaneous nerve stimulation. The joint angle between the arm and the forearm was set at 90°, which was used for both voluntary and evoked isometric muscle actions. Subjects completed 2, 4–5 second maximal voluntary isometric contractions (MVIC) of the forearm flexors with 2 minutes of rest between each muscle action. The highest MVIC torque recorded was used to calculate the target force levels during the subsequent, randomly ordered, isometric step muscle actions at 10, 20, 30, 40, 50, 60, 70, 80, and 90% of MVIC. During each step muscle action, the subjects were required to trace their force production on an external computer monitor that displayed the real-time digitized force signal overlaid on the target force level. During these trials, doublet stimuli were applied to the musculocutaneous nerve (2) to assess %VA (i.e., interpolated twitch procedure). Three to 5 seconds after these submaximal step muscle actions, a doublet stimulus was administered at rest (potentiated twitch). A final 4–5 second MVIC was completed after the submaximal step muscle actions during which a doublet stimulus was also applied. Three to 5 seconds after this MVIC, a final potentiated twitch was evoked. Percent VA was calculated as (1-[superimposed twitch/potentiated twitch])*100 (1) during all submaximal step muscle actions and the final MVIC.
Transcutaneous electrical stimuli were delivered by bipolar surface electrodes placed over the musculocutaneous nerve just medial to the anterior deltoid using a high voltage (maximal voltage = 400 V), constant-current stimulator (Digitimer DS7AH, Hertfordshire, UK). Optimal stimulation electrode location was determined by delivering single low-amperage exploratory stimuli (20 mA) using a hand-held stimulation probe (Digitimer Bipolar Felt Pad Electrodes, Hertfordshire, UK). Electrode location was selected based on visual inspections of the twitch force and the compound muscle action potential (M-wave) amplitudes that were displayed on an external computer screen. Once the location was determined and marked, disposable 20 mm diameter adhesive surface electrodes (Plaquette Disposable 4-Disk Electrodes, Technomed Europe, the Netherlands) were taped to the skin with an interelectrode distance of 25.4 mm (distance between the anode and cathode of the hand-held probe). Maximal peak-to-peak M-wave amplitude (MP-P) was achieved by increasing amperage in 10–20 mA increments until a plateau in MP-P, and twitch force was observed after 3 consecutive amperage increases. To ensure a supramaximal stimulus, 120% of the stimulus used to evoke the maximal MP-P was used to evoke the forearm flexor muscles with a doublet stimulus (200 ms duration square-wave impulse at 100 Hz).
After US and isometric strength testing, 1RM testing was performed according to the guidelines established by the National Strength and Conditioning Association (43). Specifically, the subjects performed a light warm-up set with 5–10 repetitions at 50% of estimated 1RM, followed by 2–3 heavier warm-up sets of 2–5 repetitions with loads increasing by 10–20% at each set. Subjects then began completing trials of 1 repetition with increasing loads (10–20%) until they were no longer able to complete a single repetition. The highest load (kg) successfully lifted through the entire range of motion with proper technique was denoted as the 1RM, which was determined in ≤4 trials for all subjects. An electrogoniometer was fixed proximal and distal to the elbow joint during all 1RM attempts. Two to 4 minutes of rest were allowed between successive warm-up sets and 1RM trials.
Pregelled bipolar surface electrodes (Ag/AgCl, AccuSensor; Lynn Medical, Wixom, MI, USA) were placed on the BB muscle of the right arm with an interelectrode distance of 30 mm. The center of the bipolar electrode pair was placed at 33% of the distance between the cubital fossa and the acromion process (29). A single pregelled surface electrode (Ag/AgCl, AccuSensor; Lynn Medical) was placed on the lateral epicondyle of the humerus to serve as the reference electrode. All electrode locations were marked with a permanent marker and were kept throughout the duration of the study. To reduce interelectrode impedance and increase the signal-to-noise ratio (4), local areas of the skin were shaved, abraded, and cleaned with isopropyl alcohol before the placement of the electrodes. Interelectrode impedance was measured using a digital multimeter (Fluke 179 True RMS Multimeter, Everett, WA, USA) and was kept below 2,000 Ω (4).
Mechanomyographic signals were detected with a mini accelerometer (EGAS-FT-10/V05; Measurement Specialties, Inc., Hampton, VA, USA) that was preamplified with a gain of 200, a frequency response of 0–200 Hz, sensitivity of 70 mV/m·second−2, and range of ±98.1 m·second−2. The accelerometer was placed on the BB muscle at the center of the EMG electrode arrangement and was fixed with 3M double-sided foam tape (6).
Electromyographic, MMG, and force signals were recorded during all isometric testing. Electrogoniometer, EMG, and MMG signals were recorded during the 1RM attempts. The EMG, MMG, force, and electrogoniometer signals were sampled simultaneously at 2 kHz with a Biopac data acquisition system (MP150WSW; Biopac Systems, Inc., Santa Barbara, CA, USA), recorded on a personal computer, and processed offline with custom written software (Labview v. 12.0; National Instruments, Austin, TX, USA). The EMG signals were amplified (gain 1,000) using a differential amplifier (EMG 100, Biopac Systems, Inc., bandwidth 1–5,000 Hz) with a common mode rejection ratio of 110 dB min and an impedance of 2 MΩ, and signals digitally filtered (zero phase shift 4th order Butterworth filter) with a bandpass of 10–499 Hz. The MMG signals were digitally filtered (zero phase shift 4th order Butterworth filter) with a band pass of 5–100 Hz. The force and electrogoniometer signals were lowpass filtered (zero phase shift 4th order Butterworth filter) with a 15-Hz cutoff. The force obtained from the load cell (N) was multiplied by the lever arm length (m) to calculate torque (Nm). All subsequent analyses were completed on the filtered and scaled signals.
During the MVICs, the torque, EMG AMP, EMG MPF, MMG AMP, and MMG MPF values were calculated from the 500 ms epoch corresponding to the highest average force value that occurred during the MVIC plateau. During the submaximal isometric step muscle actions, EMG AMP, EMG MPF, MMG AMP, and MMG MPF values were calculated from a 500-ms steady force epoch that occurred before the delivery of the doublet stimulus (17,28). During 1RM testing, the EMG AMP and MPF values were calculated from the EMG signal epochs corresponding to the 70° range of motion occurring between 35° and 105° of forearm flexion (0° = full extension) during the concentric portion of each repetition based on the electrogoniometer signal. The EMG AMP was expressed as the integrated amplitude value (iEMG; μV.s) during the isometric muscle actions, and as the time-averaged, integrated amplitude value during the 1RM, which was calculated as the integral of the full-wave rectified EMG signal divided by the time over which it occurred (TA iEMG; μV) (40). The standard trapezoidal rule (35) was used to calculate all integrals. The MMG AMP was expressed as the root mean square (RMS) value in m·second−2. The frequency domain of the EMG and MMG signals were expressed as the MPF in Hz. To quantify EMG and MMG MPF, each signal epoch was processed with a Hamming window and a discrete Fourier transformation based on the recommendations of Diemont et al. (19) and calculated as described by Kwatny et al. (38).
The absolute EMG AMP, EMG MPF, MMG AMP, and MMG MPF values at 10–100% MVIC at baseline, week 2, and week 4 were normalized to the corresponding EMG AMP, EMG MPF, MMG AMP, and MMG MPF value at 100% MVIC at baseline and expressed as %MVIC.
During all 11 training visits, subjects completed 3 sets of dynamic constant external resistance forearm flexion resistance training (e.g., dumbbell biceps curls) to failure with loads corresponding (to the nearest 1.1 kg) to either 80 or 30% of 1RM. The subjects stood with their backs against a wall and their elbows supported by a brace (Bicep Bomber; Body Solid, Inc., Forest Park, IL, USA) to eliminate swinging of the torso or arms. Subjects were instructed to perform all repetitions through a complete range of motion. A metronome (Pro Metronome; EUMLab, Berlin, Germany) was set to 1 Hz, and subjects were instructed to perform the concentric and eccentric phases corresponding with each tick of the metronome so that the concentric and eccentric phases were approximately 1 second. Verbal instruction and encouragement were provided during each set. Failure was defined as the inability to complete another concentric muscle action through the full range of motion. Two minutes of rest was provided between sets for both conditions (80 and 30% 1RM). The weight used during training was adjusted based on the new 1RM established at the 2-week testing session. Total exercise volume was calculated for each subject as the sum of the product of the number of repetitions completed and the weight lifted and expressed in au for each set across all sets and exercise sessions. Total time under tension was calculated for each subject as the sum of the times to completion for each set across all sets and exercise sessions. Because it has been suggested that the timing and type of protein-ingested surrounding resistance training may augment the magnitude and duration of the muscle protein synthetic response to training (14), each participant consumed a protein shake mixed with water in the laboratory (EAS 100% Whey Protein; EAS Sports Nutrition, Abbott Laboratories, Columbus, OH, USA) that provided 150 kcals and 26 g of protein immediately after each resistance training session.
Two separate independent samples t-tests were used to analyze total exercise volume and time under tension. Two separate 3-way mixed factorial analyses of variance (ANOVAs) (time [Baseline vs. week 2 vs. week 4] × location [Prox vs. Mid vs. Dist] × group [80 1RM vs. 30% 1RM]) were used to analyze MT and EI. Four separate 2-way mixed factorial ANOVAs (time [Baseline vs. week 2 vs. week 4] × group [80% 1RM vs. 30% 1RM]) were used to analyze MVIC strength, 1RM strength, and EMG AMP and EMG MPF during the 1RMs. Five separate 3-way mixed factorial ANOVAs (time [Baseline vs. week 2 vs. week 4] × contraction intensity [10 vs. 20 vs. 30 vs. 40 vs. 50 vs. 60 vs. 70 vs. 80 vs. 90 vs. 100%] × group [80 1RM vs. 30% 1RM]) were used to analyze the EMG AMP, EMG MPF, MMG AMP, MMG MPF, and %VA data during the isometric step muscle actions. Cohen's d effect sizes were calculated for the independent samples t-tests used to analyze total exercise volume and time under tension. Partial eta-squared effect sizes () were calculated for each ANOVA. Significant interactions were decomposed with follow-up repeated-measures ANOVAs, and Sidak-Bonferroni or Fisher-Hayter corrected dependent and/or independent samples t-tests on the simple main effects. Significant main effects that were not involved in an interaction were analyzed with dependent samples t-tests on the marginal means. All statistical analyses were completed using IBM SPSS Statistics (v. 22; Armonk, NY, USA), and a type-I error rate was set a priori at 5%.
Test-retest reliability for MT, EI, MVIC, and 1RM strength; EMG AMP, EMG MPF, MMG AMP, MMG MPF, and %VA during MVIC; and EMG AMP and EMG MPF during 1RM was assessed from familiarization to baseline. Repeated-measures ANOVAs were used to assess systematic error, and model 2,k (49) was used to calculate intraclass correlation coefficients (ICCs) and SEMs. The SEMs were expressed as a percentage of the grand mean and were reported as coefficients of variation (CV) (30). The 95% confidence intervals for the ICCs were calculated according to the procedure described by Shrout and Fleiss (49).
Total Exercise Volume and Time Under Tension
The mean (±SE) repetitions completed during sets 1, 2, and 3 for the 80% group were 12.3 ± 0.4, 8.6 ± 0.3, and 6.6 ± 0.2 repetitions, respectively. The mean (±SE) repetitions completed during sets 1, 2, and 3 for the 30% group were 51.7 ± 9.4, 27.9 ± 4.9, and 24.5 ± 4.3 repetitions, respectively. There was no difference (p = 0.58; d = 0.30) in total exercise volume between the 80% (mean ± SE = 4,509.92 ± 558.01 au) vs. 30% 1RM (4,945.93 ± 510.69 au) groups. Total time under tension, however, was greater (p < 0.001; d = 6.46) for the 30% (2,262.34 ± 282.77 seconds) than 80% 1RM (805.66 ± 49.73 seconds) group (Figure 2).
Muscle Thickness and Echo Intensity
The mean values (±SE) for MT are displayed in Table 1. For MT, there were no interactions (p > 0.05; = 0.03–0.06), but there were main effects for location (p < 0.001; = 0.94) and time (p < 0.001; = 0.65). The MT increased from baseline (2.92 ± 0.11 cm) to week 2 (3.02 ± 0.11 cm) and from week 2 to 4 (3.14 ± 0.11 cm) for the 80 and 30% 1RM groups (Figure 3). The MTPROX (mean ± SE = 3.55 ± 0.13 cm) was greater than MTMID (2.95 ± 0.11 cm) and MTDIST (2.57 ± 0.10 cm), and MTMID was greater than MTDIST. For EI, there were no interactions (p > 0.05; = 0.04–0.17) or main effects for time (p = 0.08; = 0.18), location (p = 0.36; = 0.08), or group (p = 0.11; = 0.19).
Maximal Isometric Muscle Strength
For MVIC strength, there was a time × group interaction (p = 0.03; = 0.23). The MVIC strength did not change from baseline (111.71 ± 13.88 Nm) to week 2 (119.96 ± 16.58 Nm), but increased from week 2 to 4 (136.05 ± 19.31 Nm) in the 80% 1RM group (Figure 4). In contrast, MVIC strength did not change from baseline (103.05 ± 11.73 Nm) to week 2 (104.52 ± 12.23 Nm) or week 4 (109.45 ± 13.80 Nm) for the 30% 1RM group.
One Repetition Maximum
For 1RM strength, there was a time × group interaction (p ≤ 0.001; = 0.64). A 1RM strength was increased from baseline (17.33 ± 1.54 kg) to week 2 (19.60 ± 1.67 kg) and week 4 (21.02 ± 1.65 kg) but did not change from week 2 to 4 for the 80% 1RM group; whereas 1RM did not change from baseline (14.74 ± 1.53 kg) to week 2 (13.18 ± 1.47 kg) or week 4 (14.42 ± 1.55 kg) for the 30% 1RM group (Figure 5A). For EMG AMP during the 1RMs, there was a time × group interaction (p = 0.01; = 0.28). The EMG AMP increased from baseline (1,324.70 ± 203.17 μV) to week 4 (1,869.64 ± 273.32 μV) for the 80% group but did not change (1,478.17 ± 228.40 μV, 1,531.27 ± 309.41 μV, 1,378.63 ± 209.71 μV, at baseline, week 2, and 4, respectively) for the 30% 1RM group (Figure 5B). For EMG MPF during the 1RMs, there was no time × group interaction (p = 0.76; = 0.02) or main effect for time (p = 0.62; = 0.04) (Figure 5C).
Electromyographic Amplitude and Mean Power Frequency During Isometric Step Muscle Actions
For EMG AMP, there were no interactions (p > 0.05; = 0.01–0.07) or main effects for time (p = 0.98; < 0.01) or group (p = 0.70; = 0.01). However, there was a main effect for contraction intensity (p < 0.001; = 0.92). The EMG AMP increased from 10% (5.80 ± 0.57% MVIC) to 100% (104.97 ± 2.83% MVIC) MVIC.
For EMG MPF, there were no interactions (p > 0.05; = 0.06–0.11) or main effects for time (p = 0.06; = 0.20), contraction intensity (p = 0.06; = 0.13), or group (p = 0.37; = 0.06).
Mechanomyographic Amplitude and Mean Power Frequency During Isometric Step Muscle Actions
Figure 6 depicts the normalized MMG AMP vs. force relationships at baseline, week 2, and 4 for the 80 and 30% 1RM groups. For MMG AMP, there was a time × contraction intensity interaction (p = 0.03; = 0.12). At baseline, MMG AMP did not change from 10 to 20% MVIC, increased from 20% to 80% MVIC, plateaued from 80 to 90% MVIC, and then decreased at 100% MVIC. At week 2, MMG AMP did not change from 10 to 30% MVIC, increased from 30% to 80% MVIC, and then plateaued from 80 to 100% MVIC. At week 4, MMG AMP did not change from 10 to 30% MVIC, increased from 30% to 60% MVIC, and then plateaued from 60 to 100% MVIC. The MMG AMP at 80 and 90% MVIC decreased from baseline (116.71 ± 7.51 and 118.37 ± 8.56% MVIC, respectively) to week 4 (86.91 ± 8.02% MVIC and 92.73 ± 8.87% MVIC, respectively).
For MMG MPF, there were no interactions (p > 0.05; = 0.04–0.08) or main effects for time (p = 0.80; = 0.02) or group (p = 0.18; = 0.14). However, there was a main effect for contraction intensity (p < 0.001; = 0.42). The MMG MPF increased from 10 to 30% MVIC, plateaued from 30 to 90% MVIC, and then decreased at 100% MVIC.
Voluntary Activation during Isometric Step Muscle Actions
For %VA, there was a time × contraction intensity interaction (p ≤ 0.001; = 0.16). In general, %VA increased from 10 to 70% MVIC and then plateaued from 70 to 100% MVIC at baseline and week 2, and increased from 10 to 80% and then plateaued from 90 to 100% MVIC at week 4. At 20% MVIC, %VA increased from baseline (37.6 ± 5.5%) to week 2 (53.6 ± 4.4%), but week 4 (46.1 ± 5.6%) was not different from baseline or week 2. At 30% MVIC, %VA did not change from baseline (54.7 ± 4.6%) to week 2 (62.2 ± 3.7%) but increased to week 4 (66.2 ± 3.8%).
There was no systematic variability from familiarization to baseline for any of the variables (p > 0.05) except for 1RM strength. The 1RM strength increased (p = 0.03) from 15.56 to 16.12 kg from familiarization to baseline. All ICCs were greater than zero (p ≤ 0.05) according to the 95% confidence intervals. The ICCs for MTMID, MTPROX, and MTDIST were 0.96, 0.99, and 0.97, respectively. The SEMs for MTMID, MTPROX, and MTDIST were 0.10, 0.04, and 0.08 cm, respectively. The CVs for MTMID, MTPROX, and MTDIST were 3.07, 1.58, and 3.17%, respectively. The ICCs for EIMID, EIPROX, and EIDIST were 0.73, 0.75, and 0.65, respectively. The SEMs for EIMID, EIPROX, and EIDIST were 4.32, 3.78, and 5.88 au, respectively. The CVs for EIMID, EIPROX, and EIDIST were 3.26, 2.91, and 4.58%, respectively. The ICC, SEM, and CV for MVIC strength were 0.96, 7.45 Nm, and 6.99%, respectively. The ICCs for EMG AMP, EMG MPF, MMG AMP, MMG MPF, and %VA during MVIC were 0.70, 0.86, 0.58, 0.74, and 0.60, respectively. The SEMs for EMG AMP, EMG MPF, MMG AMP, MMG MPF, and %VA during MVIC were 118.60 µV.s, 3.64 Hz, 0.09 m·second−2, 3.00 Hz, and 2.04%, respectively. The CVs for EMG AMP, EMG MPF, MMG AMP, MMG MPF, and %VA during MVIC were 26.02, 5.08, 15.79, 16.08, and 2.09%, respectively. The ICC, SEM, and CV for 1RM strength were 0.99, 1.36 kg, and 3.91%, respectively. For EMG AMP and EMG MPF during 1RM, the ICCs were 0.85 and 0.78, the SEMs were 268.64 μV and 6.44 Hz, and the CVs were 17.75 and 8.21%, respectively.
Our study is the first, to our knowledge, to examine the neuromuscular adaptations to high-load vs. low-load resistance training. The primary results of this study indicated that MT increased similarly (7 and 9%) after 4 weeks of training for the 80 and 30% 1RM groups, respectively. In contrast, MVIC and 1RM strength increased by 23 and 22%, respectively, in the 80% 1RM group but did not improve significantly in the 30% 1RM group (7 and 1% increases, respectively). The increase in 1RM strength for the 80% 1RM group was accompanied by a 43% increase in EMG AMP, whereas there was no change in EMG AMP for the 30% 1RM group. There were also subtle changes from pretraining to posttraining in the normalized MMG AMP and %VA vs. force relationships, but these changes were independent of the training loads. Therefore, our results supported previous studies showing that high-load and low-load resistance training to failure resulted in similar muscular hypertrophy (41,44); however, only the high-load resistance training caused significant increases in maximal isometric (44) and 1RM strength (41,44). Our results extended previous findings (41,44) by suggesting that the neuromuscular adaptations during 4 weeks of training at 80 and 30% 1RM were not only subtle and similar but also difficult to explain with EMG, MMG, and %VA at adapting submaximal percentages of MVIC. Therefore, there may be other methods by which to evaluate the different neuromuscular adaptations that seem to be occurring during the early phases of resistance training programs at 80 vs. 30% 1RM.
Mitchell et al. (41) demonstrated 6–7% increases in quadriceps muscle volume after 10 weeks of resistance training to failure at 80% and 30% 1RM. Ogasawara et al. (44) showed similar 10–12% increases in triceps brachii and 18–21% increases in pectoralis major muscle cross-sectional areas (mCSA) after 6 weeks of resistance training to failure at 75 and 30% 1RM. Our results supported that the findings of Mitchell et al. (41) and Ogasawara et al. (44) and showed that resistance training to failure at 80 and 30% 1RM produced similar hypertrophy in the forearm flexors after 4 weeks of resistance training (Figure 3). Our applied data also supported the findings of Burd et al. (9) who demonstrated similar acute increases in muscle protein synthesis after resistance training at 30 vs. 90% 1RM to failure. It should also be noted that although Mitchell et al. (41) and Ogasawara et al. (44) used magnetic resonance imaging (MRI) technology to measure muscle volume and/or mCSA, the US measurements of MT used in this study were capable of demonstrating short-term, 4-week adaptations. Therefore, these data also supported our previous study (33), which demonstrated that single transverse US imaging for quantifying changes in MT was sensitive and reliable measurement in the forearm flexors, which is easier and less expensive than MRI.
Interestingly, muscle hypertrophy is typically regarded as minimal during the first 4 weeks of a resistance training program (24,42), and the increases in muscle strength observed during this period are generally attributed to neural adaptations (24,42,45). However, recent studies have indicated that hypertrophy can occur during the early stages of a resistance training program. For example, Seynnes et al. (48) demonstrated 4–5% increases in leg extensor mCSA after 20 days of training, whereas DeFreitas et al. (18) showed a 3% increase in thigh mCSA after only 2 training sessions and a 6% increase in hypertrophy after 4 weeks of training. However, Damas et al. (16) recently suggested that early phase resistance training-induced increases in muscle size may be partly due to edema. Thus, our data were added to the growing body of the literature (18,48) suggesting that muscle hypertrophy may occur earlier than reported previously (42) during the time course of a resistance training program, although it is possible that edema had some influence on our MT values.
It was hypothesized that achieving similar levels of muscle activation during low-load and high-load resistance training to failure was the primary explanation for the similar muscle protein synthetic rates (9) and muscle hypertrophy (9,41) observed in previous studies. However, more recent studies have suggested that muscle activation is lower during training at 30% vs. 75–80% 1RM to failure (32,46). Consequently, it is likely that other factors such as exercise volume (9,32) or time under tension (7,32) may influence the hypertrophic response to high-load vs. low-load resistance training. In this study, exercise volume was not different (4,946 au vs. 4,510 au), whereas time under tension was 181% greater for the 30% vs. 80% 1RM groups (Figure 2). Therefore, the similar hypertrophic adaptations observed in this study in the 30% 1RM and 80% 1RM groups may be explained, in part, by the greater time under tension for the 30% 1RM group despite the lower training load or by the similar overall training volume for the 80 and 30% 1RM groups.
Although muscle hypertrophy was similar between the 30 and 80% 1RM groups in this study, muscle strength increased in the 80% 1RM group but not the 30% 1RM group. These data supported previous studies (10,41,44) indicating that high-load training (i.e., 75–80% 1RM) was superior to low-load training (i.e., 30% 1RM) for increasing muscle strength. For example, Mitchell et al. (41) reported 34–36% and vs. 20–27% increases in MVIC and 1RM leg extension strength after 10 weeks of 80 vs. 30% 1RM training, respectively. Ogasawara et al. (44) reported 14–21% vs. 7–9% increases in forearm extension MVIC and bench press 1RM strength after 6 weeks of 75 vs. 30% 1RM training, respectively. Campos et al. (10) reported greater improvements in leg press strength after 8 weeks of training with 9–11RM loads compared with 20–28RM loads, although squat and leg extension strength increased similarly in both groups. Despite the relatively consistent differences in strength adaptations after high-load vs. low-load resistance training, the mechanism(s) responsible are not clear.
In this study, there were no changes in the EMG AMP vs. force relationships from baseline to week 4 for either group, despite nonsignificant 15 and 6% increases in EMG AMP during MVIC for the 80 and 30% 1RM groups, respectively. Electromyographic AMP has been used to examine neural adaptations to resistance training (20,27,37,42,50). For example, Moritani and deVries (42) interpreted training-induced increases in EMG AMP as neural adaptations and stated that the EMG “…activation level is necessarily the result of the interaction of both facilitatory and inhibitory phenomena, which may act at various levels of the nervous system” (pg. 116). Similarly, Komi et al. (37) and Thepaut-Mathieu et al. (50) reported training-induced increases in EMG AMP and suggested that these increases reflected greater motor unit activation after training. However, the practice of interpreting changes in surface EMG AMP as reflective of neural adaptations has been criticized (3,11,23). Cannon and Cafarelli (11) observed increased MVIC strength in the trained and untrained limbs after 5 weeks of unilateral training without a corresponding increase in EMG AMP. The authors (11) suggested that the increased strength was related to peripheral adaptations such as muscle fiber hypertrophy but could not discount the possibility of central nervous system adaptations that were not manifested in EMG AMP. Therefore, the early phase strength adaptations observed in the 80% 1RM group in this study may have resulted, in part, from neural adaptations that were not identified by EMG AMP.
In this study, there were similar training-induced changes in the MMG AMP vs. force relationships for both the 80 and 30% 1RM groups. Few studies (17,20,21) have investigated the effects of resistance training on MMG AMP. Evetovich et al. (21) and Ebersole et al. (20) reported no changes in MMG AMP after 12 and 8 weeks of isokinetic or isometric training, respectively. DeFreitas et al. (17), however, examined the MMG AMP vs. force relationships after 8 weeks of dynamic constant external resistance training at 80% 1RM and demonstrated significant decreases in MMG AMP at 30–60% and 80–100% MVIC. The authors (17) suggested that the training-induced decreases in MMG AMP represented a hypertrophy-related decrease in motor unit recruitment because an increase in contractile protein content would decrease the need for active motor units to produce the same force compared with pretraining. Alternatively, it has been suggested that training-induced hypertrophy may cause increases in muscle stiffness, which would attenuate the MMG signal (17,20). In this study, there were significant decreases in MMG AMP at 80 and 90% of MVIC from baseline to week 4 after both 80 and 30% 1RM training (Figure 6). Together with the similar hypertrophy observed in the 80 and 30% 1RM groups in this study, our findings supported the hypothesis of DeFreitas et al. (17) regarding a diminished need for motor unit recruitment or increased muscle stiffness caused by muscle hypertrophy. Future studies are needed to examine the utility of MMG AMP at the same absolute force levels for measuring the efficiency of activation during resistance training programs.
There were no changes in MMG MPF after training for the 80 or 30% 1RM groups. Our results supported those of Evetovich et al. (22), who observed no change in MMG MPF after 12 weeks of isokinetic leg extension training despite an increase in peak torque. However, our results were not consistent with Cerquiglini et al. (13) who reported a shift toward higher frequencies in the MMG power density spectrum after 2 months of resistance training. Training-induced increases in the frequency of the MMG signal may be related to increased muscle stiffness manifested by an increase in the muscle's resonance frequency (5,22) and/or increases in motor unit firing rate (Beck et al. 2005). The MPF of the EMG signal may also contain information regarding the global motor unit firing rate and motor unit synchronization (23). Despite the lack of changes observed in this study for either MMG or EMG MPF, we cannot rule out potential training-induced changes in muscle stiffness, motor unit firing rate, or synchronization. Future studies should compare the effects of high-load vs. low-load resistance training on variables that may be influenced by musculotendinous stiffness, motor unit firing rate, and/or synchronization such as the electromechanical delay (12) and rate of torque development (31,34,51).
Overall, the results indicated that 4 weeks of resistance training to failure at 80 and 30% 1RM caused similar muscle hypertrophy in the forearm flexors. However, training at 80% 1RM caused greater strength adaptations. Despite the increases in strength for only the 80% 1RM group, there were similar training-induced changes in the MMG AMP vs. force relationships for both the 80 and 30% 1RM groups that may have reflected subtle adaptations in motor unit recruitment and/or muscle stiffness. We also observed small changes in %VA at submaximal force levels that occurred independent of the training load. However, there were no training-induced changes in EMG AMP, EMG MPF, or MMG MPF for either group. Because of the different strength but similar hypertrophic and subtle neuromuscular adaptations observed for the high-load and low-load training groups in this study, future studies are needed to further understand the specific adaptations to high-load vs. low-load resistance training that may underlie the differential strength improvements.
The results of this study indicate that 4 weeks of resistance training to failure with loads at 30% of 1RM may elicit similar increases in muscle size as training at 80% of 1RM. Training at 80% 1RM, however, seems to be superior for increasing muscle strength. These disparate strength adaptations were difficult to explain with neuromuscular adaptations because they were subtle and similar for the 80 and 30% 1RM groups. Thus, future studies are needed to further investigate the neuromuscular adaptations to high-load vs. low-load training.
The authors would like to thank Noelle M. Yeo and Jessie M. Miller for their help with data collection. This study was supported in part by the University of Nebraska Agricultural Research Division with funds provided through the Hatch Act (Agency: US Department of Agriculture, National Institute of Food and Agriculture; Accession No: 1000080; Project No: NEB-36–078).
1. Allen GM, Gandevia SC, McKenzie DK. Reliability of measurements of muscle strength
and voluntary activation using twitch interpolation. Muscle Nerve 18: 593–600, 1995.
2. Allen GM, McKenzie DK, Gandevia SC. Twitch interpolation of the elbow flexor muscles at high forces. Muscle Nerve 21: 318–328, 1998.
3. Arabadzhiev TI, Dimitrov VG, Dimitrov GV. The increase in surface EMG could be a misleading measure of neural adaptation during the early gains in strength. Eur J Appl Physiol 114: 1645–1655, 2014.
4. Beck TW, Housh TJ. Use of electromyography
in studying human movement. In: Routledge Handbook of Biomechanics and Human Movement. Hong Y., Bartlett R., eds. New York, NY: Routledge, 2008. pp. 214–230.
5. Beck TW, Housh TJ, Cramer JT, Weir JP, Johnson GO, Coburn JW, Malek MH, Mielke M. Mechanomyographic amplitude and frequency responses during dynamic muscle actions: A comprehensive review. Biomed Eng Online 4: 67, 2005.
6. Beck TW, Housh TJ, Johnson GO, Weir JP, Cramer JT, Coburn JW, Malek MH. Mechanomyographic and electromyographic responses during submaximal to maximal eccentric isokinetic muscle actions of the biceps brachii. J Strength Cond Res 20: 184–191, 2006.
7. Burd NA, Andrews RJ, West DW, Little JP, Cochran AJ, Hector AJ, Cashaback JG, Gibala MJ, Potvin JR, Baker SK, Phillips SM. Muscle time under tension during resistance exercise stimulates differential muscle protein sub-fractional synthetic responses in men. J Physiol 590: 351–362, 2012.
8. Burd NA, Moore DR, Mitchell CJ, Phillips SM. Big claims for big weights but with little evidence. Eur J Appl Physiol 113: 267–268, 2013.
9. Burd NA, West DW, Staples AW, Atherton PJ, Baker JM, Moore DR, Holwerda AM, Parise G, Rennie MJ, Baker SK, Phillips SM. Low-load
high volume resistance exercise stimulates muscle protein synthesis more than high-load
low volume resistance exercise in young men. PLoS One 5: e12033, 2010.
10. Campos GE, Luecke TJ, Wendeln HK, Toma K, Hagerman FC, Murray TF, Ragg KE, Ratamess NA, Kraemer WJ, Staron RS. Muscular adaptations in response to three different resistance-training regimens: Specificity of repetition maximum training zones. Eur J Appl Physiol 88: 50–60, 2002.
11. Cannon RJ, Cafarelli E. Neuromuscular adaptations to training. J Appl Physiol (1985) 63: 2396–2402, 1987.
12. Cavanagh PR, Komi PV. Electromechanical delay in human skeletal muscle under concentric and eccentric contractions. Eur J Appl Physiol 42: 159–163, 1979.
13. Cerquiglini S, Figura F, Marchetti M, Salleo A. Evaluation of athletic fitness in weight lifters through biomechanical, bioelectrical, and biacoustical data. In: Biomechnics III. Joki F., ed. Basel, Switzerland: Karger, 1973. pp. 189–195.
14. Churchward-Venne TA, Burd NA, Phillips SM. Nutritional regulation of muscle protein synthesis with resistance exercise: Strategies to enhance anabolism. Nutr Metabol 9: 40, 2012.
15. Cook SB, Murphy BG, Labarbera KE. Neuromuscular function after a bout of low-load
blood flow-restricted exercise. Med Sci Sports Exerc 45: 67–74, 2013.
16. Damas F, Phillips SM, Lixandrao ME, Vechin FC, Libardi CA, Roschel H, Tricoli V, Ugrinowitsch C. Early resistance training-induced increases in muscle cross-sectional area are concomitant with edema-induced muscle swelling. Eur J Appl Physiol 116: 49–56, 2015.
17. DeFreitas JM, Beck TW, Stock MS. Effects of strength training on mechanomyographic amplitude. Physiol Meas 33: 1353–1361, 2012.
18. DeFreitas JM, Beck TW, Stock MS, Dillon MA, Kasishke PR II. An examination of the time course of training-induced skeletal muscle hypertrophy
. Eur J Appl Physiol 111: 2785–2790, 2011.
19. Diemont B, Figini MM, Orizio C, Perini R, Veicsteinas A. Spectral analysis of muscular sound at low and high contraction level. Int J Biomed Comp 23: 161–175, 1988.
20. Ebersole KT, Housh TJ, Johnson GO, Perry SR, Bull AJ, Cramer JT. Mechanomyographic and electromyographic responses to unilateral isometric training. J Strength Cond Res 16: 192–201, 2002.
21. Evetovich TK, Housh TJ, Johnson GO, Smith DB, Ebersole KT, Perry SR. Gender comparisons of the mechanomyographic responses to maximal concentric and eccentric isokinetic muscle actions. Med Sci Sports Exerc 30: 1697–1702, 1998.
22. Evetovich TK, Housh TJ, Weir JP, Housh DJ, Johnson GO, Ebersole KT, Smith DB. The effect of leg extension training on the mean power frequency of the mechanomyographic signal. Muscle Nerve 23: 973–975, 2000.
23. Farina D, Merletti R, Enoka RM. The extraction of neural strategies from the surface EMG. J Appl Physiol (1985) 96: 1486–1495, 2004.
24. Gabriel DA, Kamen G, Frost G. Neural adaptations to resistive exercise—Mechanisms and recommendations for training practices. Sports Med 36: 133–149, 2006.
25. Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee IM, Nieman DC, Swain DP; American College of Sports Medicine. American college of sports medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med Sci Sports Exerc 43: 1334–1359, 2011.
26. Gordon G, Holbourn AH. The sounds from single motor units in a contracting muscle. J Physiol 107: 456–464, 1948.
27. Hakkinen K, Komi PV. Electromyographic changes during strength training and detraining. Med Sci Sports Exerc 15: 455–460, 1983.
28. Herda TJ, Ryan ED, Beck TW, Costa PB, DeFreitas JM, Stout JR, Cramer JT. Reliability of mechanomyographic amplitude and mean power frequency during isometric step and ramp muscle actions. J Neurosci Meth 171: 104–109, 2008.
29. Hermens HJ, Freriks B, Merletti R, Stegeman D, Blok J, Rau G, Disselhorst-Klug C, Hagg G. SENIAM 8: European Recommendations for Surface Electromyography
. The Netherlands: Roessngh Research and Development, 1999.
30. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 30: 1–15, 2000.
31. Jenkins ND, Buckner SL, Cochrane KC, Bergstrom HC, Palmer TB, Johnson GO, Schmidt RJ, Housh TJ, Cramer JT. Age-related differences in rates of torque development and rise in EMG are eliminated by normalization. Exp Gerontol 57C: 18–28, 2014.
32. Jenkins ND, Housh TJ, Bergstrom HC, Cochrane KC, Hill EC, Smith CM, Johnson GO, Schmidt RJ, Cramer JT. Muscle activation during three sets to failure at 80% vs. 30% 1RM resistance exercise. Eur J Appl Physiol 115: 2335–2347, 2015.
33. Jenkins ND, Miller JM, Buckner SL, Cochrane KC, Bergstrom HC, Hill EC, Smith CM, Housh TJ, Cramer JT. Test-retest reliability of single transverse versus panoramic ultrasound imaging for muscle size and echo intensity of the biceps brachii. Ultrasound Med Biol 41: 1584–1591, 2015.
34. Jenkins NDM, Palmer TB, Cramer JT. Comparisons of voluntary and evoked rate of torque development and rate of velocity development during isokinetic muscle actions. Isokinet Exerc Sci 21: 253–261, 2013.
35. Kline M. Calculus: An Intuitive and Physical Approach. New York, NY: Wiley, 1967.
36. Knight CA, Kamen G. Adaptations in muscular activation of the knee extensor muscles with strength training in young and older adults. J Electromyogr Kinesiol 11: 405–412, 2001.
37. Komi PV, Viitasalo JT, Rauramaa R, Vihko V. Effect of isometric strength training of mechanical, electrical, and metabolic aspects of muscle function. Eur J Appl Physiol 40: 45–55, 1978.
38. Kwatny E, Thomas DH, Kwatny HG. An application of signal processing techniques to the study of myoelectric signals. IEEE Trans Biomed Eng 17: 303–313, 1970.
39. Lee M, Gandevia SC, Carroll TJ. Short-term strength training does not change cortical voluntary activation. Med Sci Sports Exerc 41: 1452–1460, 2009.
40. Merletti R. Standards for reporting EMG data. J Electromyogr Kinesiol 9: III–IV, 1999.
41. Mitchell CJ, Churchward-Venne TA, West DW, Burd NA, Breen L, Baker SK, Phillips SM. Resistance exercise load
does not determine training-mediated hypertrophic gains in young men. J Appl Physiol (1985) 113: 71–77, 2012.
42. Moritani T, deVries HA. Neural factors versus hypertrophy in the time course of muscle strength
gain. Am J Phys Med 58: 115–130, 1979.
43. NSCA. Essentials of Strength Training and Conditioning. Champaign, IL: Human Kinetics, 2008.
44. Ogasawara R, Loenneke JP, Thiebaud RS, Abe T. Low-load
bench press training to fatigue results in muscle hypertrophy
similar to high-load
bench press training. Int J Clin Med 4: 114–121, 2013.
45. Sale DG. Neural adaptation to resistance training. Med Sci Sports Exerc 20: S135–S145, 1988.
46. Schoenfeld BJ, Contreras B, Willardson JM, Fontana F, Tiryaki-Sonmez G. Muscle activation during low- versus high-load
resistance training in well-trained men. Eur J Appl Physiol 114: 2491–2497, 2014.
47. Schuenke MD, Herman J, Staron RS. Preponderance of evidence proves “big” weights optimize hypertrophic and strength adaptations. Eur J Appl Physiol 113: 269–271, 2013.
48. Seynnes OR, de Boer M, Narici MV. Early skeletal muscle hypertrophy
and architectural changes in response to high-intensity resistance training. J Appl Physiol (1985) 102: 368–373, 2007.
49. Shrout PE, Fleiss JL. Intraclass correlations: Uses in assessing rater reliability. Psychol Bull 86: 420–428, 1979.
50. Thepaut-Mathieu C, Van Hoecke J, Maton B. Myoelectrical and mechanical changes linked to length specificity during isometric training. J Appl Physiol (1985) 64: 1500–1505, 1988.
51. Van Cutsem M, Duchateau J, Hainaut K. Changes in single motor unit behaviour contribute to the increase in contraction speed after dynamic training in humans. J Physiol 513: 295–305, 1998.
52. Van Roie E, Bautmans I, Boonen S, Coudyzer W, Kennis E, Delecluse C. Impact of external resistance and maximal effort on force-velocity characteristics of the knee extensors during strengthening exercise: A randomized controlled experiment. J Strength Cond Res 27: 1118–1127, 2013.