Muscular endurance training and motor unit firing patterns during fatigue

Abstract

With
muscular training, the central nervous system may regulate motor unit firing rates to sustain force output and delay fatigue. The aims of this study were to investigate motor unit firing rates and patterns of the adductor pollicis (AdP) muscle in young, able-bodied adults throughout a sustained submaximal isometric fatiguing contraction and postactivation potentiation pre-post 4 weeks of muscular endurance training. Fifteen participants (training group: N = 10; control group: N = 5) performed maximal voluntary contractions (MVCs) and a sustained isometric 20 % MVC fatigue task pre-post training. Single-motor-unit potentials were recorded from the AdP during the fatigue task with intramuscular fine-wire electrodes. Twitch force potentiation was measured during single-pulse electrical stimulation of the ulnar nerve before and after MVCs. The training group endurance trained their AdP muscle at 20 % MVC for 4 weeks. Mean motor unit firing rates were calculated every 5 % of endurance time (ET). ET increased by 45.2 ± 8.7 % (p < 0.001) following muscular endurance training. Although ET increased, mean motor unit firing rates during the fatigue task did not change significantly with training. The general motor unit firing pattern consisted of an initial slowing followed by an increase in firing rate late in fatigue and remained consistent pre-post training. Potentiation did not change following training. These data suggest that the ability of the neuromuscular system to sustain motor unit firing rate may serve as a mechanism to augment the duration of submaximal muscle performance and delay muscular fatigue.

Full text

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Exp Brain Res (2016) 234:267–276
DOI 10.1007/s00221-015-4455-x
RESEARCH ARTICLE
Muscular endurance training and motor unit firing patterns
during fatigue
Joni A. Mettler1 · Lisa Griffin2
Received: 28 March 2015 / Accepted: 23 September 2015 / Published online: 8 October 2015
© Springer-Verlag Berlin Heidelberg 2015
neuromuscular system to sustain motor unit firing rate may
serve as a mechanism to augment the duration of submaxi-
mal muscle performance and delay muscular fatigue.
Keywords Motor unit · Training · Potentiation ·
Muscular endurance · Fatigue
Introduction
The neuromuscular system is highly adaptable and quickly
responds to new patterns of muscular activity. In the earli-
est phase of muscular training, changes in force production
may be due to neuromuscular adaptations related to learn-
ing optimal muscle activation patterns (for review, see Grif-
fin and Cafarelli 2005; Carroll et al. 2011). For example,
increases in motor unit firing rate (Van Cutsem et al. 1998;
Kamen and Knight 2004) and earlier motor unit recruit-
ment (Van Cutsem et al. 1998; Keen et al. 1994) occur dur-
ing the first few weeks of resistance training. Maximal H
to M (H/M) wave ratios of the triceps surae muscles are
higher in endurance-trained compared to power-trained
and sedentary individuals (Rochcongar et al. 1979; Maffi-
uletti et al. 2001), suggesting that endurance training may
increase excitability of the spinal cord. Further, motor unit
firing rates during a brief non-fatiguing contraction at 30 %
maximal voluntary contraction (MVC) were lower after
6 weeks of aerobic cycle ergometer training (Vila-Cha et al.
2010). In contrast, the same study also found that motor
unit firing rates during brief non-fatiguing contractions
were higher after resistance training (Vila-Cha et al. 2010).
The study by Vila-Cha et al. (2010) and other studies cited
above indicate that the specificity of training principle may
play a role in training-related neuromuscular adaptations,
namely single-motor-unit firing rate patterns. Therefore, it
Abstract With muscular training, the central nerv-
ous system may regulate motor unit firing rates to sus-
tain force output and delay fatigue. The aims of this study
were to investigate motor unit firing rates and patterns of
the adductor pollicis (AdP) muscle in young, able-bodied
adults throughout a sustained submaximal isometric fatigu-
ing contraction and postactivation potentiation pre-post
4 weeks of muscular endurance training. Fifteen partici-
pants (training group: N = 10; control group: N = 5) per-
formed maximal voluntary contractions (MVCs) and a
sustained isometric 20 % MVC fatigue task pre-post train-
ing. Single-motor-unit potentials were recorded from the
AdP during the fatigue task with intramuscular fine-wire
electrodes. Twitch force potentiation was measured during
single-pulse electrical stimulation of the ulnar nerve before
and after MVCs. The training group endurance trained their
AdP muscle at 20 % MVC for 4 weeks. Mean motor unit
firing rates were calculated every 5 % of endurance time
(ET). ET increased by 45.2 ± 8.7 % (p < 0.001) follow-
ing muscular endurance training. Although ET increased,
mean motor unit firing rates during the fatigue task did not
change significantly with training. The general motor unit
firing pattern consisted of an initial slowing followed by
an increase in firing rate late in fatigue and remained con-
sistent pre-post training. Potentiation did not change fol-
lowing training. These data suggest that the ability of the
* Lisa Griffin
l.griffin@austin.utexas.edu
1 Department of Health and Human Performance, Texas State
University, San Marcos, TX, USA
2 Department of Kinesiology and Health Education, University
of Texas at Austin, Bellmont 222, 1 University Station,
D3700, Austin, TX 78712, USA

268 Exp Brain Res (2016) 234:267–276
1 3
is also possible that altered motor unit firing rates and fir-
ing patterns contribute to delayed fatigue onset during pro-
longed submaximal force output following local muscular
endurance training (i.e., low-intensity resistance training
specifically designed to improve local muscular endur-
ance). To our knowledge, however, no study has measured
single-motor-unit firing rates and firing patterns throughout
the time-course of muscle fatigue following local muscular
endurance training. Throughout this paper, local muscular
endurance training will often be referred to as muscular
endurance training.
In untrained muscle, the typical pattern of most motor
units recruited from the onset of submaximal isometric sus-
tained fatiguing contractions consists of an early decrease
in firing rate which increases later in fatigue (Garland et al.
1997; Adam and De Luca 2005). Additionally, Vila-Chã
et al. (2012) reported a decline in motor unit firing rate
from the first 10 s of muscle contraction to the 60–70-s
time period of muscle contraction of a fatigue task in the
quadriceps muscle, with no change in the rate of decline
during this time segment following 6 weeks of cycle
ergometer endurance training performed at 50–70 % of
heart rate reserve. The present study expands on this study
by examining firing rates and the pattern of firing rate of
a single motor unit throughout the time-course of muscle
fatigue following local muscular endurance training. The
initial decline in motor unit firing rate during fatigue has
been correlated with force potentiation magnitude (Klien
et al. 2001). Because muscle fibers produce greater force
in the potentiated state, firing rates may slow to avoid an
overshoot of the target force during submaximal contrac-
tion. It is also possible that firing rates of active motor units
fire at a higher rate and are maintained over a longer dura-
tion to maintain submaximal force output with recruitment
of fewer motor units during fatigue. Our previous work
has shown that 8-week muscular endurance training leads
to greater postactivation potentiation during a submaximal
fatigue task and following maximal effort conditioning
contractions (Mettler and Griffin 2012). Endurance athletes
have greater potentiation in the trained muscles following
maximal voluntary conditioning contractions compared
to untrained individuals (Hamada et al. 2000). Therefore,
changes in force potentiation as a result of muscular endur-
ance training may alter motor unit firing patterns and act as
a mechanism to counteract muscular fatigue.
As muscle contraction is maintained, metabolites accu-
mulate that can activate Group III and IV afferents (Rotto
and Kaufman 1988) which inhibit depolarization of the
motor neuron. Ischemia, such as produced during sus-
tained muscle contraction, increases the concentration
of these metabolites in the active muscle tissue and can
inhibit cortical excitability (Taylor and Gandevia 2008),
reduce H-reflex amplitude (Garland 1991) and decrease
single-motor-unit firing rates (Bigland-Ritchie et al. 1986).
Endurance training effectively decreases the production of
metabolites (Lucia et al. 2000) and increases capillarization
and blood flow throughout the muscle to increase clearance
of metabolites produced during muscle activity (Brodal
et al. 1977; Lucia et al. 2000). Thus, muscular endurance
training may reduce the inhibition from Group III and IV
afferents to induce higher motor unit firing rates and to sus-
tain firing frequencies over a longer duration and improve
muscle endurance.
The purpose of this study was to determine single-
motor-unit firing rates and patterns of the adductor polli-
cis (AdP) muscle throughout the time-course of a sustained
submaximal fatigue task before and after 4 weeks of local
muscular endurance training. We also aimed to determine
the postactivation potentiation response to MVCs pre- can
post- 4 weeks of muscular endurance training.
Materials and methods
Participants
Fifteen healthy males (N = 7) and females (N = 8) par-
ticipated in this study. Participants were randomly assigned
to training (N = 10) and control groups (N = 5). The
training group consisted of four males and six females
(25.1 ± 1.5 years old). The control group consisted of three
males and two females (24.3 ± 1.8 years old). A control
group was included in this study to ensure a methodologi-
cally sound design. Having a larger treatment group than
control group does not present any special statistical prob-
lems for the analysis technique we used, other than the
general truth that larger sample sizes yield greater power
to detect effects that exist in the population from which
the sample was drawn. In terms of both invasiveness and
time, testing and analysis of each subject is not a trivial
task. While the inclusion of a control group strengthens
the design, there was of course no reason to suspect that
the control group would differ from the treatment group
at pretest. There was also little reason to suspect that the
control group would change significantly over time, but in
any event statistical power to detect change over time in
the same individuals tends to be high. We suspected that
a fairly minimal control group would therefore suffice. In
contrast, capturing the change that was expected to occur in
the training group was our primary concern. We considered
the possibility of individual differences in both response
to training and fidelity to the training regimen. These were
obviously no concerns for the control group. Participants
in this study were healthy, did not take medications known
to affect nervous system function, and had no history of
neurological disorder or injury to the non-dominant hand.

269Exp Brain Res (2016) 234:267–276
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Musicians and athletes with a highly trained non-dominant
hand were also excluded from the study. Participants were
instructed to abstain from caffeine consumption on experi-
mental test days. All procedures were approved by The
University of Texas at Austin Internal Review Board, and
all individuals signed informed consent forms prior to par-
ticipation in the study.
Experimental setup
Participants first attended an initial orientation session in
which they were familiarized with the experimental setup,
equipment and protocol. They also practiced performing
MVCs and holding isometric contractions. They returned
to the laboratory at least 48 h after the orientation session
for the pretraining experimental session. Participants were
seated with the non-dominant forearm supported in a splint.
The wrist was placed in a pronated position, and the thumb
was abducted and positioned against a metal strain-gauge
force transducer. To determine maximal M-wave, a pair
of pregelled, adhesive, Ag/AgCl disposable surface elec-
tromyography (EMG) electrodes (Danlee Products, Inc.,
Syracuse, NY) were placed on the palmer surface of the
hand, over the AdP muscle, and a ground surface electrode
was placed on the radial styloid process of the wrist. The
skin surface was prepped with alcohol at the intramuscu-
lar electrode insertion site and the surface electrode place-
ment sites. Intramuscular insulated stainless steel fine-wire
(0.002 mm) electrodes (California Fine Wire Company,
Grover Beach, CA) made of three fine wires were used to
record single-motor-unit data. The intramuscular electrodes
were then inserted with a thin hollow needle (25 g) just
under the skin and into the muscle belly of the AdP of the
non-dominant hand. A ground surface electrode was placed
at the unlar styloid process of the wrist. A surface stimulat-
ing electrode was secured with a strap over the unlar nerve
at the wrist. Straps at the wrist, forearm, upper arm and
shoulder secured the limb and hand position. Therapeutic
hand putty was also placed around the hand and fingers
to prevent the hand from slipping. A visual display of the
force and EMG was provided on a computer screen posi-
tioned in front of the individual.
Experimental protocol
To test postactivation potentiation, maximal M-wave
amplitude was determined by applying single-pulse (50 µs
duration) surface electrical stimulation (Digitimer DS7A,
Garden City, England) to the ulnar nerve at the wrist and
increasing the stimulation intensity until the M-wave
reached maximal amplitude and increasing the intensity
did not increase the peak to peak M-wave amplitude. All
stimulation was supramaximal (at a stimulation intensity
10 % higher than required to evoke a maximal M-wave).
After the maximal M-wave was determined, five single
twitches were evoked with single-pulse surface stimula-
tion of the ulnar nerve at the wrist. Participants then per-
formed three MVCs of the AdP muscle. Each MVC was
held approximately 3.5 s, and participants were instructed
to adduct the thumb against the metal strain-gauge bar as
fast and forcefully as possible to MVC. Verbal encourage-
ment was provided during each MVC. Immediately follow-
ing the MVCs, five maximal twitches were again evoked to
determine the potentiated twitch force.
Following a 7-min rest period, participants performed
the fatigue task which consisted of holding a 20 % MVC
isometrically until the endurance limit. Verbal encourage-
ment was provided to participants during the fatigue task.
The fatigue task force was calculated based on the largest
MVC of each respective test day. The criterion for endur-
ance time (ET) was determined post hoc and was defined as
two force fluctuations of ≥10 % MVC within a 10-s time
period. Previous single-motor-unit fatigue studies have
used a similar criterion for ET (Adam and De Luca 2005;
Garland et al. 1997; Contessa et al. 2009). The same exper-
imental protocol was utilized for the pretest and posttest.
The posttest was performed 2 days after the last training
day. The control group did not participate in any training
and performed only the pretest and posttest approximately
4 weeks apart.
Muscular endurance training
The training group trained the AdP muscle of the non-
dominant thumb every other day for 4 weeks for a total of
14 training sessions. Muscular endurance training was per-
formed using a portable, custom-designed and built thumb
training device (University of Texas Mechanical Engineer-
ing Department, Austin, TX) which isolated thumb adduc-
tion. The muscular endurance training protocol consisted
of performing three sets of seven 1-min isometric thumb
adduction contractions at 20 % MVC. Each repetition was
followed by a 5-s rest interval and each set by a 2-min rest
interval. The training protocol in this study was based on
The American College of Sports Medicine Position Stand
that states that local muscular endurance can be most effec-
tively improved by performing light resistance loads at less
than 50 % of the 1-repetition maximum and high repeti-
tions (≥15–25) (Ratamess et al. 2009; Garber et al. 2011).
Participants were provided with visual feedback of
the force they were exerting via a gauge on the training
device, which allowed them to maintain the target force
level throughout the contraction. The first and every third
training session were conducted in the laboratory under
the supervision of the experimenter to ensure that training
was performed correctly to measure MVC and to adjust

270 Exp Brain Res (2016) 234:267–276
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training load accordingly. All other training sessions were
performed at home, and participants were provided with a
training device, a hand-held stopwatch and a training log on
which to record their training sessions. Subjects reported
100 % training compliance and were able to complete each
training session.
Data analysis
Surface EMG was high-pass-filtered at 13 Hz, gain 100
(Coulbourn Instruments, Allentown, PA), and digitized at
2000 Hz [Cambridge Electronic Design (CED), Cambridge,
England]. Intramuscular EMG was preamplified, band-
pass-filtered 10 Hz–3.12 kHz with a gain of 330 (B&L
Engineering, Tustin, CA) and digitized at a sampling rate
of 20 kHz. The force signal was low-pass-filtered at 1 kHz
with a gain of 100 (World Precision Instruments, Sarasota,
FL) and digitized at a sampling rate of 1 kHz. Force and
intramuscular EMG were synchronously recorded (Fig. 1).
All data were analyzed off-line using Spike2 for Windows
(version 5) software package (CED, Cambridge, England).
Individual motor unit potentials were analyzed off-line
with the Spike2 waveform discrimination system (CED,
Cambridge, England).
Mean single-motor-unit firing frequency was meas-
ured off-line during 5-s time bins every 5 % of ET. The
first 5 % segment of the fatigue task represented the ini-
tial motor unit firing frequency, the last 5 % segment of
the fatigue task represented the final motor unit firing
frequency, and the segment with the lowest mean motor
unit firing frequency represented the minimum motor
unit firing frequency. Motor unit firing rates in absolute
time and relative to ET (every 5 % ET) were compared.
The slopes of firing rate over time during the fatigue
task were compared before and after endurance training.
Mean motor unit firing rates during the initial, mini-
mum and final time bins of the fatigue task were also
compared. During the fatigue task, a total of 31 motor
units were recorded and analyzed throughout the fatigue
task (14 pretraining and 17 posttraining). All interspike
intervals (ISIs) ≤20 and ≥200 ms were excluded from
analysis because they result in false-positive and false-
negative ISIs, respectively, and, therefore, alter mean
firing rate (Garland et al. 1994). Approximately 5 %
of the identified action potentials were excluded from
analysis.
The mean peak twitch force from the five single pulses
measured before the three MVCs served as the control
twitch force. The mean peak twitch force from the five sin-
gle pulses after the MVCs served as the potentiated twitch
force. Each participant’s ET and MVC are expressed as a
percent change pre- and post-test.
Statistical analysis
A between–within general linear mixed model (GLMM)
with group (training and control), training (pre and post)
and fatigue time (initial, minimum and final) as the inde-
pendent variables was used to test motor unit firing rate
changes with training. A GLMM with group × training as
the independent factors was also used to test pre- and post-
training changes in time to minimum motor unit firing rate
Fig. 1 Representative force
(top trace) and intramuscular
EMG (bottom trace) record-
ings from the adductor pollicis
muscle during the 20 % MVC
sustained isometric fatigue
task. The intramuscular EMG
recording depicts two single
motor units that were following
throughout the course of the
fatigue task

271Exp Brain Res (2016) 234:267–276
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and training-related differences in overall mean motor unit
firing rates at relative and absolute times during the fatigue
task. The slopes of the motor unit firing rate changes at rel-
ative and absolute times from the start of the fatigue task
were compared using a group × training × fatigue time
GLMM.
Two-way repeated measures ANOVA with
group × training as the independent factors was used to test
pre-post training differences in ET and MVC. Postactiva-
tion potentiation was compared using a three-way repeated
measures ANOVA with twitch force (control and potenti-
ated), training and group as the independent factors. Bon-
ferroni corrections were used for post hoc analysis of mul-
tiple comparisons. An alpha level p ≤ 0.05 was accepted as
the level of statistical significance for all tests. All data are
reported as mean ± standard error.
Results
Endurance time
There were a significant main effect for training
(p < 0.001) and a significant group × training interaction
(p = 0.030) for ET. Post hoc comparisons revealed that
muscular endurance training resulted in a 45.2 ± 8.7 %
(p < 0.001) (9.5 ± 1.7 and 13.8 ± 2.8 min, pre- and
posttraining, respectively) increase in ET of the fatigue
task for the training group and no significant change
in ET for the control group (12.6 ± 6.8 %; p = 0.27)
(12.0 ± 2.3 vs. 13.6 ± 2.8 min, pre- and posttraining,
respectively).
Maximal voluntary contraction
There was a significant training main effect (p = 0.05)
for an increase in MVC following training. There was
no difference between groups (p = 0.09), and the train-
ing × group interaction (p = 0.22) was not significant for
MVC (training group: 78.0 ± 10.7 vs. 91.3 ± 13.1 N; con-
trol group: 50.4 ± 6.6 vs. 53.9 ± 7.5 N, pre- and posttrain-
ing, respectively).
Postactivation potentiation
There was a significant main effect for potentiation (con-
trol vs. potentiated twitch force) (p < 0.001) which showed
that twitch force increased significantly following the
three 3.5-s MVCs. Compared to the control twitch force,
the average potentiated twitch force increased by 3.9 N
and 4.2 N pre- and posttraining, respectively, for the train-
ing group, and by 2.7 N and 2.9 N pre- and posttraining,
respectively, for the control group. Data are displayed in
Fig. 2. The main effect for training and the interactions
were not significant.
Motor unit firing patterns
Thirty-one motor units were recorded throughout the course
of the fatigue task. In the training group, nine motor units
from eight subjects (one motor unit for seven subjects; two
motor units for one subject) were analyzed pretraining and
12 motor units from 10 subjects (one motor unit for eight
subjects; two motor units for two subjects) were analyzed
0
2
4
6
8
10
12
14
16
PrePostPre Post
Control GroupTraining Group
Twitch Force (N)
Control Twitch
Potentiated Twitch
****
Fig. 2 Mean control and potentiated twitch forces. *Potentiated
twitch force is significantly greater than the control twitch force
(p < 0.001)
Fig. 3 Mean initial, minimum and final motor unit firing rates for
motor units analyzed throughout the fatigue task. *Significantly lower
motor unit firing rate than initial. †Significantly lower motor unit fir-
ing rate than final. The bracket indicates main effect

272 Exp Brain Res (2016) 234:267–276
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posttraining. In the control group, five motor units from
four subjects (one motor unit for three subjects; two motor
units for one subject) were analyzed pretraining and five
motor units from four subjects (one motor unit for three
subjects; two motor units for one subject) were analyzed
posttraining from four subjects. At least one motor unit for
at least one test was recorded for all subjects included in
the data analysis. Mean motor unit firing rate patterns did
not change with muscular endurance training. Motor unit
firing rates during the initial, minimum and final sections of
the fatigue task were compared, and there was a significant
main effect for fatigue time (p < 0.001). Post hoc results
show that initial motor unit firing rates were significantly
higher than minimum firing rates (p < 0.001) and final fir-
ing rates (p < 0.001) and that final firing rates were higher
than minimum firing rates (p < 0.001) (Fig. 3). There was
no significant main effect for training (p = 0.245) or group
(p = 0.106), and no significant interactions.
Although the time from the start of the fatigue task to
the point in the fatigue task where minimum motor unit
firing rate occurred increased; the main effect for training
and the training × group interaction were not statistically
significant (Fig. 4). Additionally, the group × training and
group × training × fatigue time interactions were not sig-
nificantly different when mean motor unit firing rate of the
5-s time bins was compared at points relative to ET (Fig. 5)
or when compared at absolute times (Fig. 6) during the
fatigue task indicating no change in mean motor unit firing
rate and no change in the slope of motor unit firing behav-
ior, respectively, throughout the fatigue task (p > 0.05).
Individual motor unit firing rate patterns during the fatigue
task are displayed in Fig. 7. Additionally, newly recruited
motor units were observed in some subjects during the
fatigue task; however, they were not quantified or ana-
lyzed as the purpose of the present study was to examine
a specific motor unit from the onset of muscle contraction
throughout the time-course of muscle fatigue.
Discussion
To our knowledge, this is the first study to examine motor
unit firing rates and the pattern in which the firing rate of a
single motor unit changes throughout the course of a sus-
tained submaximal voluntary fatigue task before and after
local muscular endurance training. Although ET increased,
we found that the pattern of single-motor-unit firing rate
activity during the fatigue task did not change with mus-
cular endurance training. The general pattern of motor unit
02468
Group
Control Training
Time to Minimum Firing Rate (M in)
Pre-Training
Post-Training
Fig. 4 Mean time at which minimum motor unit firing rates occurred
during the fatigue task. There was no significant difference pre-post
training
6
9
12
15
18
21
% Endurance Time
Motor Unit Firing Rate (Hz)
025507
51
00
6
9
12
15
18
21
% Endurance Time
Motor Unit Firing Rate (Hz
)
Pre-Training
Post-Training
025507
51
00
Pre-Training
Post-Training
(a)
(b)
Fig. 5 Mean motor unit firing rate averaged over 5-s bins every 5 %
endurance time (20 time bins) pre- and posttraining. Each data point
is the mean of all motor units analyzed. Training group: pretraining
12 motor units, posttraining nine motor units; control group: pretrain-
ing five motor units, posttraining five motor units. a Training group
and b control group. There was no significant change between the
pre- and post-tests (p = 0.09)

273Exp Brain Res (2016) 234:267–276
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firing observed in the present study during a submaximal
fatiguing contraction is consistent with our previous work
(Garland et al. 1997; Griffin et al. 2000) and the work of
others (Garland et al. 1994; Adam and De Luca 2005) in
untrained individuals, whereby most initially recruited
motor units display an initial decrease in firing rate and an
increase late in fatigue. Our data are also in agreement with
a cycle ergometer training study in which motor unit firing
rates were lower during the 60–70-s time period of contrac-
tion compared to the first 10 s of the 30 % MVC with no
training-related change (Vila-Chã et al. 2012). This decline
in motor unit firing rate during fatigue has been attributed
to the muscle wisdom hypothesis (Marsden et al. 1983),
twitch force potentiation (Klien et al. 2001), decreased
central drive (Gandevia 2001; Taylor and Gandevia 2008),
motor neuron adaptation (Kernell and Monster 1982),
decrease in Ia afferent excitatory input to the motor neuron
(Macefield et al. 1991) and inhibition from Group III and
IV afferents (Bigland-Ritchie et al. 1986; Garland 1991).
The late increase in motor unit firing rate may be due to
increased central drive and increased Ia afferent activity
late in fatigue (Ljubisavlijecvic and Anastasijevic 1994). In
the present study, this pattern was also maintained pre-post
0
5
10
15
20
25
30
35
0500 1000 1500 2000
Motor Unit Firing Rat e (Hz)
Absolute Time (s)
Pre-Training
0
5
10
15
20
25
30
35
0500 1000 1500 2000
Motor Unit Firing Rate (Hz)
Absolute Time (s)
Pre-Training
(a)
(b)
Fig. 6 Motor unit firing rates in absolute time from the onset of the
fatigue task for the training group. Each data point represents the
mean firing rate over a 5-s time bin during the fatigue task. To dem-
onstrate the mean motor unit firing rate and slope of the change in
firing rate pattern throughout the course of fatigue, the data were fit
with a second-order polynomial trendline. a Pretraining firing rates:
y = 8E − 06x2 − 0.0087x + 15.061; R2 = 0.0442, and b posttrain-
ing firing rates: y = 2E − 06x2 − 0.0045x + 15.662; R2 = 0.0245.
There were no significant changes in mean motor unit firing rate or
the slope of the curve pre-post training
Fig. 7 Individual single-motor-unit data are displayed during the
time-course of muscle fatigue relative to endurance time. To demon-
strate the individual single-motor-unit firing rate pattern throughout
the course of fatigue, the mean motor unit firing rate of each motor
unit during the 5-s time bins was fit with a second-order polynomial
trendline. Motor units are numbered, with each number representing
a specific subject a pretraining and b posttraining

274 Exp Brain Res (2016) 234:267–276
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muscular endurance training and, therefore, may serve as
the optimal central nervous system (CNS) strategy to post-
pone fatigue during sustained muscular activity.
The mean firing rate at the onset of contraction, at the
end of the fatigue task, and the lowest firing frequency
during the fatigue task did not change with training. Addi-
tionally, mean motor unit firing rates did not change with
training when compared at points relative to ET or when
compared in absolute time from the onset of muscle con-
traction. Yet, because muscular ET increased significantly
with training, the CNS was able to sustain similar firing
rates of a single motor unit over a longer period of time in
the endurance-trained state compared to the untrained state.
Several neural and metabolic adaptations that occur in
response to endurance training may have contributed to
the maintenance of pretraining firing rates over the course
of a longer posttraining fatigue task and thus contribute to
the enhanced muscular endurance. Group III and IV small
diameter afferents likely inhibit cortical motoneurons (Tay-
lor and Gandevia 2008), and increased activation of Group
III and IV afferents occurs in response to the accumula-
tion of metabolites produced during prolonged contractile
activity (Mense and Stahnke 1983; Rotto and Kaufman
1988). Trained individuals, however, deplete muscle glyco-
gen stores more slowly than untrained individuals and in
so doing may delay and/or reduce lactate production (Her-
mansen et al. 1967) which may reduce motor unit inhibi-
tion to allow the neuromuscular system to sustain a given
motor unit firing frequency over a longer duration of sub-
maximal muscle contraction.
During sustained MVC, motor unit firing rates have
been found to continue to decline under ischemic condi-
tions until blood flow was re-established (Woods et al.
1987). Motor unit firing rates, however, are maintained
during dynamic fatiguing submaximal contractions (Miller
et al. 1996; Griffin et al. 1998), perhaps due to greater
blood flow during dynamic contractions which increases
metabolite removal from the muscle. Aerobic endurance
training (running) produces adaptations such as a reduc-
tion in metabolite production (Lucia et al. 2000), increased
capillarization and increased blood flow to the muscle
to aid in the clearance of metabolic byproducts (Brodal
et al. 1977; Lucia et al. 2000). Indeed, increased blood
flow and decreased metabolite production may decrease
Group III and IV afferent inhibition to the motor neuron
pool in the muscle trained for local muscular endurance
and allow for prolonged maintenance of motor unit firing
rate. In the present study, these physiological adaptations
may explain why the neuromuscular system sustains pre-
training firing frequencies over a longer period of time after
training to defer muscle fatigue. Furthermore, a trend was
observed where the minimum firing rate occurred later in
the fatiguing contraction after training, also suggesting that
higher firing rates were maintained over a longer duration
in the endurance-trained muscle.
Central fatigue may also play a role in the performance
of submaximal sustained contractions as excitability of the
motor neuron has been found to decrease during submaxi-
mal fatiguing contractions (McNeil et al. 2011). Motor unit
firing rates decrease as pain increases (Farina et al. 2004) in
part due to stimulation of Group III and IV afferents which
inhibit motor unit activation. Additionally, rating of per-
ceived effort during a sustained 15 % MVC increased by
almost four times during the course of a 40-min contraction
(Sogaard et al. 2006). It is possible that perception of effort
is reduced after muscular endurance training. Increases in
central drive may allow for firing rate to be maintained over
a longer duration, thereby sustaining force longer follow-
ing muscular endurance training. Further, we have previ-
ously found that cortical excitability increases with short-
term resistance training (Griffin and Cafarelli 2007) and
the excitability of the spinal cord (H/M ratio) is greater
in endurance-trained compared to sedentary individuals
(Rochcongar et al. 1979; Maffiuletti et al. 2001). These
factors may also allow for more efficient neural activation
to assist in sustaining motor unit firing rates longer. Our
data support previous findings that mean motor unit firing
rate did not change following 6 weeks of cycle ergometer
endurance training during unfatigued, 10-s contractions at
10 % MVC (Vila-Cha et al. 2010), but are in contrast to
the same study that reported lower motor unit firing rates
during an unfatigued, 10-s contraction performed at 30 %
MVC after 6 weeks of cycle ergometer endurance training
(Vila-Cha et al. 2010). Differences in training mode and the
short duration of muscular activity may account for the dis-
crepancy between results observed in the present study and
those of Vila-Cha et al. (2010).
We did not find a muscular endurance training-related
change in twitch force potentiation magnitude when MVCs
were used as conditioning contractions. Our previous work
shows that 8 weeks of similar muscular endurance training
in the AdP muscle increased maximal muscle twitch force
potentiation following MVC and during a submaximal
fatiguing contraction (Mettler and Griffin 2012). Endur-
ance athletes have also been found to have greater potentia-
tion in the trained muscles compared to untrained individu-
als (Hamada et al. 2000). It is, however, likely that 4-week
training was not long enough to induce significant changes
in potentiation. Additionally, we did not evoke electrically
induced contractions to test twitch force potentiation dur-
ing the fatigue task in the present study as that may have
altered motor unit behavior, and therefore, it is not clear
whether potentiation influenced motor unit firing rates dur-
ing the submaximal fatigue task.

275Exp Brain Res (2016) 234:267–276
1 3
Study limitations
Results obtained in the predominately slow twitch AdP
muscle may not generalize to all muscles, and future
study is needed to examine muscular endurance training
responses during a fatiguing contraction in larger muscles
of the lower and upper extremities and in muscles of differ-
ent fiber type composition. Also, although a small sample
of single motor units was followed throughout the fatigue
task, the sample size in the present study is consistent with
previous studies in which the same motor unit was fol-
lowed throughout the entire course of the fatigue task (Gar-
land et al. 1997; Adam and De Luca 2005). These studies
followed seven motor units (Garland et al. 1997) and eight
motor units (Adam and De Luca 2005) that were followed
during the entire fatigue task. In addition, an inherent limi-
tation to single motor unit recording using intramuscular
EMG is that it is not possible to ensure that the same motor
unit is recorded during different experimental sessions. The
firing rates of motor units vary within a given motor pool.
It is therefore possible that the firing rate of motor units
recorded during pretraining may have changed with train-
ing; however, since different motor units were recorded
posttraining, these physiological changes may have been
obscured. Similarly, motor unit firing rates vary across sub-
jects, and motor units from several subjects were pooled in
this study which also may have potentially obscured train-
ing-related changes in motor unit firing patterns. Addition-
ally, a control group was included in this study to ensure a
methodologically sound design. Although the control group
was smaller than the training group, having a larger treat-
ment group than control group does not present any spe-
cial statistical problems for the analysis technique we used,
other than the general truth that larger sample sizes yield
greater power to detect effects that exist in the population
from which the sample was drawn.
Postfatigue MVCs and postfatigue twitch forces may
have provided physiological information to assist with
interpretation of the motor unit data. During pilot testing,
however, we determined that it would not be technically
feasible to obtain postfatigue twitch forces due to diffi-
culty in maintaining electrode placement during the fatigue
task and this would be necessary in order to elicit maximal
twitch force immediately postfatigue task. In addition, sub-
jects reported pain at the wrist from the pressure of secur-
ing the stimulating electrode during the fatigue task. Motor
units are inhibited by pain, and we did not want to compro-
mise the motor unit data; therefore, we elected to forfeit the
postfatigue twitch data. Postfatigue MVCs were performed;
however, because the fatigue criterion was determined post
hoc, the postfatigue MVCs were not reported as they did
not provide meaningful information regarding the degree
of muscle fatigue. Motor unit recruitment thresholds were
not measured in the present study. It is possible that altered
recruitment threshold may have contributed to prolonged
muscular endurance and future research is warranted to
investigate recruitment threshold changes with muscular
endurance training.
In conclusion, we found that 4 weeks of local muscu-
lar endurance training resulted in increased local muscular
endurance. The mean motor unit firing rates of a sustained
submaximal fatigue task did not change with 4 weeks of
muscular endurance training. ET significantly increased
posttraining; therefore, mean firing rates were sustained
longer, and the pattern of single-motor-unit firing rate
changes during the course of muscle fatigue occurred over
a longer duration in the trained muscle. These findings sug-
gest that preservation of firing rates during the course of
sustained submaximal muscle contraction may be a mecha-
nism that contributes to increased muscular endurance and
delayed fatigue onset following short-term local muscular
endurance training.
Acknowledgments The authors would like to thank statistician,
Michael Mahometa, Ph.D., for consulting on the statistical analyses
and Brian Huynh for his time working on this project. We would also
like to thank all of the study participants for their time and dedication
to this project.
Author contributions Joni A. Mettler involved in experimental
design, training protocol design, data acquisition and analysis, inter-
pretation of data and writing of manuscript. Lisa Griffin involved in
conception, experimental design, interpretation of data and editing of
manuscript.
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