Jacques Duchateau, John G. Semmler and Roger M. Enoka
J Appl Physiol 101:1766-1775, 2006. First published Jun 22, 2006; doi:10.1152/japplphysiol.00543.2006
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Postactivation potentiation in a human muscle: effect on the rate of torque development of
tetanic and voluntary isometric contractions
S. Baudry and J. Duchateau
J Appl Physiol, April 1, 2007; 102 (4): 1394-1401.
[Abstract] [Full Text] [PDF]
J Appl Physiol 101: 1766 –1775, 2006;
doi:10.1152/japplphysiol.00543.2006.
Invited Review
HIGHLIGHTED TOPIC
Neural Changes Associated with Training
Training adaptations in the behavior of human motor units
Jacques Duchateau,1 John G. Semmler,2 and Roger M. Enoka3
1
Laboratory of Applied Biology, Université Libre de Bruxelles, Brussels, Belgium; 2Discipline of Physiology and Research
Centre for Human Movement Control, School of Molecular and Biomedical Science, University of Adelaide, Adelaide,
Australia; and 3Department of Integrative Physiology, University of Colorado, Boulder, Colorado
electromyogram; discharge rate; recruitment; motor unit synchronization; steadiness
(124), the motor unit is the common
final pathway of the motor system and comprises a motor
neuron in the ventral horn of the spinal cord, its axon, and the
muscle fibers that the axon innervates. The average number of
fibers innervated by a motor neuron is ⬃300, but the range
extends from tens to thousands (37). The basic function of a
motor unit is to transform synaptic input received by the motor
neuron into mechanical output by the muscle (57).
The group of motor neurons in the spinal cord innervating a
single muscle is referred to as a motor unit pool (15). The
motor unit population that forms a motor pool is heterogeneous
with respect to the properties of both the motor neurons and the
muscle fibers that they innervate (13). A motor neuron can be
characterized by its morphology, excitability, and distribution
of input (12, 13, 69), whereas muscle fibers vary in contraction speed, force-generating capacity, and resistance to fatigue
(14, 70).
Although the distribution of synaptic inputs can influence
the order in which motor units are recruited, the most
important determinant is the size of the motor neuron. As
AS DEFINED BY SHERRINGTON
Address for reprint requests and other correspondence: J. Duchateau, Laboratory of Applied Biology, Université Libre de Bruxelles, 28 Ave., P. Héger
CP 168, 1000 Brussels, Belgium (e-mail: jduchat@ulb.ac.be).
1766
initially reported by Henneman (59), there is a strong
relation between the size of a motor neuron and the order in
which it is activated. This association has become known as
the size principle. The influence of size on recruitment order
is attributable to its effect on input resistance. According to
Ohm’s law, the change in membrane potential in response to
a synaptic current is proportional to the input resistance of
the motor neuron. Because small motor neurons have a high
input resistance, they are the first to be recruited in response
to an increase in depolarizing synaptic currents. As a consequence of this relation, smaller motor units tend to be
activated before larger units. Due to the properties of the
muscle fibers innervated by the different motor neurons, this
recruitment sequence results in slow-contracting and fatigue-resistant motor units being recruited before fast-contracting and fatigable motor units. Although there is some
variability in the recruitment order of motor units with
similar thresholds (44, 135), the recruitment order of motor
units is essentially the same for isometric and dynamic
contractions, including shortening and lengthening contractions (122, 126, 131), and during rapid (ballistic) isometric
(33, 34) and shortening (60) contractions. Furthermore,
recruitment order during the stretch reflex follows the size
principle (17).
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Duchateau, Jacques, John G. Semmler, and Roger M. Enoka. Training
adaptations in the behavior of human motor units. J Appl Physiol 101: 1766 –1775,
2006. doi:10.1152/japplphysiol.00543.2006.—The purpose of this brief review is to
examine the neural adaptations associated with training, by focusing on the
behavior of single motor units. The review synthesizes current understanding on
motor unit recruitment and rate coding during voluntary contractions, briefly
describes the techniques used to record motor unit activity, and then evaluates the
adaptations that have been observed in motor unit activity during maximal and
submaximal contractions. Relatively few studies have directly compared motor unit
behavior before and after training. Although some studies suggest that the voluntary
activation of muscle can increase slightly with strength training, it is not known
how the discharge of motor units changes to produce this increase in activation. The
evidence indicates that the increase is not attributable to changes in motor unit
synchronization. It has been demonstrated, however, that training can increase both
the rate of torque development and the discharge rate of motor units. Furthermore,
both strength training and practice of a force-matching task can evoke adaptations
in the discharge characteristics of motor units. Because the variability in discharge
rate has a significant influence on the fluctuations in force during submaximal
contractions, the changes produced with training can influence motor performance
during activities of daily living. Little is known, however, about the relative
contributions of the descending drive, afferent feedback, spinal circuitry, and motor
neuron properties to the observed adaptations in motor unit activity.
Invited Review
MOTOR UNIT ADAPTATIONS
MOTOR UNIT RECRUITMENT AND RATE CODING
Fig. 1. The reduction in recruitment threshold (means ⫾ SD for 10 trials) for
three motor units (MU) in tibialis anterior with an increase in the mean rate of
torque development by the dorsiflexor muscles. Inset: six different rates of
increase in torque to the target force of 120 N [⬃50% maximal voluntary
contraction (MVC)], with the most rapid contraction (0.15 s to peak force)
indicated by the arrow. The thresholds decreased for rates ⬎60 N/s and
become zero for the most rapid contraction. Note that the decrease in recruitment threshold was greatest for unit with the highest recruitment threshold, but
there was no change in recruitment order predicted by the size principle.
[Adapted from Desmedt and Godaux (33).]
J Appl Physiol • VOL
ability to perform fast contractions. Furthermore, recruitment
thresholds can be lower during dynamic contractions compared
with isometric contractions (133) and at short muscle lengths
compared with long lengths during isometric contractions (98).
Although the rate at which a motor neuron discharges action
potentials increases linearly with the depolarizing current it
receives (68, 114), there is a sigmoidal relation between discharge rate and muscle force (40, 83, 90, 92). The minimal rate
at which most motor neurons discharge action potentials repetitively during voluntary contractions is 5– 8 pulses per
second (pps) (126, 141), but the maximal discharge rates vary
across muscles. Average rates of 30 –50 pps have been recorded for most muscles during isometric contractions (for a
review, see Ref. 37), whereas rates of ⬃10 pps have been
recorded for the slow-contracting soleus muscle (11). Instantaneous discharge frequencies during rapid contractions, however, can reach values of 100 –200 pps (33, 139, 140).
The maximal discharge rate usually matches the fiber-type
composition of the muscle with muscles that contain a high
percentage of slow fibers displaying lower maximal rates (6).
The general slope of the relation between discharge rate and
muscle force has been reported to vary as a function of
recruitment threshold of the motor unit in some studies (45,
90), but not in others (89). There is also no consensus on the
relative distributions of minimal and maximal discharge rates
across the motor unit population. Some studies found that the
minimal rate was constant (90) or decreased with recruitment
threshold (132), whereas others suggested that the minimal rate
increased with recruitment threshold (40, 52, 92). Similarly,
some studies found a negative correlation between peak discharge rate and recruitment threshold during ramp isometric
contractions (32, 36), whereas a recent study reported that peak
discharge rate increased with recruitment threshold when subjects performed discrete isometric contractions at various target
forces (92). One potential explanation for the difference in the
association between recruitment threshold and peak discharge
rate between studies might be that a continuous ramp contraction and a series of brief contractions evoke different historydependent effects, such as those that involve persistent inward
currents (50, 58).
In addition to depending on mean discharge rate, muscle
force is influenced by the variability and modulation of motor
unit discharge. The coefficient of variation for discharge rate,
which is a measure of relative discharge rate variability and a
factor that has a significant effect on the force fluctuations
during steady contractions (39, 74, 134), appears to decline
exponentially with an increase in muscle force above the
recruitment threshold of each motor unit in a hand muscle (92).
Additionally, the trains of action potentials discharged by each
motor neuron can also be modulated in distinct frequency
bands (30, 42, 138), and the amount of modulation appears to
vary across subjects and tasks (62, 118, 119, 121).
MEASURING MOTOR UNIT ACTIVITY
Surface electromyography (EMG) records the action potentials generated by active motor units as detected by electrodes
placed on the skin over the muscle (41). EMG is often used,
therefore, to estimate the motor output from the spinal cord
during various types of contractions. However, the surface
EMG is insensitive to modest changes in motor unit activity.
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The force that a muscle exerts depends on the amount of
motor unit activity (3), changing with the number of motor
units that are active (motor unit recruitment) and the rates at
which motor neurons discharge action potentials (rate coding).
The relative contributions of recruitment and rate coding to the
force exerted by a muscle vary with the level of muscle force
and the muscle performing the contraction. Due to the exponential distribution of recruitment thresholds within a motor
unit pool, most motor units have low recruitment thresholds,
and, therefore, low forces are mainly produced by the recruitment of motor units. In most muscles, the upper limit of motor
unit recruitment is ⬃85% of the maximal force (32, 75, 141).
In some hand muscles, however, the upper limit of motor unit
recruitment is ⬃60% of maximum (32, 36, 89, 92). The
increase in muscle force beyond the upper limit of motor unit
recruitment is accomplished entirely by rate coding.
The absolute force at which a motor unit is recruited is not
fixed and varies with the speed and type of muscle contraction.
For example, the recruitment thresholds of motor units in the
tibialis anterior decrease progressively with an increase in the
rate of force development (Fig. 1; Ref. 33). As a consequence
of this adjustment, motor units are activated earlier during
rapid contractions, and approximately three times as many
motor units are recruited to produce a given peak force during
a rapid contraction compared with a slow-ramp contraction
(33). Due to this effect, most motor units are likely to be
recruited when performing a rapid contraction with a load
equivalent to 33% of maximum. The extent of the reduction in
recruitment threshold, however, is greater for units in slowcontracting muscles (e.g., soleus) compared with fast-contracting muscles (e.g., masseter) (34). The greater reduction in
recruitment thresholds for slow muscle likely facilitates their
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MOTOR UNIT ADAPTATIONS
MAXIMAL CONTRACTIONS
The strength of a muscle is often estimated as the peak force
achieved during a maximal voluntary contraction (MVC).
Changes in MVC force are attributable to adaptations in the
force capacity of the muscle fibers and the activation characteristics of the involved motor units. A common approach used
to identify the neural mechanisms that contribute to changes in
MVC force is to assess the maximality of a contraction. When
an individual is unable to activate a muscle or a group of
muscles maximally (4), training-induced increases in MVC
force could involve improvements in motor unit activation.
Different methods have been used to estimate the maximal
activation of the motor unit pool: surface EMG (2, 54, 91),
interpolated twitch (5, 72), and the ratio of evoked tetanic force
to MVC force (28, 35). The results obtained with these different methods provide mixed information on the potential conJ Appl Physiol • VOL
tributions of changes in motor unit activity to gains in MVC
force.
At the whole muscle level, the classic approach is to record
changes in average EMG activity during a maximal contraction. For example, it has been found that the EMG during an
MVC often increases after a program of strength training (2,
54, 91). This result has not been consistent, however, as some
studies have not found that EMG increases with MVC force
(18), even when the EMG was normalized to the maximal M
wave (64). These mixed results are not particularly surprising,
given what is known about the influence of amplitude cancellation on estimates of EMG amplitude.
An alternative approach is to compare the force exerted
during an MVC with the force that can be elicited artificially
with electrical stimulation (10, 86). The stimulus can be either
applied during an MVC to determine whether the voluntary
force can be increased or delivered to a resting muscle so that
the evoked tetanic force can be compared with the voluntary
force. Most individuals are able to achieve full activation of the
biceps brachii muscle in about one out of four attempts when
a few stimuli are superimposed during static and concentric
MVCs (4, 48). This conclusion has been confirmed with the
application of transcranial magnetic stimulation (TMS) during
an MVC (136). In contrast, many individuals exhibit submaximal activation during an MVC when the superimposed stimulus involves a brief train of shocks (67, 130). Furthermore,
muscle activation appears to be markedly less than maximal
during eccentric contractions (5, 102, 142).
Because activation seems to be near maximal when assessed
with the twitch superimposition technique, there are minimal
changes after strength training when the activation of the motor
unit pool is estimated with this technique (55, 72). In contrast,
Duchateau and Hainaut (35) observed an increase in the ratio
of MVC force to tetanic force for the adductor pollicis muscle
before and after 6 wk of strength training. The training involved voluntary contractions and loads that were ⬃65% of
maximum. The greater increase in MVC force (22%) compared with tetanic force (15%) suggests that the training
produced an adaptation that resulted in a 7% increase in the
activation of the motor unit pool for the hand muscle.
Although a decrease in the deficit detected with the interpolated twitch and an increase in the ratio of tetanic and MVC
forces indicate that muscle activation is enhanced after strength
training, the source of the improvement could be anywhere
from the motor command to the processes involved in neuromuscular propagation. Identifying the locus of the adaptation is
difficult. For example, a change in the ratio between tetanic
force and MVC force could be produced by a change in the
contribution of synergist muscles, such as those required for
postural stabilization (77), which are activated during voluntary contractions but not evoked contractions. Furthermore,
these techniques cannot distinguish between contributions
from recruitment and rate coding to increases in MVC force.
For example, what does an increase in voluntary activation
from 90 to 98% of maximum indicate about the activation of
the motor unit pool? Because the upper limit of motor unit
recruitment is ⬃85% MVC (32, 75, 141), increases in force
above this level can only be achieved with adaptations in
discharge rate and not by an increase in recruitment. However,
Pucci et al. (105) reported that strength training increased
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For example, Mottram et al. (94) showed that, although the
surface EMG of the biceps brachii increased at a comparable
rate during two types of fatiguing contractions, there were
significant differences between the two tasks in the decrease in
discharge rate and increase in recruitment of single motor
units.
The limitations of surface EMG recordings have been recognized for several decades. The magnitude of the difficulty in
interpreting surface EMG records has recently been underscored with results on the extent to which the signal underestimates the amount of motor unit activity due to signal cancellation from the overlap of the positive and negative phases of
motor unit potentials (29, 65). Although amplitude cancellation
does not increase linearly across excitation levels (65), the
increase is monotonic, and normalization of the surface EMG
amplitude to the value obtained with maximal activation provides a reasonable estimate of the amount of muscle activation.
Importantly, these results underscore the need to normalize
EMG recordings across muscles, between subjects, and between days.
The preferred method to study motor unit behavior, however, is to use an electrode that can record the discharge of
identifiable single motor units, because this provides information on the discharge characteristics of motor neurons in the
spinal cord due to the faithful transmission of each neuronal
action potential to the muscle fibers. Several electrodes have
been developed for this purpose: fine-wire electrode (89),
concentric needle electrode (129), subcutaneous electrode (38),
arrays of electrodes distributed over the surface of the muscle
(85), and macro-EMG (128). Each technique has its advantages
and limitations (for review, see Ref. 84). The most common
method is to use a fine-wire electrode. The procedure consists
of inserting wires (diameter: 10 –50 m), which are insulated
except for the ends, into the muscle with a hypodermic needle.
The ends of the wires serve as the detection surface to record
the action potentials of single motor units. Because it is often
difficult to discriminate the action potentials of single motor
units at high forces, an alternative approach is to use a concentric needle electrode to record the activity of several motor
units and then use a signal-processing algorithm to decompose
the composite signal into the constituent single motor unit
potentials (78, 84).
Invited Review
MOTOR UNIT ADAPTATIONS
voluntary activation from 96 to 98%, but there was no change
in discharge rate as measured with multiunit recordings.
Single Motor Unit Recording
30 – 40% of maximum (Fig. 3). Both the rate of increase in
torque and the associated EMG during submaximal dynamic
contractions increased with training. To assess the contribution
of motor unit discharge rate to the faster rate of increase in
torque for the submaximal dynamic contractions, the instantaneous rate for the first four action potentials was determined in
single motor units before and after training. Although no
change was observed in the recruitment order of motor units,
the average instantaneous discharge rate increased from 69 to
96 pps with training. Furthermore, training caused a significant
increase in the number of motor units (from 5 to 33%) that
discharged with brief interspike intervals (⬍5 ms). Thus the
increase in the rate of force development during rapid contractions appears to have been achieved by an adaptation in motor
unit discharge rate.
Motor Unit Synchronization
Since the classic observation of Milner-Brown et al. (88)
that the synchronization of motor unit discharge is greater in a
strength-trained hand muscle, it has frequently been assumed
that strength gains can involve an increase in motor unit
synchronization. However, this study was based on an indirect
assessment of synchronization obtained from the surface EMG,
which is now known to contain several limitations (146).
Nonetheless, the cross-correlation of discharge times from
pairs of motor units, which represents the gold standard to
quantify motor unit synchronization during voluntary contractions in humans, has indicated that the amount of motor unit
synchronization can vary with contraction type (122) and the
type of habitual physical activity performed by an individual
(118, 121, 122). However, a recent study found that significant
strength gains after 4 wk of training were not accompanied by
increases in synchronization between pairs of concurrently
active motor units in the first dorsal interosseus muscle (120).
These experimental data are consistent with a simulation study
that suggested motor unit synchronization does not influence
the maximal force that can be produced by a muscle (145). The
central mechanisms that influence the correlated discharge of
motor units and its expression as short-term synchronization
appear to be unrelated to the activation characteristics that
influence the force capacity of a muscle.
Coordination Between Muscles
Fig. 2. Changes in strength (MVC force) of the quadriceps femoris muscles
(A) and the discharge rate of MUs in vastus lateralis (B) for young (E) and old
(F) adults during a 6-wk training program. The measurements at days 1 and 8
represent baseline measurements. The discharge rates were recorded during
submaximal (10 and 50%) and maximal (100%) isometric contractions. pps,
Pulses per second. [Adapted from Kamen and Knight (63).]
J Appl Physiol • VOL
Another possible adaptation in the activation of the motor
unit pool with training is the distribution of activation among
the muscles involved in the task (8, 123). A frequently examined example of this effect is coactivation of agonist and
antagonist muscles (7, 31, 80, 104). Coactivation increases
joint stability and stiffness and varies with factors such as the
intensity and type of the contraction, movement speed, the
amount of fatigue, and the level of training (for review, see
Ref. 66). Alterations in coactivation with training may be
related to a change in the ability to focus the motor command
to the appropriate muscles involved in the task, through the
differential modulation of intracortical inhibition (148). Because coactivation reduces the net force produced by the
agonist muscles, the level of coactivation has to be adjusted by
the nervous system when it impedes the performance of the
agonist muscles. For example, elite athletes exhibit reduced
coactivation of the semitendinosus muscle compared with
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Although it is a relatively trivial matter to record the activity
of a single motor unit during a voluntary contraction, assessing
the effect of a chronic intervention is much more challenging.
In addition to the technical difficulties of identifying the
activity of single motor units, the comparison of motor unit
function before and after an intervention requires a sufficient
sample size to represent the population of motor units and an
adequate number of measurements to characterize the behavior. As a consequence, few studies have compared motor unit
behavior before and after strength training.
Kamen and Knight (63) reported that a 33% increase in the
MVC force for the knee extensor muscles after 6 wk of
strength training was accompanied by increases in the maximal
discharge rates of motor units in the vastus lateralis of young
(15% increase) and old (49% increase) adults (Fig. 2). Similarly, Van Cutsem et al. (140) compared the average instantaneous discharge rate of motor units at the beginning of a rapid
contraction in the tibialis anterior before and after 12 wk of
dynamic training. The training consisted of rapid contractions
with the dorsiflexor muscles against a load that represented
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MOTOR UNIT ADAPTATIONS
sedentary subjects when performing isokinetic contractions
with the knee extensor muscles (5), and strength gains can be
accompanied by a reduction in coactivation of the antagonist
muscles within the first week of training (18). In short-term
training, however, the reduction in coactivation is not always
evident (54). Possible adaptations in coactivation during maximal contractions, however, have not been examined at the
motor unit level.
Even less attention has been afforded to the changes that
occur in synergist and postural muscles. These effects are
significant, as indicated by the specificity of strength gains
(143), the importance of postural requirements (77, 109), the
improvement in coordination that occurs after strength training
(19), and the transfer effects associated with cross education
(95). As with coactivation, however, these adaptations with
maximal contractions have not been examined at the level of
the motor unit.
SUBMAXIMAL CONTRACTIONS
The force that a muscle exerts during a voluntary contraction
is not constant but fluctuates about an average intended value.
The magnitude of the fluctuations is influenced by such factors
as the intensity of the contraction, the type of muscle contraction, the muscle group involved in the task, the level of
physiological arousal, and the amount of fatigue (21, 22, 47,
93, 108). One functional outcome of these fluctuations is that,
when an individual repeats a task several times, the characteristics of the performance vary from trial to trial and influence
the accuracy with which the task can be performed (22, 56,
113, 125).
The variability in motor output is attributable to differences
in the motor units that are recruited, within and across muscles,
and the rates at which the motor neurons discharge action
potentials. Because the force that a newly recruited motor unit
contributes to the net force declines exponentially with an
increase in muscle force (46), tasks that involve low forces are
more susceptible to the variable forces produced by the few
active motor units (Fig. 4A). Furthermore, the fluctuations in
J Appl Physiol • VOL
motor unit force are exacerbated at low forces, because the
rates at which motor neurons discharge action potentials during
voluntary contractions are located on the lower region of the
force-frequency relation, which causes each motor unit to
contribute an unfused tetanus to the net force (Fig. 4, B and C;
Refs. 40, 83, 90, 92). This effect is most pronounced for the
last recruited motor unit, as it likely discharges action potentials at the lowest rate (32, 101).
The adaptations that can occur in motor unit behavior and
the effect on motor performance have been examined in two
protocols: steady contractions and force-tracking tasks. Steadiness is defined as the ability to produce a constant force or
trajectory during a voluntary contraction and is quantified as
the fluctuations in force during an isometric contraction or the
fluctuations in acceleration during an anisometric contraction
(16, 47, 51). The fluctuations in motor output during steady
contractions are strongly influenced by the variability in discharge rate (Fig. 4; Ref. 76, 92, 134). Accordingly, a training
intervention found that 2 wk of practicing a steadiness task
with a light load (10% of maximum) produced modest parallel
declines in the fluctuations in index finger acceleration during
slow shortening and lengthening contractions and the discharge
rate variability of single motor units in a hand muscle (74).
Four weeks of subsequent strength training with heavy loads
(70% of maximum) did not further improve either steadiness or
discharge rate variability. In the old adults studied by Kornatz
et al. (74), there was a strong association between the fluctuations in motor output and manual dexterity, as assessed with
the Purdue pegboard test.
Another influence of strength training on motor units is the
reduction in activity that is necessary to lift the same absolute
load after training compared with before training. For example,
Ploutz et al. (103) reported a reduction in the amount of
contrast shift in magnetic resonance images of the quadriceps
femoris muscles when lifting the same absolute loads after 9
wk of strength training. This result suggests that less muscle
mass was activated to lift the same load after training. Although the cross-sectional area of quadriceps femoris increased
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Fig. 3. A: comparison of the torque (a) and rectified electromyography (EMG) of the tibialis anterior (b) recorded in one subject during a fast (ballistic) isometric
ankle dorsiflexion, before and after dynamic training. Although a similar relative torque (41 vs. 44% MVC) was reached during the contractions, before and after
training, the rate of torque development was increased after training, and this was accompanied by an earlier and intensified EMG activity at the onset of the
contraction. B: schematic representation of the effects of dynamic training on the torque (a) and behavior of single MU from the tibialis anterior (b and c) during
fast isometric contractions with the ankle dorsiflexor muscles. Before training (left trace), the classic behavior of MUs during a fast contraction comprised a short
time lapse between the first two action potentials followed by longer interspike intervals. After training (right trace), the typical MU behavior involved a high
instantaneous discharge rate that was maintained during the subsequent interspike intervals. Training (B, c) also increased the incidence of double discharges
(interspike intervals ⬍ 5 ms) among the activated units (33% of units after training compared with 5% before training). [Adapted from Van Cutsem et al. (140).]
Invited Review
MOTOR UNIT ADAPTATIONS
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MECHANISMS OF ADAPTATION
Fig. 4. Simulated forces from a modified version of the Fuglevand model of
MU recruitment and rate coding (46). There were 180 MUs in the pool. A: the
force added by selected MUs (29, 48, 67, 99, 136, 146, 159, 169, 175, and 180)
to the net muscle force up to the upper limit of MU recruitment (59% of the
maximal force). The contribution to the net force by a newly recruited unit is
greatest at low forces. B: the unfused tetani produced by MU 90 when the net
muscle force was 10%, 20%, and 40% of maximum (% max). MU 90 was
recruited at 3.9% MVC force. C: the tetani produced by MUs 1, 30, 60, and
180 at forces slightly above the recruitment threshold for each MU. The
recruitment thresholds were 0.01, 0.49, 1.52, and 58.3% MVC force, respectively. The mean discharge rate and coefficient of variation for discharge rate
for the four MUs were as follows: MU 1 ⫽ 6.5 pps and 11.8%; MU 30 ⫽ 7.0
pps and 7.3%; MU 60 ⫽ 7.6 pps and 11.5%; MU 180 ⫽ 15.8 pps and 7.5%.
au, Arbitrary units. [Generated by M. Jesunathadas].
(6%), muscle biopsies indicated that fiber area did not change
with training. Furthermore, there was a reduction in the area of
contrast shift in the muscles of the untrained leg (right) after
training when lifting the same absolute loads. Presumably,
these adaptations involved some changes in motor unit activity,
J Appl Physiol • VOL
Despite evidence that suggests a significant role for neural
mechanisms in the adaptations associated with strength training, there has been less progress on identifying the specific
mechanisms responsible for these adaptations. The potential
mechanisms that might explain the increased activation of the
agonist muscles after training include subtle changes in the
pattern of motor unit recruitment and increases in the neural
drive (110, 117).
Although the timing of motor unit activation can be slightly
changed with training (26), it has been shown that the population of motor units examined before and after the intervention
still followed the size principle during a ramp contraction, after
either isometric or dynamic training (53). Furthermore, the
order of recruitment during rapid contractions did not change
after 12 wk of dynamic contractions with loads of 30 – 40% of
maximum in the tibialis anterior (140). Although the size
principle appears to be preserved after training, the absolute
force at which a specific unit is recruited depends on the
increase in the contractile characteristics (force and contraction
time) of low-threshold units after training. Essentially nothing
is known, however, about the influence of training on the upper
limit of motor unit recruitment. Decreases in the upper limit of
recruitment, such as has been observed for old adults (71),
results in a greater proportion of the force capacity of the
muscle relying on rate coding (25). It is unknown if training
can expand the range of motor unit recruitment and thereby
modify the relative contributions of recruitment and rate coding to the gradation of muscle force across the operating range
of the muscle.
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such as greater discharge rates for the active units and higher
recruitment thresholds for the nonrecruited units. Alternatively,
the ability to lift the same absolute load with less active muscle
mass may have been attributable to a more effective transmission of the force from the contractile proteins to the skeleton.
In the absence of data, however, the underlying mechanism is
not known. Nonetheless, the available data examining the
influence of strength training on the discharge rate of motor
units during submaximal and maximal contractions show
mixed results (26, 79, 100, 106).
The adaptability of motor unit behavior has also been assessed with force-tracking tasks (99). For example, Knight and
Kamen (73) examined the modulation of discharge rate during
the course of a single experimental session in which subjects
performed 15 trials of tracking a sinusoidal force profile. The
target force averaged 20% MVC force and comprised the sum
of two sine waves: 0.15 and 0.5 Hz. Subjects found it more
difficult to match the 0.5-Hz component of the target force, but
tracking at both frequencies improved with practice. The improvement in performance was accompanied by a reduction in
discharge rate variability and an increase in the modulation of
discharge rate at 0.5 Hz. This result is consistent with other
findings on the association between fluctuations in motor
output and modulation of discharge rate at low frequencies (23,
137). Nonetheless, the improvement in force tracking at 0.15
Hz observed by Knight and Kamen (73) was not accompanied
by a corresponding change in discharge rate modulation at that
frequency.
Invited Review
1772
MOTOR UNIT ADAPTATIONS
J Appl Physiol • VOL
motor performance, where long-term skilled use of the digits
may reduce the common input to motor neurons to promote
skilled neuromuscular performance, rather than contributing to
increases in strength with training (116).
Training adaptations within the spinal cord are often assessed in humans by testing electrically evoked reflexes, including the Hoffmann (H) reflex. The H reflex includes a
monosynaptic connection between the group Ia afferent and the
␣-motor neuron. Some studies have shown that strength training increases the amplitude of the H reflex (1, 112). Furthermore, when an electric stimulus sufficient to evoke a maximal
M wave is applied to a motor nerve during an MVC, two reflex
responses (V1 and V2) can be elicited. The V1-to-M-wave
ratio has been used as an index of reflex potentiation, where
there is an increase in the amplitude of the reflex (V1) relative
to the direct muscle response (M wave) after strength training
(1, 111). Observations on the operant conditioning of the spinal
stretch reflex and the H reflex suggest that much of the
plasticity in these reflexes appears to be located in the spinal
cord (144) and appears to be attributable to the role of spinal
interneurons in integrating the sensory and motor signals that
are transmitted to the motor neurons (96).
Although many investigators have used the H reflex as an
index of motor neuron excitability, the connection between the
afferent and the motor neuron is modulated by presynaptic
mechanisms, and hence the amplitude of the H reflex depends
on more than the responsiveness of the motor neuron (147). In
this context, given the observation that acute withdrawal of
group Ia feedback reduces discharge rate during a maximal
contraction (82), it is likely that training-induced changes in
afferent feedback can also influence motor unit discharge rate.
In addition to a possible role of afferent feedback in mediating
training adaptations, other evidence also indicates that the
properties of motor neurons can be altered by physical activity
(49). For example, Beaumont and Gardiner (9) reported that
endurance training in rats changed the biophysical properties of
motor neurons, which resulted in a more hyperpolarized resting
membrane potential, increased threshold for spike initiation,
and faster rise times for antidromic spikes. These adaptations,
which likely reflect alterations in ionic conductances of motor
neurons, can modify the recruitment thresholds and discharge
patterns of the neurons.
In conclusion, the neural adaptations that accompany
changes in physical training are diverse. This brief review has
examined the influence of these adaptations on the motor
output from the spinal cord as it is expressed in the recruitment
and rate coding of single motor units. There is some evidence
that adaptations in motor unit activity can contribute to improvements in motor performance. For example, the increase in
maximal rate of torque development is accompanied by a
greater motor unit discharge rate, whereas the reduction in
discharge variability appears to improve steadiness during
submaximal contractions after a training program. Because the
data are limited by technical constraints, however, it has been
difficult to demonstrate a clear association between neural
adaptations and changes in motor unit activity. Nonetheless,
recent work on rapid contractions, steady contractions, and
force-tracking tasks appear to represent promising strategies
for identifying the relations between central adaptations, motor
unit activity, and muscle function.
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The discharge rates of motor units during high-force contractions appear to place the motor units on the upper region of
the force-frequency relation but not on the plateau (83). Accordingly, the maximal rate of force development during a
tetanic contraction is usually obtained at a frequency that is
greater than the average discharge rate of motor units observed
during fast voluntary contractions (87). These observations
suggest that the MVC force and its maximal rate of development are less than the intrinsic capacity of the muscle and can
thus be improved by increasing motor unit discharge rate.
Consistent with this expectation, changes in discharge rate with
training have been observed during MVCs (63, 100) and at the
onset of a fast contraction (140).
The changes that can be evoked in neural circuits with
training are produced, in general, by adaptations at either of
two main levels: 1) supraspinal levels: corticospinal neurons,
subcortical neurons, and inhibitory and excitatory intracortical
interneurons; 2) spinal level: motor neurons, and inhibitory and
excitatory interneurons. Some studies involving short-term
motor skill training have reported that changes within the
primary motor cortex enlarge the cortical representation of the
muscles and increase the excitability of corticospinal pathways
(24, 97), possibly due to selective alterations in intracortical
inhibition (81). Despite the observation that several weeks of
skill training can increase corticospinal excitability (61, 97),
strength training does not seem to be accompanied by similar
adaptations (20, 61). For example, Jensen et al. (61) found that
skill training three times per week for 4 wk increased the
maximal motor-evoked potential (MEP) induced by TMS and
decreased the minimal stimulus intensity required to elicit
MEPs at rest and during a contraction. In contrast, the maximal
MEP and the slope of the input-output relation both decreased
significantly at rest but not during contraction in strengthtrained subjects. Furthermore, Carroll et al. (20) found that the
33% increase in maximal isometric torque of a hand muscle
after 4 wk of strength training was accompanied by no change
in corticospinal excitability measured at rest and was reduced
when tested during contractions. They also observed that the
degree of reduction in MEPs evoked by transcranial electrical
stimulation and TMS was similar. Because TMS largely excites cortical neurons through interneurons and transcranial
electrical stimulation excites the corticospinal fibers at the axon
hillock (107), these results suggest that strength training
changed the functional properties of spinal cord circuitry, but
not the output from the motor cortex.
These divergent effects of skill and strength training on the
nervous system are supported by data on motor unit synchronization. Motor unit synchronization is a measure of the
correlated discharge of action potentials by motor units and is
presumed to provide an index of the strength of common
branched input to motor neurons via the corticospinal pathway
(27, 43, 115). Motor unit synchronization is largest in weightlifters, intermediate in untrained subjects, and least for highly
skilled musicians (118), suggesting that the modification of
activity in branched corticospinal inputs to motor neurons is
related to some aspect of strength development in weightlifters
or to skilled hand function in musicians. However, computer
simulations (145) and experimental data (120) indicate a poor
association between changes in motor unit synchronization and
gains in strength. These findings suggest that alterations in
motor unit synchronization may be more closely related to fine
Invited Review
MOTOR UNIT ADAPTATIONS
GRANTS
Some experiments described in this review were performed with support
from the European Community (QLK6-CT-2001– 00323) awarded to J. Duchateau, the National Health and Medical Research Council of Australia
(274307) awarded to J. G. Semmler, and National Institutes of Health Awards
AG-09000 and NS-043275 to R. M. Enoka.
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