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MUSCLE STRENGTH, COORDINATION, AND MUSCLE FUNCTION
Roger M. Enoka
Department of Integrative Physiology, University of Colorado, Boulder, CO 80301-0354, USA.
([email protected])
Although the force capacity of isolated muscle is strongly associated with its cross-sectional area
[Powell et al. 1984], its strength clearly depends on the extent to which it, its synergistic and
antagonistic muscles, and the associated postural muscles are activated by the nervous system. The
purpose of this presentation is to review recent developments on the limits imposed by the nervous
system on the expression of muscle strength.
Several observations underscore a significant role for the nervous system in the assessment of
strength: (1) the variability in the association between muscle cross-sectional area and strength
[Kanehisa et al. 1994]; (2) the variable effects of strength training on the different measures of
strength [Laidlaw et al. 1999; Rutherford & Jones, 1986]; (3) the often poor transfer of strength gains
to improvements in motor performance [Tracy & Enoka, 2006]. Presumably, these effects are
attributable to the involvement of multiple muscles, more than just one group of agonist muscles, in
the performance of a prescribed task.
Task Failure and the Significance of Postural Activity
Muscle fatigue can be quantified as an exercise-induced decline in the maximal force capacity of
muscle. Although it is caused by an impairment of either the activation signal or the function of the
contractile proteins, the specific mechanisms depend on the details of the task. Critical task variables
include the type and intensity of exercise, the type of load supported during the contraction, the
muscle groups involved, and the physical environment in which the task is performed [Gandevia,
2001]. Because of the task-dependent variation in the prevailing mechanisms, it has not been
possible to identify a single factor that is responsible for muscle fatigue. An alternative strategy to
study muscle fatigue, therefore, is to identify the mechanisms responsible for the failure of specific
tasks [Maluf & Enoka, 2005].
This approach has been used to compare performance on a task in which a subject pushes against a
restraint and maintains a submaximal force for as long as possible (force task) with supporting an
equivalent mass for as long as possible while maintaining a prescribed joint angle (position task).
The time to task failure is generally longer for the force task. For example, the time to task failure
was 1402 ± 728 s for the force task and 702 ± 582 s for the position task when subjects matched
loads of 15% MVC force with the elbow flexor muscles [Hunter et al. 2002]. Measures of central
neural activity (motor unit recruitment and rate coding, mean arterial pressure, heart rate, variability
in motor output) indicate that the motor unit pool is recruited more rapidly during the position task,
which contributes to its briefer duration [Maluf et al. 2005; Mottram et al. 2005].
aEMG (% MVC)
60
50
Position
40
30
20
Force
10
0
0
100
200
300
400
Time (s)
500
600
Figure 1 The average, rectified EMG (aEMG, normalized to peak MVC value, mean ± SE) for three rotator cuff
muscles during the force and position tasks with the forearm in a horizontal position. The aEMG was averaged over
30-s intervals during each task. Subjects sustained each task at 20% MVC force for as long as possible with the
elbow flexor muscles.
The difference in the time to failure for these two tasks, however, varies with the muscle that
performs the fatiguing contractions and the position of the limb. For example, the time to failure for
the position task was 77% of that for the force task when the elbow flexor muscles sustained a force
at 20% MVC force with the forearm vertical [Rudroff et al. 2005], whereas it was 51% when the
forearm was horizontal [Hunter et al. 2002] even though the rate of increase in aEMG was similar
during the two tasks in both studies. The relative difference between the two tasks appears to have
been influenced by the greater demands placed on postural muscles when the forearm was horizontal.
Figure 1 shows that the rate of increase in the average EMG (aEMG) for three rotator cuff muscles
(supraspinatus, infraspinatus, teres minor) was much greater during the position task, which was
associated with the difference in the time to failure for the force and position tasks (8.8 ± 3.6 and 5.2
± 2.6 min, P = 0.003) [Rudroff et al. submitted].
Reflexes Between Synergist Muscles
The contribution of a muscle to the net muscle torque about a joint depends on its architecture (crosssectional area, length of muscle fibers, pennation angles) and on its attachment sites to the skeleton.
The attachment sites influence the magnitude of the moment arm and the axes about which the
muscle can exert a torque. Because of these effects, muscles can act as synergists for one action but
antagonists for another action. For example, biceps brachii contributes to the elbow flexor and
supinator torques, whereas brachioradialis contributes to the elbow flexor and pronator torques. As a
consequence of this difference, the degree of pronation-supination of the forearm influences the
relative contributions of biceps brachii and brachioradialis to a net flexor torque [Buchanan et al.
1989].
Figure 2 Quantification of the effect of the delivery of an electric shock (stimulation condition) or not (control) to
the brachioradialis nerve on the discharge of a motor unit in biceps brachii. The stimulus, which generated afferent
feedback that was delivered to the motor neurons innervating biceps brachii, was delivered at a delay of 30 ms after a
randomly selected motor unit potential. The time from the stimulus to the next discharge (PSTH interval) was
entered in the post-stimulus time histogram (PSTH). As indicated in this record, the time to the next discharge was
prolonged when a stimulus was applied to the nerve due to an inhibitory pathway from the brachioradialis muscle to
the biceps brachii.
One factor that might contribute to the influence of limb posture on the time to task failure is the
reflex pathways between muscles. For example, Naito et al. [1996] have reported an inhibitory
pathway from brachioradialis to biceps brachii. This interaction was examined by quantifying the
influence of afferent feedback over the brachioradialis branch of the radial nerve on the discharge
rate of single motor units in biceps brachii [Pascoe et al. 2006; Riley et al. 2006]. Single stimuli were
delivered at 0.9x motor threshold at a delay of 30 ms after the discharge of the isolated motor unit.
Participants were required to maintain the discharge of an isolated motor unit in biceps brachii at
about 10 pps for 4 min. A stimulus was applied to the brachioradialis nerve once every 2-3 s for a
total of 100 stimuli. The influence of the stimulus was evaluated by constructing post-stimulus time
histograms in the presence and absence of the stimulus (Figure 2). There was a depression in the
relative post-stimulus time histogram that denoted the presence of an inhibitory pathway. The extent
to which the stimulus delayed the next action potential was greatest when the forearm was pronated
and least when it was supinated (Figure 3). Thus, the inhibition of motor neurons that innervate
biceps brachii by afferent feedback from brachioradialis varied with the posture of the forearm.
Figure 3 Difference in the interspike interval (ISI) for action potentials discharged by motor units (n = 18) in
biceps brachii before and after a stimulus was delivered to the brachioradialis branch of the radial nerve. No stimulus
was delivered in the control condition.
Muscle Coordination
According to the principle of specificity, the gains that are achieved with a strength-training program
are limited to the conditions that existed during the performance of the exercises [Wilson et al. 1996].
For example, strength training can often produce disparate increases in MVC force and 1-RM load
[Hortobágyi et al. 1996; Tracy & Enoka, 2006]. As described in the seminal study by Rutherford &
Jones [1986], one factor that can contribute to the variable gains across tasks is the coordination of
the involved muscles [Barry & Carson, 2004].
Koyama [1994, 2004] suggests that one of the major limitations of most training techniques is that
they fail to train the patterns of muscle activation used during unconstrained movements. To remedy
this deficit, he developed a technique known as Beginning Movement Load (BML) training; this
technique is well known in Japan but not elsewhere. The three key features of BML training are: (1)
prime mover – the muscle is stretched to a long length while relaxed and then performs a shortening
contraction against a load that is greatest at the onset of the contraction; (2) activation sequence – the
muscles involved in the task are activated in a sequence that proceeds in the proximal-to-distal
direction and there is minimal coactivation of the agonist and antagonist muscles; and (3) dodge
movement – the activation sequence is facilitated by a rotation about the longitudinal axis of the
segment.
To realize these patterns of activation, Koyama has developed a number of BML machines (patents
pending) that employ cam systems to provide the maximal load at the onset of the shortening
contraction and include additional degrees of freedom to enable dodge movements. A preliminary
report on a lat pull-down machine indicates that the BML machine requires a greater range of motion
for the scapula and involves a different pattern of muscle activations compared with a conventional
lat pull-down machine [Koyama et al. 2005]. The BML machine includes two additional degrees of
freedom: one for pronation-supination of the forearm and another for flexion-extension of the
shoulder in a horizontal plane.
In summary, the presentation attempts to support two main conclusions about the improvements in
performance with strength training: (1) strength gains can be limited by the demands imposed on
postural muscles and by the reflex pathways that exist between the involved muscles; and (2) the
patterns of muscle activity used to perform the exercises likely constrain the potential to improve
performance on functional tasks.
Some of the research reported in this presentation was supported by awards from the National
Institute on Aging (R01 AG090000) and the National Institute of Neurological Disorders and Stroke
(NS43275).
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