The main finding of this study was that highly skilled individuals present a greater ability to perform steady submaximal isometric wrist flexions at matched levels of MVC than less skilled participants. This greater steadiness was not accompanied by group differences in the agonist and antagonist EMG and it was not length specific.
Experts are much steadier than similarly strong sedentary
Several hypotheses could be formulated to justify why experts are more accurate than sedentary young adults with the same level of force such as group differences in activation strategy of the agonist muscle, simultaneous activation by other synergistic muscles, antagonist coactivation, integration of visual feedback, and muscle fiber typology and mechanics. First, force fluctuations are dependent on the interaction between firing patterns of motor units of the agonist muscles (variability, firing rate, common modulation, and synchronization) (Jones et al.
2002; Kornatz et al.
2005; Laidlaw et al.
2000; Moritz et al.
2005; Semmler and Nordstrom
1998; Taylor et al.
2003; Tracy et al.
2005; Vaillancourt and Newell
2003). A greater motor–output variability could be the result of an altered agonist activity. It has been reported that long-term learning of a motor task was associated with differences in higher centers and preprogrammed descending commands and adaptations in the contralateral somatosensory and motor cortex and the putamen (Floyer-Lea and Matthews
2005). Distinct functional changes in both primary somatosensory and motor cortex increase representation of the learned specific movement sequence and indicate the importance of afferent feedback to this form of predominantly implicit motor learning (Floyer-Lea and Matthews
2005). Motor-unit synchronization, as a result of strength training, could decrease the steadiness of the force exerted by the muscle in simulated contractions (Yao et al.
2000). Force tremor is reported to be higher in the strength-trained subject, median in the untrained subject and lower in the skill-trained subject (Semmler and Nordstrom
1998). However, it has recently been reported that strength training does not affect the accuracy of force gradation in an isometric task in young men, supporting that there is no evidence to expect a loss in accuracy as a result of strength training (Smits-Engelsman et al.
2008). In the same line, Hamilton et al. (
2004), comparing force fluctuation in four upper limb muscles with widely varying maximal forces and numbers of motor units (elbow extensors, wrist flexors, first dorsal interosseus, and thumb extensors), reported that stronger muscles with greater numbers of motor units had the lowest fluctuations.
Second, one may consider that the torque measured about the wrist is the sum of all the forces acting on that joint. When more than one muscle is active, there are many finite combinations of synergist and antagonist forces that can produce a given torque about the joint. Therefore, fluctuations in joint torque reflect not only the summation of force fluctuations in individual muscles, but also the shape and the temporal association in the waveform of force fluctuations between muscles. According to Shinohara et al. (
2009), an asynchronous compensatory fluctuation between individual muscles forces could happen due to subtle differences in the neural activation strategy, force production profiles, and/or force transmission characteristics across muscles. Third, a lower coactivation of the antagonists in highly skilled compared to sedentary individuals is clearly demonstrated during maximal efforts (Amiridis et al.
1996). However, in our study, the greater steadiness exhibited by experts was not accompanied by alterations at the level of the antagonist coactivation (Table
2), confirming also previous reports (Burnett et al.
2000). Four, a greater integration of visual feedback by the elite individuals could maximize information transmission and minimize force fluctuations during constant isometric tasks (Christou
2005). Finally, differences in morphological (theoretically, type II fibers having higher fusing frequencies than type I fibers, will produce more tremor at a given recruitment level) (Yao et al.
2000) and mechanical properties (series compliance and frictional interactions among muscle fibers) (Troiani et al.
1999) could also be involved to a nonlinear summation and mechanical differences between highly skilled and sedentary individuals.
The absence of differences in wrist flexors MVC scores between athletes and sedentary individuals could be partially justified by the sport skill level, velocity specificity, and the type of action. It could be assumed that the well-documented neural mechanism of motor unit synchronization following strength training (Milner-Brown et al.
1973) has not occurred in our experts. This is also supported by an unchanged coactivation level during maximal efforts, which almost always accompanies strength training adaptations (Jubeau et al.
2006).
Steadiness increases as the % MVC force increases
In the present study, the quantification of variability was based on the use of relative % MVC target levels and not absolute levels of force, as suggested previously for a generalized description of force variability during isometric actions (Christou et al.
2002). Our results showed clearly that as the force percentage increased, the CV of force decreased, regardless of the expertness level (Fig.
2). This seems to be in line with previous studies (Christou and Carlton
2002, Laidlaw et al.
2000), but not with others which reported that, during isometric handgrip, force tremor amplitude increased from 20 to 60% MVC and decreased at 80% MVC (Loscher and Gallash
1993). However, the pattern of the variability alteration could be described better as a sigmoidal (Christou et al.
2002; Loscher and Gallash
1993) than an exponential (Slifkin and Newell
1999) relationship. Differences in temporal parameters, age of participants, sex, type of action, muscular group, and visual feedback could only partly explain such a discrepancy. We propose that at very low levels of force both experts and active young adults present an increased variability because of synchronization of motor units. When greater levels of force are exerted, the variability decreases. Although in our study we did not examine motor unit firing patterns, it is tempting to consider that a more stochastically independent discharge of motor units in experts contributed to the lower force fluctuations in these participants compared with sedentary ones (Semmler and Nordstrom
1998; Christakos
1982).
Steadiness remains unaffected from the muscular length
No wrist angle effect on force variability measurements was observed in both experimental groups, suggesting that the length of the flexor muscles does not influence the steady application of force. The absence of any length specificity could support that expert and sedentary participants used their wrist flexors across the whole range of motion in a similar manner. The maximum force was attained when the wrist was maximally extended (Table
1). This confirms a previous study which combined morphological data from a cadaver with a mathematical model (Friden and Lieber
1998).
In conclusion, we observed that a group of individuals who have a longer expertise in utilizing the wrist muscles present significant differences on force variability compared with individuals with no previous experience. However, this observation was not accompanied by group differences in either agonist or antagonist muscle activity patterns. Because extended practice increases the importance of task-specific sources of variation and defines someone as an expert in one task but novice to another, further examination of other factors, such as motor unit behavior is required to examine whether force variability is related to skill level.