In this response, the major criticisms of the target article are addressed. Terminology from the target article that may have caused some confusion is clarified. In particular, the tasks that have the basic features of muscle coordination, as identified in the target article, have been limited in scope. Anew metabolic optimization criterion suggested by Alexander (2000) is examined for its ability to predict muscle coordination in walking. Issues concerning the validation of muscle force predictions, the rules of muscle coordination, and the role of directional constraints in coordination of two-joint muscles are discussed. It is shown in particular that even in one-joint systems, the forces predicted by the criterion of Crowninshield and Brand (1981) depend upon the muscle moment arms and the physiological cross-sectional areas in much more complex ways than either previously assumed in the target article, or incorrectly derived by Herzog and Ait-Haddou (2000). It is concluded that the criterion of Crowninshield and Brand qualitatively predicts the basic coordination features of the major one- and two-joint muscles in a number of highly skilled, repetitive motor tasks performed by humans under predictable conditions and little demands on stability and accuracy. A possible functional significance of such muscle coordination may be the minimization of perceived effort, muscle fatigue, and/or energy expenditure.
Boris I. Prilutsky
Akinori Nagano and Karin G.M. Gerritsen
The purpose of this study was twofold: (a) to systematically investigate the effect of altering specific neuromuscular parameters on maximum vertical jump height, and (b) to systematically investigate the effect of strengthening specific muscle groups on maximum vertical jump height. A two-dimensional musculoskeletal model which consisted of four rigid segments, three joints, and six Hill-type muscle models, representing the six major muscles and muscle groups in the lower extremity that contribute to jumping performance, was trained systematically. Maximum isometric muscle force, maximum muscle shortening velocity, and maximum muscle activation, which were manipulated to simulate the effects of strength training, all had substantial effects on jumping performance. Part of the increase in jumping performance could be explained solely by the interaction between the three neuromuscular parameters. It appeared that the most effective way to improve jumping performance was to train the knee extensors among all lower extremity muscles. For the model to fully benefit from any training effects of the neuromuscular system, it was necessary to continue to reoptimize the muscle coordination, in particular after the strength training sessions that focused on increasing maximum isometric muscle force.
Rositsa T. Raikova
This commentary emphasizes three points of discussion. (a) The terminology: The terms multifunctional, synergisic, antagonistic muscles, and synergistic and antagonistic coactivations are discussed and the conclusion is drawn that they could not be used without mentioning the particular joint motion. (b) The importance of the external joint moments for activation of the muscles is confirmed on the basis of logical and mechanical considerations. Not all experimental results, however, could be explained by this means. (c) The optimization criterion: Prilutsky's conclusion concerning the predicted muscle force proportionality to the muscle moment arm and PCSA is confirmed using a simple analytical solution of the optimization problem. It is shown, however, that the proportionality to the PCSA is a consequence of the chosen optimization criterion.
Afshin Samani and Mathias Kristiansen
, Gritsenko, & Yakovenko, 2002 ). Thus, investigating muscle synergy components during bench press can set a benchmark to study muscle coordination in motor tasks where strength is a major factor. Further, within the field of strength training, strength and conditioning professionals can manipulate exercise
Jos J. de Koning, Gert de Groot and Gerrit Jan van Ingen Schenau
The purpose of this study was to describe the intermuscular coordination and power production for the constrained asymmetrical movement during skating the curves. Seven elite male speed skaters took part in the experiments. The speed skaters were simultaneously filmed from frontal and sagittal views. EMGs were obtained telemetrically and push-off force was registered with special skates. Inverse dynamic analysis yielded power production data, which differed for left and right leg. Marked differences were also found in intermuscular coordination of each leg. The activation patterns of the muscles were influenced by the asymmetrical nature and the typical body position during the speed skating movement. External power output was determined by three methods. The mean joint power output for left and right leg showed similar values as the external power output calculated from air and ice friction. These values were lower than the values predicted with a geometrical model for skating the curves.
Geetanjali Gera, Kelsey E. McGlade, Darcy S. Reisman and John Peter Scholz
In this study, we investigated deficits in coordination of trunk muscle modes involved in the stabilization of the trunk’s trajectory for reaching upward and downward beyond functional arm length. Trunk muscle activity from 10 stroke survivors (8 men, 2 women; 64.1 ± 10.5 years old) and 9 healthy control subjects (7 men, 2 women; 59.3 ± 9.3 years old) was analyzed. Coordination of trunk muscle modes to stabilize the trunk trajectory was investigated using the uncontrolled manifold (UCM) analysis. The UCM analysis decomposes the variability of muscle modes into good and bad variability. The good variability does not affect the control of trunk motion, whereas the bad variability does. In stroke survivors, deficits in the ability to flexibly combine trunk muscle modes was associated with reduced ability to minimize those combinations of trunk muscle modes that led to an error in trunk trajectory (bad variability), and this had a greater effect on reaching upward. This reduced coordination of trunk muscle modes during reaching was correlated with a clinical measure of trunk impairment.
Stephanie L. Jones and Graham E. Caldwell
This study examined the role of mono- and biarticular muscles in control of countermovement jumps (CMJ) in different directions. It was hypothesized that monoarticular muscles would demonstrate the same activity regardless of jump direction, based on previous studies which suggest their role is to generate energy to maximize center-of-mass (CM) velocity. In contrast, biarticular activity patterns were expected to change to control the direction of the ground reaction force (GRF) and CM velocity vectors. Twelve participants performed maximal CMJs in four directions: vertical, forward, intermediate forward, and backward. Electromyographical data from 4 monoarticular and 3 biarticular lower extremity muscles were analyzed with respect to segmental kinematics and kinetics during the jumps. The biarticular rectus femoris (RF), hamstrings (HA), and gastrocnemius all exhibited changes in activity magnitude and pattern as a function of jump angle. In particular, HA and RF demonstrated reciprocal trends, with HA activity increasing as jump angle changed from backward to forward, while RF activity was reduced in the forward jump condition. The vastus lateralis and gluteus maximus both demonstrated changes in activity patterns, although the former was the only monoarticular muscle to change activity level with jump direction. Mono- and biarticular muscle activities therefore did not fit with their hypothesized roles. CM and segmental kinematics suggest that jump direction was initiated early in the countermovement, and that in each jump direction the propulsion phase began from a different position with unique angular and linear momentum. Issues that dictated the muscle activity patterns in each jump direction were the early initiation of appropriate forward momentum, the transition from countermovement to propulsion, the control of individual segment rotations, the control of GRF location and direction, and the influence of the subsequent landing.
Steven A. Kautz, Richard R. Neptune and Felix E. Zajac
The target article presents a framework for coordination of one- and two-joint muscles in a variety of tasks. Static optimization analyses were performed that minimize muscle fatigue, and it is claimed that the predicted muscle forces account for essential features of EMG activity “qualitatively” well. However, static optimization analyses use the observed joint moments, which implicitly assumes that they minimize the total muscle fatigue of the task. We use a forward dynamics (i.e., relationship between muscle forces and the kinematics and kinetics of task performance) modeling approach to show that this assumption does not appear to be true in cycling (which was used as an example task in the target article). Our results challenge the hypothesized coordination framework and the underlying concept that general coordination principles for dynamic tasks can be elucidated using inverse-dynamics-based analyses.
Boris I. Prilutsky and Robert J. Gregor
The purpose of this study was to simulate the control of an external force using different strategies of muscle coordination and to compare the predicted patterns of muscle forces with those of electromyographic activity reported in the literature for the same task. We simulated a motor task in which a person sitting on a chair exerts an external force by pushing on the ground (or pulling a strap) in five different directions with two different force magnitudes. The results of this study suggest that during the control of an external force in pushing directions, more force is allocated to muscles with long moment arms and a large physiological cross-sectional area, and the number of simultaneously active muscles is increased. This strategy of muscle coordination corresponds to the strategy of minimizing muscle fatigue, and it is characterized by features of muscle coordination that agree with those reported in experimental studies of walking, running, jumping, and cycling.
The target article by Prilutsky gives an excellent overview of the predictions of the Crowninshield and Brand model and about the relevant literature about muscle coordination. However, we do not agree with the claim that the Crowninshield and Brand model can explain the coordination between one-joint and two-joint muscles. In this commentary we will make three claims: (a) The Crowninshield and Brand model cannot explain all aspects of muscle coordination, (b) there is good experimental evidence that different constraints and models may be necessary to explain muscle coordination in different motor tasks, and (c) the reason for the lack of quantitative fits between predictions about muscle force and experimental data is that it is hard to measure muscle force in man. As a compromise one has to rely on EMG activity as a measure of muscle force. Because of the complex relationship between EMG and muscle force, a quantitative test of models is difficult.