Download Changes in muscle coordination with training

J Appl Physiol 101: 1506 –1513, 2006.
First published August 3, 2006; doi:10.1152/japplphysiol.00544.2006.
Invited Review
HIGHLIGHTED TOPIC
Neural Changes Associated with Training
Changes in muscle coordination with training
Richard G. Carson
School of Psychology, Queen’s University Belfast, Belfast, Northern Ireland, United Kingdom
movement; synergy; cortex; resistance; motor unit
BACKGROUND
IN ENGAGING IN TRAINING THAT has as its specific aim an
increase in muscular strength, most participants have another
more general objective in mind, namely to increase their level
of performance in functional tasks, whether these be defined in
the context of daily living or by the pursuit of athletic, artistic,
or recreational goals. The accomplishment of purposeful tasks
necessarily requires coordination: “the organisation of control
of the motor apparatus” (Ref. 3, p. 355). To undertake a
meaningful study of coordination, it is first necessary to consider the level of description at which the elements of the motor
apparatus are to be delineated. For the purposes of the present
review, the relevant element is deemed to be the motor unit.
Groups of muscle fibers normally contract together (5). A
motor unit is designated as those muscle fibers, which may be
dispersed widely throughout a muscle, that are innervated by a
single motoneuron. Muscle coordination is, therefore, defined
as the organization of control of motor units.
Even though the motor unit is the only available external
output channel of the brain (33), the degrees of freedom via
which variations in motor output may be expressed are suffi-
Address for reprint requests and other correspondence: R. G. Carson, School
of Psychology, Queen’s Univ. Belfast, Belfast, N. Ireland BT7 1NN, UK
(e-mail: [email protected]).
1506
ciently numerous that the translation of muscle coordination
into purposeful action necessarily occurs in the context of
constraints imposed by the organization of the central nervous
system (CNS). In the present review, consideration will be
given to the nature of some of the constraints on muscle
coordination and to the means by which their influence may be
either ameliorated or consolidated by training. The emphasis
will be on a small number of core concepts that are perhaps
infrequently considered in this domain, rather than on a general
coverage of neural adaptations to resistance training, for which
a number of comprehensive reviews exist already (e.g.,
Ref. 18).
ACTIVITY-DEPENDENT COUPLING
Brain activity during functional movement tasks. During
goal-directed movements, synchronization (coherence in the 2to 14-Hz range) of the electromyogram (EMG) and cortical
activity registered by high-density electroencephalography
(EEG) is widely expressed across multiple motor and premotor
areas (e.g., Ref. 17). These and related observations suggest
that the transsynaptic spread of coherent activity through the
motor network is an integral aspect of its function (cf. Ref. 54).
Indeed, it is now apparent that activity-dependent coupling
between neuronal oscillators is a generic characteristic of the
brain. Importantly, the potential for activity-dependent cou-
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Carson, Richard G. Changes in muscle coordination with training. J Appl Physiol 101:
1506–1513, 2006. First published August 3, 2006; doi:10.1152/japplphysiol.00544.2006.—
Three core concepts, activity-dependent coupling, the composition of muscle
synergies, and Hebbian adaptation, are discussed with a view to illustrating the
nature of the constraints imposed by the organization of the central nervous system
on the changes in muscle coordination induced by training. It is argued that training
invoked variations in the efficiency with which motor actions can be generated
influence the stability of coordination by altering the potential for activity-dependent coupling between the cortical representations of the focal muscles recruited in
a movement task and brain circuits that do not contribute directly to the required
behavior. The behaviors that can be generated during training are also constrained
by the composition of existing intrinsic muscle synergies. In circumstances in
which attempts to produce forceful or high velocity movements would otherwise
result in the generation of inappropriate actions, training designed to promote the
development of control strategies specific to the desired movement outcome may be
necessary to compensate for protogenic muscle recruitment patterns. Hebbian
adaptation refers to processes whereby, for neurons that release action potentials at
the same time, there is an increased probability that synaptic connections will be
formed. Neural connectivity induced by the repetition of specific muscle recruitment patterns during training may, however, inhibit the subsequent acquisition of
new skills. Consideration is given to the possibility that, in the presence of the
appropriate sensory guidance, it is possible to gate Hebbian plasticity and to
promote greater subsequent flexibility in the recruitment of the trained muscles in
other task contexts.
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MUSCLE COORDINATION
mechanisms employed by the CNS to coordinate groups of
motor units or muscles into functional assemblies (e.g., Ref.
55). Although muscle synergies appear to represent an elegant
solution to the problem posed by the multiple degrees of
freedom that characterize the output of the human motor
system, their implementation necessarily requires that the motor centers in the brain instantiate highly organized patterns of
facilitation and inhibition that are spatially, temporally, and
functionally discrete and are tailored to the specific requirements of the task at hand.
The cortical representations of muscles overlap broadly
(e.g., Refs. 25, 30), and activity in each region of cortex thus
has the potential to influence the projections to a wide distribution of motor units. This is depicted schematically in Fig. 1
(top). The complex connectivity that exists between multiple
frontal motor areas (37) also points to means by which interference may occur between the cortical representations of the
focal muscles recruited in a movement task and brain circuits
that do not contribute directly to the required movement (24,
44). In so much as purposeful action requires the focal recruitment of muscles in the context of a specific synergy, factors
such as elevations in the rate of movement, which increase the
distribution of cortical reactivity, have the capacity to disrupt
coordination. Indeed, it has been proposed previously that the
potential for interference between functionally proximal areas
of the cerebral cortex is contingent on the degree to which
these areas are activated (29) and that it is by this means that
the efficiency with which motor actions can be generated
dictates the stability of coordination (10).
Variations in the efficiency of motor actions. How is the
construct of “efficiency” to be understood? For the present
purposes it can be said to reflect the relationship between the
level of task contingent activity in the cortical motor network
and the consequential alterations in muscle force (cf. Ref. 23).
Unit changes in the firing rate of the corticomotoneuronal cells
that innervate the flexor muscles of the upper limb result in
Fig. 1. Activity (¥) in the region of cortex of cortex
that projects to the focal muscles recruited in a movement task has the potential to influence brain circuits
that do not contribute directly to the required movement (␣, ␤, and ␹). In the top row, the level of activity
in the region of cortex of cortex (¥) and the consequential levels of activity that are induced in the other
brain areas (␣, ␤, and ␹) are represented by the intensity of the shading (deeper shading indicates greater
activity). In the middle row, the relationship between
the level of task contingent activity in the cortical
motor network (¥) and the consequential alterations in
muscle force (i.e., the efficiency of the motor action) is
represented before (A) and after (B) a period of training
that increases the force-generating capacity of the skeletal muscle. After training, there is a reduction in the
level of task contingent cortical activity that is required
to achieve a specific movement outcome. In the bottom
row, the corresponding levels of activation in the brain
circuits that do not contribute directly to the required
movement (␣, ␤, and ␹) are shown directly. EMG,
electromyogram.
J Appl Physiol • VOL
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pling is to a large extent independent of the underlying (structural) pattern of interconnections present between groups of
neurons, and it is contingent primarily on their respective
levels of activity (45, 46).
A body of evidence now exists to support the proposition
that the required degree of muscle activation determines the
distribution of brain activity associated with a functional movement task. The area of primary motor cortex that is activated
increases with the rate of movement (4, 43, 51), and there is a
close relationship between levels of motor output and the
functional magnetic resonance imaging-registered brain activity present both in motor-function-related cortical fields and
across the entire brain (16). Examination of the relationship
between EEG-derived motor activity-related cortical potentials
and voluntary muscle activation suggests that the magnitude of
the signal recorded from sensorimotor cortex and supplementary motor area is contingent on the intensity of the contraction
(48, 49). After the administration of repetitive transcranial
magnetic stimulation, which increases the amplitude of motor
potentials evoked subsequently in the target muscle by singlepulse transcranial magnetic stimulation, there occurs a corresponding increase in the excitability of corticospinal projections to other muscles of the same limb. This spread of
reactivity appears to be mediated by intracortical mechanisms,
in particular by changes in the excitability of interneurons
mediating intracortical inhibition (36). Thus increases in the
excitability of specific regions of motor cortex, whether induced by changes in the required level of muscle activation or
by electromagnetic stimulation, lead to widely distributed alterations in cortical reactivity.
Synergies. The essence of coordination is the formation of
“structural units”: groups of elements united in relation to a
common goal (20). In this regard, it is evident that natural tasks
seldom involve a single classically defined motoneuron pool
and its motor units. More often a group of muscles or motor
units will be involved. Synergies are defined operationally as
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J Appl Physiol • VOL
damage induced by eccentric contractions require corresponding increases in cortical motor network activity to bring about
equivalent behavioral outcomes (14). It seems reasonable to
suppose therefore that, by virtue of the fact that there is a
commensurate decrease in the descending efferent drive required to bring about an equivalent movement outcome (see
Fig. 1), increases in the force-generating capacity of skeletal
muscle fibers will result in a reduction of task contingent
activity in the cortical motor network and thus in diminished
interference mediated by activity-dependent coupling. As a
result of training-induced intramuscular adaptations, therefore,
the processes of instantiating task specific synergies in the
motor centers of the brain, and the muscle coordination to
which these synergies give rise, will be more robust than when
before training muscle force was generated with lower efficiency.
THE COMPOSITION OF MUSCLES SYNERGIES
Stability and adaptability. To appreciate the potentially
beneficial effects of increases in strength in complex natural
tasks, it is necessary to also consider the context in which
muscle actions are performed. Tasks encountered in daily
living seldom involve a single muscle. The potential contribution of an increase in strength in a particular muscle, or group
of muscles, to the performance of a particular movement task
is constrained by the composition of the synergy within which
the muscles are activated. Intrinsic synergies are conceived of
as protogenic (literally, formed at the beginning) muscle recruitment patterns that generate our basic repertoire of movements. For example, rhythmic flexion and extension of the
wrists require the alternating recruitment of muscles that have
mechanically opposed lines of action. These movements are
supported by neural circuitry that promotes the reciprocal
activation of anatomical (as opposed to functional) agonist and
antagonist muscles [e.g., flexor carpi radialis (FCR) and extensor carpi radialis (ECR)]. Abduction-adduction movements of
the wrists can be brought about only via control strategies that
inhibit the expression these protogenic muscle recruitment
patterns (2, 9). Although the radial wrist extensor (ECR) and
flexor (FCR) behave as classical antagonists during flexion and
extension movements, they are activated together during abduction of the wrist. Although control regimes sufficient to
generate rhythmic abduction-adduction movements can be instantiated in most circumstances, when task demands are
increased, for example, by increasing the required rate of
movement, reciprocal activation of the flexors and extensors
becomes dominant as the more robust intrinsic synergies are
expressed (31). Despite the fact that many muscle systems are
characterized by intrinsic synergies, these patterns of activation
do not necessarily always result in the most effective solution
to task demands defined in an occupational or recreational
setting (12).
The evident potential for task-dependent modulation of
muscle recruitment patterns in the context of skill acquisition
indicates that there is also a certain amount of flexibility in the
composition of muscle synergies (e.g., Refs. 26, 47). Yet it is
apparent that the CNS maintains a balance between the facility
for adaptation in response to novel task requirements and the
number of parameters with respect to which variations in motor
output are expressed. Programs of training that involve the
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greater increases in torque than equivalent changes in the firing
rate of cells that project to the extensor muscles (15). This is
also consistent with the observation that a smaller proportion of
flexor motor units must be activated to produce a given level of
force (53). It can thus be said that the flexor muscles of the
upper limb generate motor actions more efficiently than the
extensor muscles. It is notable, therefore, that tasks that require
synchronization of flexion movements with an external stimulus are performed in a more consistent fashion than otherwise
equivalent tasks in which extension movements are emphasized (11, 13).
It follows from this line of reasoning that acute or chronic
alterations in the efficiency with which motor actions are
generated should have a corresponding impact on the quality of
coordination. In this regard, it has been shown that alterations
in the lengths of muscles, such as those that arise from changes
in the posture of the limb, result in changes in the level of force
that is generated for a given neural input (e.g., Ref. 21), and
correspondingly, manipulations of posture have both predictable and reliable effects on the stability with which sensorimotor coordination tasks can be performed (11, 13). Of greater
relevance in the present context is the observation that chronic
changes in the strength of specific muscles, induced by a
program of resistance training, also have a reliable influence on
the stability of sensorimotor coordination. Carroll et al. (6)
reported that increases in the strength of the muscles that
extend the index finger lead to enhancement of the execution of
a task that required that the extension phase of rhythmic
movements be made in time with the beat of an auditory
metronome. Typically, the performance of such tasks becomes
highly variable, and the required pattern of coordination is
compromised as the frequency of movement is increased. After
4 wk of focal resistance training, however, there was a distinct
increase in the frequency at which the task could be performed
in an accurate and stable fashion (6).
Are such changes in the stability of behavior mediated by
trained induced alterations in the efficiency with which motor
actions are generated? One direct consequence of resistance
training appears to be an increase in the gain of the corticospinal pathway (8). After a training intervention of 4-wk
duration, the level of input to the spinal motoneurons that is
associated with a particular degree of muscle activation or joint
torque is lower than that present before training (see also Ref.
27). In so much as there has been a modification of the
relationship between the level of activity in the cortical motor
network that is directly related to that specific task and the
corresponding muscle force, a change in efficiency can thus be
inferred.
Recent reports that the corticomotoneuronal synapse exhibits plasticity, and is subject to short-term modulation in response to voluntary activity (19, 40), raise the possibility of
that chronic adaptations at this synapse may be induced by
high-intensity training. It is perhaps more typical, however, to
think of the changes in strength induced by resistance training
in terms of intramuscular adaptations in contractile properties.
In short, resistance training-mediated changes in protein mass
and the [myosin heavy chain (MHC) isoform] composition of
skeletal muscle fibers alter (i.e., increase) their intrinsic capacity to generate force in response to efferent neural drive.
Certainly factors that (acutely) decrease the force-generating
capacity of the peripheral musculature, such as muscle fiber
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J Appl Physiol • VOL
FVI) was maintained, even at the highest frequencies. In
contrast, as the pace of the movements was elevated, the
activity in FDS and EDC increased in overall intensity, and it
became either tonic or intermittent. As training proceeded, and
performance improved, alterations in muscle coordination
were expressed primarily in the extrinsic muscles (EDC and
FDS). These changes took the form of increases in the postural
role of these muscles, shifts to phasic patterns of activation, or
selective disengagement of these muscles (12). Although performance of the task improved in every instance, the fact that
the nature of the adaptive change was quite distinct for the
various individuals who participated in the study, corroborates
the view that the suppression of intrinsic muscle synergies can
only be achieved via complex, and often idiosyncratic, neural
control strategies. It seems reasonable to conclude that programs of training that engage muscles in patterns of activation
that are not promoted by intrinsic synergies and thus require
the development of novel strategies of control, also promote
flexibility in the subsequent recruitment of these muscles in
other task contexts. The evidence to be considered in the
following section suggests, however, that when intrinsic muscle synergies are reinforced by repetitive and stereotypical
(resistance) training regimes, enhancement of the facility to
recruit the trained muscles in other task contexts cannot be
assumed.
HEBBIAN ADAPTATION
Neurons that fire together wire together. Although synergies
represent the building blocks of our repertoire of voluntary
movements, the acquisition of novel motor skills is necessarily
based on their recomposition. It is clear, however, that this
process requires that highly refined patterns of descending
control be instantiated, to counteract protogenic muscle recruitment patterns, subject to habitual reinforcement, that might
otherwise interfere with the desired movement outcome. It
would be surprising, therefore, if training movements that
required the activation of muscles in habitual patterns were
also able to promote their flexible recruitment in other task
contexts.
In 1949, Donald Hebb (22) introduced the idea that connections between cortical neurons are strengthened to the degree
that they are active simultaneously.
When an axon of cell A is near enough to excite a cell B and
repeatedly or persistently takes part in firing it, some growth
process or metabolic change takes place in one or both cells
such that A’s efficiency, as one of the cells firing cell B, is
increased.
The concept that “neurons that fire together, wire together,”
as depicted schematically in Fig. 3A, is now a central tenet of
developmental neuroscience, and it is supported by empirical
evidence that for neurons that release action potentials at the
same time, there is an increased probability that synaptic
connections will be formed. Associations required by the
eliciting “behavioral” context are thus retained, whereas others
are eliminated. By the same token, it is assumed that uncorrelated activity diminishes functional connectivity. Although
these processes are thought to play an important role in
cognitive and linguistic development (e.g., Ref. 39), there are
circumstances in which they can lead to undesirable consequences. In extreme examples such as epilepsy, neurons that
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activation of muscles in ways not favored by intrinsic synergies
may in principal promote flexibility in the subsequent recruitment of these muscles in other task contexts and thus enhance
their functional capabilities. It is evident, however, that only a
small subset of all possible muscle combinations is employed
in the regulation of movement. The muscle synergies represented by these combinations appear particularly sensitive to
biomechanical factors, including the force-generating capabilities of the individual muscles acting on the limb (35) and their
respective muscle moment arms. Necessarily, therefore, the
subspace of possible muscle combinations that can be accessed
during training is highly constrained.
An illustrative example. The nature of the constraints on
training that are imposed by the presence of intrinsic muscle
synergies may be illustrated by a sensorimotor coordination
task that at first glance may appear to lack the complexity of
movements that are employed in the course of daily living.
Nonetheless, it affords a clear view of principles that apply
more generally. When first asked to generate rhythmic abduction-adduction movements of the index finger (about the metacarpal-phalangeal joint) in time with the beat of a metronome,
most individuals exhibit involuntary spontaneous transitions to
rotary motion of the finger and ultimately to flexion-extension,
as the frequency of movement is increased (28). The undesired
behavior arises as a direct consequence of the fact that abduction-adduction movements of the fingers can be brought about
only via complex neural control strategies that must serve to
inhibit the expression of basal (i.e., intrinsic) muscle synergies.
An analysis of musculoskeletal anatomy suggests that the
side-to-side motion of the fingers demanded by the coordination task can be brought about by the action of muscles
intrinsic to the hand: the first dorsal interosseus (FDI) and the
first volar interosseus (FVI). Yet muscles originating in the
forearm, which act primarily to flex and extend the finger such
as extensor digitorum communis (EDC) and the index finger
portion of flexor digitorum superficialis (FDS), also have the
potential to contribute to abduction and adduction (e.g., Ref.
52). On initial exposure to the abduction-adduction task, efferent drive is not simply directed to the interossei; the extrinsic
muscles originating in the forearm are also engaged. Because
most individuals are incapable of directing focal motor commands to the intrinsic hand muscles alone as the frequency of
movement is increased, and the force-generating capacity of
the forearm muscles is substantially greater than that of the
interossei, their recruitment ultimately results in motion that is
dominated by their major moment arms: i.e., flexion and
extension (12).
In a recent study (12; illustrated schematically in Fig. 2), we
sought to assess the patterns of muscle coordination that are
implemented by the CNS, not only on initial exposure to this
task but also after an intensive training period. Five sessions,
each consisting of 20 trials, were conducted on successive
days. In each trial, the participants attempted to produce
abduction-adduction movements as the frequency of a pacing
metronome was increased. EMG activity was recorded from
FDI, FVI, FDS, and EDC. By the final day of the training
period, the movements more accurately matched the required
profile (i.e., abduction-adduction), and they exhibited greater
spatial and temporal stability than those generated during
initial performance. In the early stages of training, an alternating pattern of activation in the intrinsic hand muscles (FDI and
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are activated synchronously during seizures exhibit chronic
adaptations such as axonal sprouting. Hebbian adaptation may
strengthen the neural response that is generated by a specific
input; however, this is only useful if the elicited response is
appropriate to the context in which the desired behaviour will
ultimately be expressed. In circumstances in which a dissimilar
response would be more appropriate, Hebbian reinforcement
can have deleterious consequences.
It is now generally recognized that the effectiveness with
which resistance training-induced adaptations transfer to other
functional tasks depends on the similarity between the muscle
coordination that is consolidated through the regular performance of the training exercise and that which is required to
meet movement goals that are defined in the pursuit of other
activities (e.g., Ref. 41). It is anticipated that positive transfer
will occur in circumstances in which the specific muscle
activation patterns reinforced through training are also those
required in the alternative task context. In the event that the
activation patterns reinforced by training are inconsistent with
J Appl Physiol • VOL
those required by the target behavior, negative transfer is likely
to occur. We have proposed previously that the potential for
negative transfer may in principle be reduced by the implementation of specific control mechanisms mediated by the
higher brain centers (7). These may include the regulation of
inhibitory intracortical pathways that are believed to mediate
surround inhibition in the motor system (e.g., Ref. 50).
The mediating role of feedback. Although Hebbian mechanisms appear to provide a promising basis on which to account
for various aspects of neural adaptation, including long-term
potentiation, it is now evident that this framework is not fully
sufficient to account for changes in behavior without elaboration to encompass sensitivity to outcome information. In contemporary analyses (e.g., Ref. 38), consideration has been
given to the means by which an inherently Hebbian adaptive
process may be guided by superordinate control schemes,
based on the provision of feedback on which potential outcomes may be discriminated. The key insight in this regard,
which is of particular relevance in relation to adaptations to
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Fig. 2. In generating alternating abduction (abd) and adduction (add) movements of the index fingers, efferent drive (¥) is directed to the intrinsic hand muscles
first dorsal interosseus (FDI) and first volar interosseus (FVI). These muscles exhibit a reciprocal pattern of activation (the interneurons that mediate reciprocal
inhibition are represented by the F). In addition, efferent drive is directed to extensor digitorum communis (EDC) and the index finger portion of flexor digitorum
superficialis (FDS), because these muscles also have the potential to contribute to abduction and adduction of the finger (cf. Ref. 32). In circumstances in which
low-force or low-velocity movements are required, and the level of efferent drive is relative low (A), the side-to-side motion of the fingers demanded by the
coordination task can be brought about by the action of muscles intrinsic to the hand. When movements of higher force or velocity are demanded (B), because
most individuals are incapable of directing focal motor commands to the intrinsic hand muscles alone, and the force-generating capacity of the forearm muscles
is substantially greater than that of the interossei, their recruitment ultimately results in motion that is dominated by their major moment arms, i.e., flexion and
extension. deg, Degree.
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training (as illustrated schematically in Fig. 3), is the recognition that, in the presence of the appropriate sensory guidance,
it is possible to gate Hebbian plasticity (e.g., Ref. 42).
In a recent experiment conducted in our laboratory (1), we
examined the impact of resistance training on the coordinated
production of force by older adults. Thirty individuals completed a visually guided aiming task to a range of targets that
required the precise generation of isometric torque in 2 degrees
of freedom (i.e., pronation-supination and flexion-extension)
about the elbow, both before and after a 4-wk training period.
Groups of six participants were allocated to two progressive
[40 –100% maximal voluntary contraction (MVC)] resistancetraining (PRT) groups, to two constant low-load (10% MVC)
training groups (CLO), and to one no-training control group.
Separate groups of six participants in the PRT and CLO
cohorts performed training movements that required either the
generation of combined flexion and supination torques or the
combined extension and supination torques. These specific
combinations were selected because in combined flexion and
supination the biceps brachii acts as an agonist in both degrees
of freedom, whereas, in flexion and pronation, this muscle is an
agonist for flexion but is an antagonist with respect to pronation. It was presumed therefore that, with respect to this muscle
at least, the generation of combined flexion and supination
would serve to reinforce an existing synergy, whereas combined flexion and pronation would require a novel strategy of
control. In each case, the training movements were guided by
the provision of continuous visual feedback of the level of
torque currently being applied in each degree of freedom. A
critical finding was that the improvements in the performance
J Appl Physiol • VOL
of the visually guided aiming task exhibited by the participants
who trained with low loads were more consistent than those
realized by the group that had trained with progressively
increasing loads. Most notably, the group that generated combined flexion and supination during training with progressively
increasing loads exhibited a decrease in performance (an increase in target-acquisition time) when a pure supination
movement was subsequently required in the transfer task. No
such deficits were observed for the group that performed
precisely the same training combination at low loads.
With regard to the flexion-supination training group, when
the level of torque required was relatively low (10% MVC), the
provision of visual feedback of the training movement appears
to have been sufficient to engender positive transfer to the
aiming task. In contrast, in circumstances in which the level of
torque required by the training task was substantial (40 –100%
MVC), there was evidence of negative transfer. These findings
are amenable to interpretation in terms of a Hebbian referenced
analysis (e.g., Ref. 56). In this regard, the (flexion-supination)
training task can be characterized in terms of the operation of
two concurrent processes. It would be anticipated that the
frequent repetition of a recruitment pattern subserved by an
intrinsic muscle synergy would further consolidate functional
connectivity within the corresponding neural networks (e.g.,
Ref. 34). In so much as the level of activity is thought to be a
critical determining factor in Hebbian adaptation, the level of
consolidation induced by this means is likely to have been
greater for those participants who generated contractions of
high, and progressively increasing, intensity than for those who
applied low levels of force. A further important aspect of the
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Fig. 3. Hebbian adaptation encapsulates the
premise that connections between cortical neurons are strengthened to the degree that they are
active simultaneously. In the top row, 2 cells A
and B that are engaged in the context of a
training task are shown exhibiting synchronous
spike trains. In the event that Hebbian adaptation
occurs (the thickness of the arrows linking A and
B denotes the strength of the synaptic connections), the functional connections between the 2
cells will be strengthened as the training
progresses (A). In the event, however, that there
occurs gating of Hebbian adaptation via superordinate control based on sensory guidance (B),
the functional connections between cell A and
cell B may not be strengthened as a consequence
of training.
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training protocol employed in the Barry and Carson study (1)
was the provision of continuous and precise information concerning the progression of the training movements (i.e., the
level of torque applied in each degree of freedom). Thus to the
extent that the training task engaged superordinate control
processes based on the provision of precise sensory (visual)
feedback, a means was also provided of gating Hebbian plasticity (e.g., Ref. 38). The relative balance between these two
processes is likely to have been quite different for the two
flexion-supination training groups. For those who generated
high-force contractions, any consolidation of the functional
connectivity underlying the intrinsic muscles synergies on the
basis of Hebbian type adaptation is likely to have been dominant. In contrast, for the group that applied relatively low levels
of force, the provision of augmented feedback may have
permitted adequate gating of Hebbian type adaptive processes
and may have promoted greater subsequent flexibility in the
recruitment of the trained muscles in other task contexts.
In seeking to illustrate the nature of the constraints imposed
by the organization of the CNS on the changes in muscle
coordination induced by training, three core concepts have
been discussed: activity-dependent coupling, the composition
of muscle synergies, and Hebbian adaptation. It was argued
that training-invoked variations in the efficiency with which
motor actions can be generated influence the stability of coordination by altering the potential for activity-dependent coupling between the cortical representations of the focal muscles
recruited in a movement task and brain circuits that do not
contribute directly to the required behavior. The point was also
made that the range of behaviors that can be generated during
training is constrained by the composition of existing intrinsic
muscle synergies. In circumstances in which attempts to produce forceful or high-velocity movements would otherwise
result in the generation of inappropriate action patterns, training designed to promote the development of control strategies
that are specific to the desired movement outcome may be
necessary to compensate for vagaries in the force-generating
capacities of the muscles engaged by intrinsic synergies. It was
also shown that, in the absence of superordinate control based
on sensory feedback, there exists the possibility that the functional neural connectivity reinforced by the repetitive execution of movement patterns that are supported by intrinsic
muscle synergies, may be ill suited to the subsequent decomposition of these synergies, as may be required by other goal
directed purposeful actions.
ACKNOWLEDGMENTS
I take this opportunity to acknowledge the contributions of Tim Carroll,
Ben Barry, and Jon Shemmell, who helped shape my thinking with regard to
the issues covered in the present review, and initiated some of the related
experimental work that was conducted in the Perception and Motor Systems
Laboratory at the University of Queensland. Appreciation is also extended to
Simon Gandevia, and three anonymous reviewers, for their useful comments
on a previous version of this manuscript.
REFERENCES
1. Barry BK and Carson RG. Transfer of resistance training to enhance
rapid coordinated force production by older adults. Exp Brain Res 159:
225–238, 2004.
J Appl Physiol • VOL
101 • NOVEMBER 2006 •
www.jap.org
Downloaded from http://jap.physiology.org/ by 10.220.32.246 on June 16, 2017
GENERAL SUMMARY
2. Bawa P, Chalmers GR, Jones KE, Sogaard K, and Walsh ML. Control
of the wrist joint in humans. Eur J Appl Physiol 83: 116 –127, 2000.
3. Bernstein NA. The Coordination and Regulation of Movements. London:
Pergamon, 1967.
4. Blinkenberg M, Bonde C, Holm S, Svarer C, Andersen J, Paulson OB,
and Law I. Rate dependence of regional cerebral activation during
performance of a repetitive motor task: a PET study. J Cereb Blood Flow
Metab 16: 794 – 803, 1996.
5. Burke RE. Motor unit types of cat triceps surae muscle. J Physiol 193:
141–160, 1967.
6. Carroll TJ, Barry B, Riek S, and Carson RG. Resistance training
enhances the stability of sensorimotor coordination. Proc R Soc Lond B
Biol Sci 268: 221–227, 2001.
7. Carroll TJ, Riek S, and Carson RG. Neural adaptations to resistance
training—implications for movement control. Sports Med 31: 829 – 840,
2001.
8. Carroll TJ, Riek S, and Carson RG. The sites of neural adaptation
induced by resistance training in humans. J Physiol 544: 641– 652, 2002.
9. Carson RG. A simple and unified approach to human voluntary movements. J Mot Behav 36: 378 –380, 402– 407; discussion 408 – 417, 2004.
10. Carson RG. Governing coordination: Why do muscles matter? In: Coordination Dynamics: Issues and Trends, edited by Jirsa VK and Kelso JAS.
Berlin: Springer-Verlag, 2004, p. 141–154.
11. Carson RG. Neuromuscular-skeletal constraints upon the dynamics of
perception-action coupling. Exp Brain Res 110: 99 –110, 1996.
12. Carson RG and Riek S. Changes in muscle recruitment patterns during
skill acquisition. Exp Brain Res 138: 71– 87, 2001.
13. Carson RG and Riek S. The influence of joint position on the dynamics
of perception-action coupling. Exp Brain Res 121: 103–114, 1998.
14. Carson RG, Riek S, and Shahbazpour N. Central and peripheral
mediation of human force sensation following eccentric or concentric
contractions. J Physiol 539: 913–925, 2002.
15. Cheney PD, Fetz EE, and Mewes K. Neural mechanisms underlying
corticospinal and rubrospinal control of limb movements. Prog Brain Res
87: 213–252, 1991.
16. Dai TH, Liu JZ, Sahgal V, Brown RW, and Yue GH. Relationship
between muscle output and functional MRI-measured brain activation.
Exp Brain Res 140: 290 –300, 2001.
17. Feige B, Aertsen A, and Kristeva-Feige R. Dynamic synchronization
between multiple cortical motor areas and muscle activity in phasic
voluntary movements. J Neurophysiol 84: 2622–2629, 2000.
18. Gabriel DA, Kamen G, and Frost G. Neural adaptations to resistive
exercise: mechanisms and recommendations for training practices. Sports
Med 36: 133–149, 2006.
19. Gandevia SC, Petersen N, Butler JE, and Taylor JL. Impaired response
of human motoneurones to corticospinal stimulation after voluntary exercise. J Physiol 521: 749 –759, 1999.
20. Gelfand IM and Tsetlin ML. On mathematical modeling of the mechanisms of the central nervous system. In: Models of the Structural-Functional Organization of Certain Biological Systems, edited by Gelfand IM,
Gurfinkel SV, Fomin SV, and Tsetlin ML. Moscow: Nauka, 1966, p.
9 –26.
21. Gordon AM, Huxley AF, and Julian FJ. The variation in isometric
tension with sarcomere length in vertebrate muscle fibres. J Physiol 184:
170 –192, 1966.
22. Hebb DO. The Organization of Behavior: A Neuropsychological Theory.
New York: Wiley, 1949.
23. Heckman CJ. Active conductances in motoneuron dendrites enhance
movement capabilities. Exerc Sport Sci Rev 31: 96 –101, 2003.
24. Hufnagel A, Jaeger M, and Elger CE. Transcranial magnetic stimulation: specific and non-specific facilitation of magnetic motor evoked
potentials. J Neurol 237: 416 – 419, 1990.
25. Humphrey DR. Representation of movements and muscles within the
primate precentral motor cortex: historical and current perspectives. Fed
Proc 45: 2687–2699, 1986.
26. Jamison JC and Caldwell GE. Muscle synergies and isometric torque
production: influence of supination and pronation level on elbow flexion.
J Neurophysiol 70: 947–960, 1993.
27. Jensen JL, Marstrand PC, and Nielsen JB. Motor skill training and
strength training are associated with different plastic changes in the central
nervous system. J Appl Physiol 99: 1558 –1568, 2005.
28. Kelso JAS, Buchanan JJ, DeGuzman GC, and Ding M. Spontaneous
recruitment and annihilation of degrees of freedom in biological coordination. Phys Lett A 179: 364 –371, 1993.
Invited Review
1513
MUSCLE COORDINATION
J Appl Physiol • VOL
43. Schlaug G, Sanes JN, Thangaraj V, Darby DG, Jancke L, Edelman
RR, and Warach S. Cerebral activation covaries with movement rate.
Neuroreport 7: 879 – 883, 1996.
44. Schneider C, Devanne H, Lavoie BA, and Capaday C. Neural mechanisms involved in the functional linking of motor cortical points. Exp
Brain Res 146: 86 –94, 2002.
45. Schuster HG and Wagner P. A model for neuronal oscillations in the
visual cortex. 1. Mean-field theory and derivation of the phase equations.
Biol Cybern 64: 77– 82, 1990.
46. Schuster HG and Wagner P. A model for neuronal oscillations in the
visual cortex. 2. Phase description of the feature dependent synchronization Biol Cybern 64: 83– 85, 1990.
47. Shemmell J, Tresilian JR, Riek S, Barry BK, and Carson RG.
Neuromuscular adaptation during skill acquisition on a two degree-offreedom target-acquisition task: dynamic movement. J Neurophysiol 94:
3058 –3068, 2005.
48. Siemionow V, Yue GH, Ranganathan VK, Liu JZ, and Sahgal V.
Relationship between motor activity-related cortical potential and voluntary muscle activation. Exp Brain Res 133: 303–311, 2000.
49. Slobounov S, Johnston J, Chiang H, and Ray W. Movement-related
EEG potentials are force or end-effector dependent: evidence from a
multi-finger experiment. Clin Neurophysiol 113: 1125–1135, 2002.
50. Sohn YH and Hallett M. Surround inhibition in human motor system.
Exp Brain Res 158: 397– 404, 2004.
51. Turner RS, Grafton ST, Votaw JR, Delong MR, and Hoffman JM.
Motor subcircuits mediating the control of movement velocity: a PET
study. J Neurophysiol 80: 2162–2176, 1998.
52. Valentin P. The interossei and the lumbricals. In: The Hand, edited by
Tubiana R. Philadelphia, PA: Saunders, 1981, p. 244 –254.
53. Vallbo AB and Wessberg J. Organization of motor output in slow finger
movements in man. J Physiol 469: 673– 691, 1993.
54. Varela F, Lachaux JP, Rodriguez E, and Martinerie J. The brainweb:
phase synchronization and large-scale integration. Nat Rev Neurosci 2:
229 –239, 2001.
55. Windhorst U, Burke RE, Dieringer N, Evinger C, Feldman AG, and
Hasan Z. What are the outputs of motor behavior and how are they
controlled? In: Motor Control: Concepts and Issues, edited by Humphrey
DR and Freund H-J. New York: Wiley, 1991, p. 101–119.
56. Wolters A, Sandbrink F, Schlottmann A, Kunesch E, Stefan K, Cohen
LG, Benecke R, and Classen J. A temporally asymmetric Hebbian rule
governing plasticity in the human motor cortex. J Neurophysiol 89:
2339 –2345, 2003.
101 • NOVEMBER 2006 •
www.jap.org
Downloaded from http://jap.physiology.org/ by 10.220.32.246 on June 16, 2017
29. Kinsbourne M and Hicks RE. Mapping functional cerebral space:
competition and collaboration in human performance. In: Asymmetrical
Function of the Brain, edited by Kinsbourne M. Cambridge, UK: Cambridge University Press, 1978, p. 267–273.
30. Lemon R. The output map of the primate motor cortex. Trends Neurosci
11: 501–506, 1988.
31. Li Y, Levin O, Carson RG, and Swinnen SP. Bimanual coordination:
constraints imposed by the relative timing of homologous muscle activation. Exp Brain Res 156: 27–38, 2004.
32. Li ZM, Pfaeffle HJ, Sotereanos DG, Goitz RJ, and Woo SL. Multidirectional strength and force envelope of the index finger. Clin Biomech
(Bristol, Avon) 18: 908 –915, 2003.
33. Liddel EG and Sherrington CS. Recruitment and some other factors of
reflex inhibition. Proc R Soc Lond B Biol Sci 97: 488 –518, 1925.
34. Liepert J, Terborg C, and Weiller C. Motor plasticity induced by
synchronized thumb and foot movements. Exp Brain Res 125: 435– 439,
1999.
35. Loeb EP, Giszter SF, Saltiel P, Bizzi E, and Mussa-Ivaldi FA. Output
units of motor behavior: an experimental and modeling study. J Cogn
Neurosci 12: 78 –97, 2000.
36. Lorenzano C, Gilio F, Inghilleri M, Conte A, Fofi L, Manfredi M, and
Berardelli A. Spread of electrical activity at cortical level after repetitive
magnetic stimulation in normal subjects. Exp Brain Res 147: 186 –192,
2002.
37. Luppino G and Rizzolatti G. The organization of the frontal motor
cortex. News Physiol Sci 15: 219 –224, 2000.
38. McClelland JL. How far can you go with Hebbian learning, and when
does it lead you astray? In: Processes of Change in Brain and Cognitive
Development: Attention and Performance XXI, edited by Munakata Y and
Johnson MH. Oxford, UK: Oxford University Press, 2006.
39. McClelland JL. The interaction of nature and nurture in development: a
parallel distributed processing perspective. In: International Perspectives
on Psychological Science: Leading Themes edited by Bertelson P, Eelen P,
and D’Ydewalle G. Hillsdale, NJ: Erlbaum, 1994, p. 57– 88.
40. Petersen NT, Taylor JL, Butler JE, and Gandevia SC. Depression of
activity in the corticospinal pathway during human motor behavior after
strong voluntary contractions. J Neurosci 23: 7974 –7980, 2003.
41. Rutherford OM and Jones DA. The role of learning and coordination in
strength training. Eur J Appl Physiol Occup Physiol 55: 100 –105, 1986.
42. Salinas E and Abbott LF. Transfer of coded information from sensory to
motor networks. J Neurosci 15: 6461– 6474, 1995.