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J Appl Physiol 104: 1656-1664, 2008. First published April 10, 2008; doi:10.1152/japplphysiol.01351.2007
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Unilateral practice of a ballistic movement causes bilateral increases in performance and corticospinal excitability

Timothy J. Carroll,1,2 Michael Lee,1 Marlene Hsu,1 and Janel Sayde1

1Health and Exercise Science, School of Medical Sciences, University of New South Wales, Sydney, New South Wales, and 2School of Human Movement Studies, University of Queensland, Brisbane, Queensland, Australia

Submitted 20 December 2007 ; accepted in final form 1 April 2008


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
It has long been known that practicing a task with one limb can result in performance improvements with the opposite, untrained limb. Hypotheses to account for cross-limb transfer of performance state that the effect is mediated either by neural adaptations in higher order control centers that are accessible to both limbs, or that there is a "spillover" of neural drive to the opposite hemisphere that results in bilateral adaptation. Here we address these hypotheses by assessing performance and corticospinal excitability in both hands after unilateral practice of a ballistic finger movement. Participants (n = 9) completed 300 practice trials of a ballistic task with the right hand, the aim of which was to maximize the peak abduction acceleration of the index finger. Practice caused a 140% improvement in right-hand performance and an 82% improvement for the untrained left hand. There were bilateral increases in the amplitude of responses to transcranial magnetic stimulation, but increased corticospinal excitability was not correlated with improved performance. There were no significant changes in corticospinal excitability or task performance for a control group that did not train (n = 9), indicating that performance testing for the left hand alone did not induce performance or corticospinal effects. Although the data do not provide conclusive evidence whether increased corticospinal excitability in the untrained hand is causally related to the cross-transfer of ballistic performance, the finding that ballistic practice can induce bilateral corticospinal adaptations may have important clinical implications for movement rehabilitation.

motor control; training; transcranial magnetic stimulation; human; motor cortex

THERE IS AN EXTENSIVE LITERATURE, stemming from the mid 19th century, that unilateral motor practice can result in bilateral performance improvements (see Refs. 1, 2, 36). This effect has been variously termed "cross-transfer," "cross-education," and "interlimb transfer," and it has been demonstrated for a wide range of motor tasks including mirror tracing, movement tasks under visuomotor rotations and novel force field conditions, execution of multifinger tapping sequences, exertion of maximal force, and tasks requiring fine control of movement timing and force (e.g., Refs. 3, 11, 32, 33, 41, 43, 44). Most theoretical attempts to account for cross-transfer are based on the idea that the neural adaptations underlying improved performance with the trained limb must reside at a central nervous system (CNS) site that is also accessible for the control of the contralateral limb (e.g., Refs. 15, 21, 42). Here we test an alternative hypothesis, proposed by Parlow and Kinsbourne (30), that certain types of cross-transfer occur because practice induces bilateral neural adaptations (i.e., in the control systems for both limbs). According to this hypothesis, task execution during practice results in a "spillover" of neural activity to the control system of the passive limb, which ultimately results in bilateral neural reorganization.

The spillover hypothesis is based on evidence that there are extensive interactions between the two cerebral hemispheres, and between spinal circuits in opposite hemicords, during unilateral movement. Imaging studies indicate that motor centers in both cerebral hemispheres are active during unilateral muscle contraction (7, 9, 17, 19), and studies involving transcranial magnetic stimulation (TMS) demonstrate that ipsilateral motor cortex excitability is suppressed by weak unilateral contractions (22, 23, 37) and that it is facilitated by high-force contractions (13, 14, 38). Strong ipsilateral contractions also depress intracortical inhibition (25). Importantly, the scale of these ipsilateral cortical effects is proportional to force production: the greater the force of unilateral contraction, the larger the effect on the opposite hemisphere (9, 14, 25). At a segmental level, movements performed with one limb typically result in depression of the central gain of the Ia afferent reflex pathway (4, 6, 14). There are also crossed interactions between inhibitory interneurons that receive inputs from primary muscle afferents (8, 16, 34).

Because high-force contractions promote strong interhemispheric interactions, the spillover hypothesis fits well as a possible explanation for the bilateral improvements in muscular strength that can occur in response to unilateral exercise involving high-force contractions (i.e., strength training). This contralateral strength training effect is a form of cross-transfer that has been known since 1894 (36). Meta-analysis indicates that the average size of the strength increase in the untrained limb is ~8% of its pretraining strength, or 35–50% of the strength gain of the trained limb (3, 28). The relatively small functional improvements involved have resulted in skepticism regarding the potential clinical benefits of the contralateral strength training effect for conditions such as hemiparesis (3). However, if unilateral strength training induces neural adaptations in the ipsilateral hemisphere, it is possible that rehabilitation protocols could be designed to exploit the phenomenon to improve patient outcomes.

In the present study, we tested the spillover hypothesis by assessing performance and cortical excitability for both hands after subjects practiced a ballistic finger movement task with their right index finger. Similar training tasks have been shown to cause rapid improvements in motor performance that are mediated by adaptations in the primary motor cortex (M1) (26, 27, 45). For example, consolidation of practice-related performance gains is prevented if a repetitive TMS protocol known to reduce cortical excitability is applied to M1 immediately after practice (27), and long-term potentiation-like adaptation in M1 is suppressed by prior ballistic training (45). Furthermore, corticospinal excitability only increases in response to ballistic motor practice if there is an improvement in motor performance (26). Thus if cross-limb transfer of ballistic skill is mediated by spillover mechanisms, an increase in corticospinal excitability on the untrained side might be expected. Duque et al. (10) showed that unilateral practice of the ballistic finger movement task causes task-related cortical adaptations in the hemisphere ipsilateral to the trained hand, but they did not assess task performance with the untrained hand. In the present study, we sought to establish whether adaptations in the untrained corticospinal system are related to improved performance with the untrained limb to test the spillover hypothesis as an explanation for the transfer of ballistic motor performance. Study of ballistic tasks may also provide information that is relevant to the mechanisms that underlie the contralateral strength training effect, because optimal performance on both strength and ballistic tasks requires subjects to direct maximal drive to agonist and synergist muscles while minimizing drive to antagonists.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Subjects.   Eighteen people (7 men, 11 women, aged 18–39 yr) with no documented neurological disease participated in this experiment after providing written, informed consent to the procedures. Each person was randomly assigned to a training group (n = 9) or a control group (n = 9). All members of the control group were right handed, while the training group comprised six right handers, two left handers, and one ambidextrous individual (29). The procedures conformed to the Declaration of Helsinki and were approved by the Human Research Ethics Committee at the University of New South Wales.

Overview.   The study was designed to test the effects of motor practice performed with the right hand on subsequent performance and corticospinal excitability for both the left and right hands. The testing procedure is described schematically in Fig. 1. Corticospinal excitability was first assessed in both hands via TMS. Electromyographic (EMG) responses to supramaximal peripheral nerve stimulation (maximal M waves; Mmax) were also recorded for normalization purposes. The order of testing was randomized between the left and right hands. After baseline excitability measures were completed, left-hand performance on the ballistic motor task was measured. Subjects in the training group subsequently performed 150 movements with the right hand, whereas control subjects rested for an equivalent period (12 min). After the training period, corticospinal excitability and Mmax were remeasured in both hands, and task performance with the left hand was retested. A second block of 150 practice trials (training group), or rest (control group), was followed by a final assessment of corticospinal excitability and left-hand performance. This study design was chosen to prioritize the comparisons between left-hand effects for the training and control groups, because the primary aim was to determine whether unilateral training caused significant performance and corticospinal excitability effects on the untrained side. However, the degree of transfer from the right to the untrained left hand of the training group may have been underestimated, because the time of performance assessment and availability of feedback were different for the two hands.


Figure 1
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  		Fig. 1. Schematic representation of the experimental protocol for the training and control groups. Small arrows represent maximal M-wave (Mmax) testing, and large arrows represent transcranial magnetic stimulation (TMS) testing for both the left and right hands. The order of testing was randomised between hands. Dark columns represent performance testing on the ballistic movement task for the left hand (each column depicts 10 trials). No external feedback was provided in these blocks. Light columns represent training on the movement task with the right hand (each column depicts 10 trials). Feedback of the peak acceleration attained was provided after every trial in these blocks. L, left; R, right; LH test, left- hand performance testing; RH training; task practice with the right hand.

 
Motor task.   The motor task required subjects to maximize the peak acceleration produced during ballistic abduction movements of the right index finger. The hands were secured in a custom-designed rig that restricted movement to the second metacarpal-phalangeal joint. Movements were paced at 0.5 Hz by a visual stimulus (green light on a computer monitor), and 30-s rest periods were provided after every 10 efforts. Triaxial accelerometers (Dytran Instruments, Chatsworth, CA) were attached to both index fingers via splints to align approximately with the distal interphalangeal joint. During training, a digital display of peak acceleration from the previous two trials was provided after each effort. Participants were instructed to attempt to increase the peak acceleration recorded in the previous trial on every subsequent movement. During testing of left hand performance, no feedback was provided and participants were instructed to "move as fast as you can."

EMG.   Surface EMG recordings were taken via 1-cm2 self-adhesive electrodes (Ag-AgCl) from the left and right first dorsal interossei (FDI) and adductor digiti minimi (ADM). A belly-tendon arrangement was used for both muscles; the active electrode was placed on the motor point and the reference on the metacarpal-phalangeal joint. EMG signals were preamplified (gain of 200–500; P511 Grass Instruments, AstroMed) and band-pass filtered (10–1,000 Hz).

TMS and Nerve stimulation.   A Magstim 2002 transcranial magnetic stimulator and a 70-mm-diameter figure of eight coil were used to elicit motor-evoked potentials (MEPs) in FDI and ADM. The optimal coil positions for stimulating the left and right FDI (with posterior to anterior current flow across-the motor strip) were established and marked directly on the scalp. The resting motor threshold (MT) was determined for each hemisphere as the lowest intensity to yield MEPs in FDI (~50 µV) in at least three out of five sweeps. Five sweeps were collected at MT, 10% of the stimulator output above MT, 20% above MT, 30% above MT, and at the maximal output of the stimulator. The interval allowed between subsequent TMS pulses varied randomly between 5 and 7 s. The order of stimulus intensities was kept constant for each person but varied across participants. TMS trials were conducted after Mmax trials so that there would be at least 5 min between the end of each exercise bout and assessment of corticospinal excitability. This ensured that any excitability effects could be attributed to practice-related neural changes rather than prior muscle activity, because postexercise facilitation of MEPs dissipates within 90 s (35). For Mmax testing, the ulnar nerve was stimulated via bipolar surface electrodes at the wrist with a Digitimer DS7A stimulator (0.2-ms pulse width, cathode distal). Current was set at 120% of that necessary to elicit Mmax in the relaxed FDI. All MEPs were normalized to the mean of five Mmax amplitudes recorded at the same time point.

Data acquisition and analysis.   MEP and Mmax data were sampled at 10,000 Hz with a 12-bit National Instruments (Austin, TX) analog-to-digital board interfaced with a computer running custom-written Labview software (National Instruments). Individual sweeps were sampled from 100 ms before stimulation to 200 ms after stimulation. For the ballistic finger movement trials, data were sampled at 1,000 Hz. Each sweep was triggered when the abduction acceleration exceeded 4.9 m/s2, and data were collected from 100 ms before to 300 ms after the trigger. Data analyses were performed offline using custom-written Labview software. The peak-to-peak amplitude of MEP and Mmax were measured between cursors placed at the beginning and end of each waveform.

Acceleration data were low-pass filtered at 50 Hz before analysis. For each trace, cursors were set to specify a window of baseline acceleration before the movement and a window that captured the peak of the acceleration (see Fig. 2 for examples of raw acceleration and for EMG data). The magnitude and time of the peak were calculated. EMG data taken during the motor task were rectified and low-pass filtered at 20 Hz. For the FDI data from the moving hand in each trial, cursors were set and the amplitude and time of the burst peak were determined in the same way as for the acceleration data. The onset of the EMG burst was taken as the first time point after the beginning of the file (i.e., from 100 ms before the trigger for file collection; defined when the acceleration exceeded 4.9 m/s2) at which the acceleration was greater than two times the baseline value. The end of the burst was calculated as the first time point after the peak of the burst at which the EMG amplitude was <0.2 times the peak amplitude. The criteria for establishing the onset and offset of the EMG bursts differed because low-amplitude EMG was often present after the main burst was complete. This late EMG occurred well after the completion of positive finger acceleration, and it was probably associated with cocontraction at the end of joint range. The burst duration was taken as the time at the end of the burst minus the burst onset, and the mean EMG amplitude for the duration of each burst was calculated. Because EMG bursts were often poorly defined for the other three muscles (i.e., the ADM from the moving hand and FDI and ADM from the relaxed hand), mean and peak amplitude were calculated within the time window specified by the burst duration of the active FDI.


Figure 2
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  		Fig. 2. Pretraining (Pre) and midtraining (Mid) examples of raw acceleration and electromyographic (EMG) data taken during task performance with the right and left hands from a representative subject in the training group. FDI, first dorsal interossei; ADM, adductor digiti minimi.

 
Statistics.   All statistical analyses were conducted on the raw values taken at pretraining, midtraining, and posttraining. Percent changes in performance variables from pretraining to midtraining, and pretraining to posttraining are cited in the text to aid description of the data. A two-way ANOVA model (group x time) with repeated measures on the time factor was used to compare peak acceleration between pre-, mid- and post–training for the left and right hands of the training group and the left hand of the control group. Planned contrasts were conducted to assess changes over time for each group with modifications for multiple comparisons according to Keppel (modified Bonferroni, Ref. 18). For all variables extracted during task performance (i.e., acceleration and EMG variables), the mid- and posttraining data were taken as the mean of the final block of 10 trials in each set of 150. A three-way mixed ANOVA model (group x time x stimulation intensity), with repeated measures on time and stimulation intensity factors, was used to examine the effect of practice on MEP amplitudes for both muscles in each hand. Planned contrasts were conducted to detect significant changes in MEP amplitude across-time for each group at each stimulus intensity. For EMG variables extracted during movements, separate one-way ANOVAs were conducted for the left and right hands. Planned contrasts were used to assess changes from pre- to mid-, and mid- to posttraining. Pearson's correlations were also computed between changes in MEP amplitude (at a stimulus intensity of 20% above MT) and peak finger acceleration to test whether any changes in performance were linearly related to changes in corticospinal excitability. Statistical significance was set at P < 0.05 for all tests. All descriptive statistics are reported as means ± SE.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Task performance.   The raw acceleration traces in Fig. 2 show an increase in peak acceleration from pre- to midtraining for a representative subject. For the group, practice of the ballistic movement task with the right hand significantly increased the peak acceleration of the right index finger after 150 (pretraining = 14.0 m/s2; midtraining = 26.8 m/s2; average increase from pretraining = 114%, F1,22 = 28.9, P < 0.0001) and 300 (posttraining = 31.0 m/s2; average increase from pretraining = 140%, F1,22 = 62.8, P < 0.0001) trials (Fig. 3). Peak finger acceleration also significantly increased for movements performed with the left hand as a consequence of right-hand training (pretraining = 15.3 m/s2; midtraining = 22.6 m/s2; posttraining = 25.4 m/s2; average increase from pretraining to midtraining = 50%, F1,22 = 12.8, P = 0.002; average increase from pretraining to posttraining = 82%, F1,22 = 28.8, P < 0.0001), whereas there were no significant changes in finger acceleration for the control group (P > 0.2). There was no significant difference in pretraining performance between the left and right hands of the training group (F1,22 = 0.14, P = 0.71), and the same pattern of results emerged from the analysis if the two left handers and the ambidextrous individual were excluded from the data set.


Figure 3
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  		Fig. 3. Group data for peak index finger acceleration (normalized to initial performance) recorded before, during, and after training for both groups. Each data point represents the mean of 10 trials, and error bars represent the group average of SEs for each set of 10 trials. Trained LH, left-hand performance for the training group; Trained RH, right-hand performance for the training group; Control LH, left-hand performance for the control group. *Significant increases in finger acceleration from pretraining at mid- or posttraining for each group, P < 0.001.

 
Muscle activity during the task.   EMG records taken during the ballistic movements were analyzed to illustrate the changes in muscle activation that accompanied improved task performance. There was no significant change in the amplitude of EMG activity recorded from the right FDI during right-hand task execution (P > 0.2). In contrast, there was a significant increase in the mean amplitude of the rectified and filtered EMG from the left FDI of the training group during task execution with the left hand (midtraining = 15% increase, F1,8 = 5.8, P = 0.04; posttraining = 16% increase, F1,8 = 5.3, P = 0.05). This suggests there was an increase in neural drive to the left hand as a consequence of right hand practice. We also sampled EMG data from the ADM in an attempt to provide information about practice-related changes in the neural control of a muscle not directly involved in task execution. However, there was considerable phasic activity in the ADM of the moving hand during task performance (see Fig. 2), and this activity increased significantly after 300 practice trials in both hands (left hand = 28% increase, F1,8 = 14.5, P = 0.005; right hand = 79% increase, F1,8 = 6.6, P = 0.04). Thus training-associated increases in neural drive occurred in muscles other than the primary agonist for the ballistic movement.

Practice also induced a significant reduction in the delay between the right hand FDI EMG onset and the time to reach 4.9 m/s2 acceleration (used as the criterion for acceleration onset) by the end of the first practice block (pretraining = 39.4 ms; midtraining = 28.4 ms; F1,8 = 16.1, P = 0.004) that was maintained at the posttraining block (posttraining = 29.1 ms; comparison with pretraining F1,8 = 5.4, P = 0.05). There was also a reduction in the time from the onset of FDI EMG to the peak of the enveloped EMG burst in the right hand after 300 trials (pretraining = 63.0 ms; posttraining = 57.0 ms; F1,8 = 7.6, P = 0.03). There was a nonsignificant trend toward a similar result for the left hand of subjects in the training group (pretraining = 70.7 ms; posttraining = 62.5 ms; F1,8 = 4.1, P = 0.08). The results suggest that participants were able to generate maximal neural drive to the right FDI more rapidly after training and that there was a tendency for a similar effect in the untrained left hand.

Figure 2 shows raw traces of finger acceleration and muscle activity for a representative subject. In addition to large EMG bursts in the FDI located in the moving hand, there was occasional low-amplitude EMG activity in the opposite FDI. Across all subjects and trials, the amplitude of this contralateral activity was 5% of that recorded in the active hand. There was no significant change in the amplitude of left FDI EMG during task performance with the right hand during the course of practice (P > 0.2), and there was a lack of correlation between the amplitude of left-hand EMG recorded during right hand practice and the increase in left-hand performance. In contrast, right FDI EMG amplitude was significantly greater during task execution with the left hand by the end of practice (44% increase, F1,8 = 6.4, P = 0.04). There was also a significant increase in the amplitude of right ADM EMG during left-hand movement with training (28% increase, F1,8 = 14.5, P = 0.005). The results for both muscles suggest that there was greater spillover of neural drive to the inactive right hand during task execution with the left hand after learning.

Corticospinal responses to practice.   The mean TMS motor threshold intensity was 40.4 ± 1.6% of stimulator output for the left hand, and 40.6 ± 1.4% of stimulator output for the right hand. The stimulus current required to elicit a maximal M wave was 80.2 ± 6.5 mA for the left ulnar nerve and 82.4 ± 6.1 mA for the right ulnar nerve. Figure 4 shows MEP data from the right FDI for a representative subject in the training group. MEP amplitudes were considerably larger after practice at stimulus intensities of 10, 20, and 30% above threshold for this individual. For the group, MEP amplitude in the right FDI was significantly greater after 150 (at 20% above threshold, F1,14 = 14.1, P = 0.002) and 300 (at 20%, F1,14 = 12.5, P = 0.003; and 30% above threshold, F1,14 = 8.3, P = 0.01) practice trials, whereas there was no significant change for the control group (Fig. 5). A very similar pattern of results occurred for the left hand. MEPs in the left FDI were significantly larger after 150 (at 20%, F1,14 = 13.8, P = 0.002; and 30% above threshold, F1,14 = 8.9, P = 0.01) and 300 trials of right-hand training (at 10%, F1,14 = 5.5, P = 0.04; 20%, F1,14 = 13.8, P = 0.002; and 30% above threshold, F1,14 = 18.8, P = 0.0007). There were no significant correlations between the training induced increases in MEP amplitude and performance for either hand at mid- or posttraining.


Figure 4
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  		Fig. 4. Pre- and midtraining examples of motor-evoked potentials (MEP) evoked by TMS (mean of 5 sweeps at each intensity) taken from the right FDI of a representative subject in the training group. T, resting motor threshold intensity; T+10, 10% stimulator output above resting motor threshold; T+20, 20% stimulator output above resting motor threshold; T+30, 30% stimulator output above resting motor threshold, Max, maximal output of the stimulator. Dashed lines, stimulation.

 

Figure 5
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  		Fig. 5. Group data for the amplitude of MEPs (normalized to Mmax amplitude) recorded in the left and right FDI before, during, and after training. Each data point represents the mean of 5 sweeps at each stimulus intensity, and error bars represent the group average of SEs from the 5 trials for individuals. Post, posttraining; Max, 100% stimulator output. *Significant increases in MEP amplitude from pre- to midtraining, P < 0.05. #Significant increases in MEP amplitude from pre- to posttraining, P < 0.05.

 
Figure 6 shows that there were also significant increases in MEP amplitude for the left ADM muscle after right-hand practice at midtraining (20%, F1,14 = 10.1, P = 0.007; and 30% above threshold, F1,14 = 12.3, P = 0.004; and 100% stimulator output, F1,14 = 9.9, P = 0.007) and posttraining (10%, F1,14 = 7.2, P = 0.02; 20%, F1,14 = 14.4, P = 0.002; and 30% above threshold, F1,14 = 15.1, P = 0.002; and 100% stimulator output, F1,14 = 10.4, P = 0.007). In the right hand, the tendency toward an increase in ADM MEP amplitude was less strong. There were significant increases in MEP amplitude only at 20% above threshold (F1,14 = 4.6, P = 0.05) and at 100% of the stimulator output after 150 trials (F1,14 = 4.4, P = 0.05), and there were nonsignificant trends toward increases at 10 and 20% above threshold after 300 trials (10%, F1,14 = 3.9, P = 0.07; 20%, F1,14 = 3.6, P = 0.08). The same pattern of MEP results emerged from the analysis if the two left handers and the ambidextrous individual were excluded from the data set.


Figure 6
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  		Fig. 6. Group data for the amplitude of MEPs (normalized to Mmax amplitude) recorded in the left and right ADM before, during and after training. Each data point represents the mean of 5 sweeps at each stimulus intensity, and error bars represent the group average of SEs from the 5 trials for individuals. *Significant increases in MEP amplitude from pre- to midtraining, P < 0.05. #Significant increases in MEP amplitude from pre- to posttraining, P < 0.05.

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Some forms of motor practice that can result in bilateral performance gains, such as sequence learning, increase corticospinal excitability only in the hemisphere that is contralateral to the training limb (31, 33). In contrast, the present results indicate that cross-transfer of ballistic motor learning is accompanied by bilateral increases in the excitability of the corticospinal tracts. However, performance improvements were not correlated with increased corticospinal excitability, and there were comparable increases in corticospinal excitability for a muscle not directly involved in task performance. Thus the data do not provide conclusive evidence that the spillover hypothesis is a mechanism that contributes to the cross-transfer of ballistic motor skill. They do, however, extend recent evidence that unilateral ballistic practice can cause lasting effects on ipsilateral cortical excitability (10, 20).

Cross-transfer of performance.   Ballistic movement training with the right hand caused a strong cross-transfer of performance to the left hand in the present study. The magnitude of cross-transfer effects can vary considerably depending on the learning context, from nil transfer to perfect transfer, and it has been argued that the extent of transfer indicates the degree to which the neural substrates of learning are accessible for the control of both limbs (15). The present task was much simpler than those employed in most previous studies, merely requiring subjects to maximize movement acceleration at a single joint under constant sensory and dynamic conditions. The performance improvements of the trained hand on such a simple task are expected to rely on "effector-specific" adaptations, and indeed there is evidence that the learning engrams that underlie improved ballistic performance develop initially in M1 (27, 45). The strong transfer of performance observed here to the untrained hand suggests either that the neural reorganizations induced within the control system for the trained limb are highly accessible to the opposite limb, or that increased corticospinal excitability of projections to the untrained hand reflects task specific neural reorganization that directly contributes to performance transfer (i.e., as predicted by the spillover hypothesis).

An increase in corticospinal excitability in the hemisphere ipsilateral to the trained hand is consistent with the possibility that ipsilateral cortical adaptations underlie performance improvements with the untrained hand. However, we cannot exclude the possibility that the observed ipsilateral increases in MEP amplitude reflect a "generalized" increase in excitability on the untrained side (i.e., that does not directly contribute to improved performance). The observation that corticospinal excitability increased for the ADM in the untrained limb might suggest such a generalized effect, because ADM does not directly contribute to task performance. A lack of correlation between increases in corticospinal excitability and performance gains is also consistent with the possibility of a generalized increase in ipsilateral excitability, although neither point provides conclusive evidence. Further experiments, perhaps involving repetitive TMS, are necessary to establish whether there is a causal link between ipsilateral cortical adaptations and cross-transfer of learning on ballistic movement tasks.

Muscle activity during task performance.   The changes in muscle recruitment may provide insight into the way in which CNS output was refined to improve performance on the ballistic task. The reduced time from EMG burst onset to the peak EMG amplitude (for the FDI in the moving hand) suggests that increased finger acceleration was associated with more rapid generation of maximal neural drive to the primary agonist. Although this effect failed to reach a statistically significant level for the left hand (P = 0.08), the mean amplitude of the left FDI EMG increased. It is possible that faster generation of neural drive to the untrained hand might be reflected by interrelated changes in both EMG timing and amplitude variables. However, the reason for the differences in EMG results for the two hands is unclear. EMG activity also increased in both ADM muscles (during ipsilateral task execution) with training, which indicates that improved performance was associated with increased drive to a functionally related muscle that has no direct influence on movement at the trained joint. This may reflect a movement strategy that is specific to the task (and hand-support rig) involved in the present study, and it may explain why there were increases in the excitability of corticospinal projections to ADM in the present study but not after ballistic finger-thumb opposition (26).

The observation that small EMG signals were often inadvertently produced in the limb contralateral to that engaged in the task is consistent with findings from studies on unilateral contractions of maximal voluntary force (46, 47). Unintended contralateral muscle activity, or "mirror movements," can also be observed during brisk, unilateral finger movements in children, Parkinson's patients, and normal adults (e.g., Refs. 5, 24). The expectation of extensive bilateral corticospinal activation during ballistic or high-force performance is, in fact, the basis for the spillover hypothesis. In the present study, the spillover of corticospinal activity was sufficient to activate contralateral motoneurons. Whether or not overt motoneuron activation is required for the cross-transfer of learning for ballistic or high-force tasks is an open question. However, it seems unlikely that small bursts of EMG could, in themselves, have caused the performance effects, because ballistic practice executed without feedback that does not induce a learning effect has no impact on corticospinal excitability for the trained hand (26).

Possible neural mechanisms underlying increased corticospinal excitability.   The precise cellular mechanisms that mediate persistent changes in corticospinal excitability after motor practice are not known. However, Muellbacher et al. (26) showed that ballistic training-induced increases in MEP amplitude are due to cortical rather than spinal adaptations by contrasting the responses to TMS and cervicomedullary stimulation. This suggests that increased MEP amplitude in the trained hand probably reflects alterations in the properties of circuitry in M1, and/or changes in the effectiveness of inputs to M1 from distant cortical areas. For example, Perez et al. (32) recently showed that the supplementary motor area is crucially important in the expression of cross-limb transfer of sequence learning performance. In contrast, there is no direct evidence to indicate the site of neural adaptation underlying the increase in corticospinal excitability for the untrained hand. Consideration of what is known about the adaptations that occur in the trained hand would favor the possibility that cortical plasticity is involved, because it is difficult to imagine that spinal adaptations would occur in the untrained hemicord, but not the trained hemicord. However, we cannot exclude the possibility spinal adaptations contribute to cross-transfer of ballistic motor skill based on the current data.

The present data support findings of recent studies that unilateral ballistic motor training can cause bilateral changes in corticospinal excitability (10, 20), although the previous studies did not assess performance transfer. Interestingly, Duque et al. (10) reported a reduction in MEP amplitude in the untrained hand in response to unilateral finger abduction practice in which they viewed their moving finger. The effect only occurred when the external direction of abduction movement for the trained finger was opposite to that for the transfer finger (i.e., the 2 fingers moved in equivalent directions in joint space, but they moved opposite directions in externally referenced space). Although the left and right fingers also moved in opposite external directions in the present study, and subjects were not explicitly prevented from viewing their moving finger, the requirement to attend to computer monitor for pacing information and performance feedback discouraged them from watching their movements. This raises the possibility that the characteristics of the crossed effects induced by ballistic practice may be dependent on the nature and availability of visual feedback. Visual information can have task-specific effects on cortical excitability, as demonstrated by the fact that the direction of TMS-evoked twitches is affected by the observation of an external agent performing ballistic finger movements (39, 40).

Clinical considerations.   In contrast to the results for ballistic movement, Perez et al. (33) found no change in the excitability of the ipsilateral motor cortex after right-hand training on an implicit, sequence-learning task. This was despite a significant increase in MEP amplitude for the trained limb, and significant cross-transfer of performance. Thus training involving ballistic movements may have a specialized (or unique) capacity to alter the excitability of the ipsilateral motor cortex. This might be useful to enhance functional capacity in the affected limbs of patients with predominantly unilateral motor deficits (e.g., stroke). The effect may be beneficial whether or not the increase in excitability directly contributes to cross-transfer of performance, because a generalized increase in excitability could conceivably assist in motor retraining by facilitating movement in neurologically affected limbs. It will also be important to establish the precise characteristics of training that are required to cause bilateral excitability increases. In particular, the potential for training involving high-force contractions (i.e., strength training) to influence ipsilateral cortical excitability should be investigated, given the similarities between strength and ballistic task characteristics and the frequent observation of a cross-transfer in strength performance with unilateral training (e.g., 3, 28).

Methodological considerations.   A key aim of the present study was to determine whether unilateral practice of a ballistic task improves performance with the opposite, untrained limb. However, because right-hand performance was assessed during the initial and final blocks of practice, the results may underestimate the degree of interlimb performance transfer. This is because feedback of peak finger acceleration was provided during performance assessment for the right hand (but not the left) and because of a delay in assessing left hand performance due to testing of corticospinal excitability testing. Importantly, an underestimation of the degree of interlimb performance transfer in no way compromises the basic conclusion that unilateral ballistic practice causes strong cross-transfer of learning.

Our random sample included both left- and right-handed individuals. Although hand dominance could influence the mechanisms of motor learning and transfer (e.g., Ref. 12), it is clear that the use of a mixed sample did not confound our basic conclusions because the same pattern of results occurred for both left and right handers. All but one subject (a right hander) showed substantial performance gains in both hands and all but two (different) subjects showed bilateral increases in corticospinal excitability (one right hander had little change in left hemisphere excitability, and another right hander had little change in right hemisphere excitability). Furthermore, if we excluded the non-right-handed subjects from the analyses, the overall pattern of results was identical (despite a reduction in the statistical power of the tests). Nevertheless, it will be important to carefully test whether there are left-right or dominant-non-dominant differences in the degree or mechanisms of inter-limb transfer induced by ballistic training (c.f. Ref. 11).


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The work was supported by the Australian Research Council.


   ACKNOWLEDGMENTS
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 ABSTRACT
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REFERENCES
 
We thank Justin Barton and Ina Janssen for assistance with data analysis and Prof. Simon Gandevia for helpful discussions.


   FOOTNOTES
 

Address for reprint requests and other correspondence: T. J. Carroll, School of Human Movement Studies, The Univ. of Queensland, Brisbane, Queensland 4072, Australia (e-mail: timothy.carroll{at}uq.edu.au)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


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