Breakdown in central motor control can be attenuated by motor practice and neuro-modulation of the primary motor cortex

Neuroscience 220 (2012) 11–18

BREAKDOWN IN CENTRAL MOTOR CONTROL CAN BE ATTENUATED BY MOTOR PRACTICE AND NEURO-MODULATION OF THE PRIMARY MOTOR CORTEX W. P. TEO, J. P. RODRIGUES, F. L. MASTAGLIA AND G. W. THICKBROOM *

mance over time. This deterioration will have various manifestations and causes; however, in many situations the motor cortex or other cortical or sub-cortical regions have been implicated. Even with fatiguing maximal voluntary contraction (MVC) tasks, where the loss of force-generating ability in muscle is the primary mechanism, central changes have been reported that are either attributable to central fatigue (Taylor et al., 2000, 2006) or to central adaptation (Benwell et al., 2006b). A motor task that does not appear to be associated with significant failure in force generation, but which nonetheless rapidly deteriorates, is a repetitive index finger flexion–extension task performed at maximal voluntary rate (MVR) in which movement rate begins to decline just a few seconds into the task (Rodrigues et al., 2009; Teo et al., 2012b). Ballistic speed and isometric strength of finger flexion and extension are preserved after task completion, there is no change in M-wave amplitude, and electromyographic traces from flexor and extensor muscles indicate a steady increase in agonist–antagonist co-contraction during the task. Together, these observations suggest that fatigue of the muscle does not contribute to the decline in movement rate, and that a breakdown in central motor control processes driving rapid rhythmic movement is a more likely mechanism. Transcranial magnetic stimulation (TMS) has shown that changes in corticomotor excitability (CME-as defined by the amplitude of the motor evoked potential (MEP) to a given stimulus intensity) and short interval cortical inhibition (SICI) after the MVR task differ from those after a task performed at a slower and sustainable rate, further supporting a central basis for the decline in movement rate (Teo et al., 2012a,b). While there are limits to MVR performance, if those limits are mainly central there remains the possibility that plasticity-related learning could be harnessed to lessen performance deterioration. Learning is an innate human ability that persists throughout an individual’s lifespan and improvement in motor performance has been demonstrated after just a short practice session that is accompanied by changes in fMRI signals(Karni et al., 1995) and CME (Muellbacher et al., 2001, 2002) and which can be persisting (Pascual-Leone et al., 1994, 1995). One way to confirm that the MVR task is limited centrally would be to endeavor to improve performance of the task with a motor learning paradigm. Although learning is a natural capability of the central nervous system, there is currently much interest in further up-regulating plasticity-related learning with TMS interventions that modulate CME. The number and type of TMS pro-

Australian Neuro-Muscular Research Institute, Centre for Neuromuscular and Neurological Disorders, University of Western Australia, Western Australia, Australia

Abstract—The performance of a repetitive index finger flexion–extension task at maximal voluntary rate (MVR) begins to decline just a few seconds into the task and we have previously postulated that this breakdown has a central origin. To test this hypothesis, we have combined two objectives; to determine whether motor practice can lessen the performance deterioration in an MVR task, and whether further gains can be achieved with a transcranial magnetic stimulation (TMS) protocol that increases corticomotor excitability (CME). Eleven right-handed subjects participated in a randomized crossover study design that consisted of a 15-min interventional TMS at I-wave periodicity (ITMS) and singlepulsed Sham intervention prior to six 10-s practice sets of a repetitive finger flexion–extension task at MVR. Motorevoked potentials (MEPs) were recorded from the first dorsal interosseous muscle. The starting movement rate, and the percentage decline in rate by the end of the MVR were quantitated. Training of the MVR task improved the sustainability of the task by reducing the decline in movement rate. CME increased steadily after each training bout, and this increase was maintained up to 20 min after the last bout. ITMS further increased CME, and was associated with an increase in both the starting rate of the MVR task and its sustainability, when compared to Sham. The results implicate central motor processes in the performance and sustainability of the MVR task, and indicate that MVR kinematics can improve with shortterm training and with non-invasive neuro-modulation. Ó 2012 Published by Elsevier Ltd. on behalf of IBRO. Key words: maximal voluntary rate, practice-dependent plasticity, transcranial magnetic stimulation, spike-timing dependent plasticity.

INTRODUCTION Most, if not all, motor tasks that are performed continuously or repetitively will show some deterioration in perfor*Corresponding author. Address: Australian Neuro-Muscular Research Institute, Centre for Neuromuscular and Neurological Disorders, University of Western Australia, Queen Elisabeth II Medical Centre, Nedlands, WA 6009, Australia. Tel: +61-(08)9346-4479. E-mail address: [email protected] (G. W. Thickbroom). Abbreviations: CME, corticomotor excitability; M1, primary motor cortex; MCP, metacarpophalangeal; MEP, motor-evoked potentials; MVC, maximal voluntary contraction; MVR, maximal voluntary rate; PRE-INT, pre-intervention; TMS, transcranial magnetic stimulation. 0306-4522/12 $36.00 Ó 2012 Published by Elsevier Ltd. on behalf of IBRO. http://dx.doi.org/10.1016/j.neuroscience.2012.06.048 11

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tocols available for neuro-modulation are considerable (Fitzgerald et al., 2006; Thickbroom, 2007), although there are fewer studies that have demonstrated an associated improvement in motor performance. Benwell et al. (2006a) showed that a TMS intervention targeting I-wave dynamics (ITMS) could lessen force-loss during a brief MVC task, and repetitive TMS (rTMS) protocols have demonstrated transient improvements in some parameters of movement that are associated with early motor learning (Muellbacher et al., 2002; Kobayashi et al., 2004; Huang et al., 2005). A further way to confirm that the MVR task is limited centrally would be to demonstrate that neuro-modulatory TMS could further improve performance of the MVR task. In the present study we have combined these two objectives; to show that elementary motor learning can lessen MVR deterioration and that this can be further improved with neuro-modulation. We investigated the kinematics of the MVR task during an elementary motor learning protocol, combined in a crossover design with an ITMS intervention that is known to increase CME or a period of Sham TMS.

EXPERIMENTAL PROCEDURES Subjects A total of 11 subjects (6M 5F, aged 21–29, right-handed) were recruited and provided informed written consent prior to the start of the experiment. The experiment was approved by the University of Western Australia Human Research Ethics Committee and is in conformity with the Declaration of Helsinki. In this study, all subjects practiced an index finger movement task after an ITMS and Sham TMS intervention, separated by a period of a week, in a pseudo-randomized order. Throughout the study, all subjects were seated comfortably with the right hand secured in a modified hand brace and were awake throughout the whole procedure. No subjects reported any ill effects during or after the experiment.

TMS and EMG setup MEPs were recorded from surface electrodes attached over the first dorsal interrosseous (FDI) of the right hand in a belly-tendon arrangement (amplification 1000, band pass 2–20 kHz). Repetitive TMS was performed using a single or paired-pulse paradigm via two magnetic stimulators (Bistim 2002, Magstim Co., UK) linked together and connected to a 7 cm figure-of-eight coil placed over the optimal scalp position (determined by initial exploration) on the contralateral primary motor cortex (M1) in a posterior-anterior direction.

Sham TMS For the Sham TMS intervention, a single pulse of TMS replaced each paired-pulse of the ITMS protocol; with single-pulse TMS delivered every 5 s for 15 min (a total of 180 single stimuli at 0.2 Hz). Stimulus intensity was set so as to elicit an MEP amplitude of 1 mV. Thus, although the total number of stimuli was half that for ITMS, the strength of the response and the subjects perception of the stimulus and response were matched.

Index finger movement task Under both ITMS and Sham conditions, all subjects practiced a movement task for six 10-s practice sets that involved the repetitive flexion and extension of the index finger at MVR. The subject’s right hand was secured to a modified hand brace that only allowed the index finger to have a full range of motion. A light-weighted goniometer (Single Axis Torsiometer Q150, Biometrics Ltd., UK) was attached across the 2nd metacarpophalangeal (MCP) joint of the right index finger to measure movement rate (RATE – Hz) and amplitude (AMP – deg). The goniometer was calibrated to enable data measurement of range of movement over the MCP joint in degrees and was shown to give reproducible results over a range of up to 90°. Data acquisition was done using a custom-written Labview (National Instrument Corporation, Austin, Texas, USA) program running on a personal computer. Prior to practicing the motor task, all subjects were instructed to move their index finger as fast as they could, while trying to maintain both rate and amplitude for the whole 10-s duration. Instructions were also given to the subjects to set the movement AMP at a range that they felt comfortable with.

Experimental procedure The experimental protocol is shown in Fig. 1. Prior to the start of the experiment, a pre-intervention (PRE-INT) baseline MEP measurement was taken using an average of 12 single-pulsed stimuli. After PRE-INT MEPs were taken, subjects performed a single 10-s bout of the MVR task to provide PRE-INT movement rate and amplitude. Once baseline MEPs and movement kinematics were collected, a 15-min intervention phase was administered and subjects were not informed of the nature of intervention that they received. After the intervention period, a post-intervention (POST-INT) baseline was again determined using the average of 12 single-pulsed stimuli. During the Practice phase, all subjects were instructed to perform 6 sets of 10-s MVR repetitive finger flexion and extension motor tasks. Each practice set was separated by a 5-min rest period, in which 12 bouts of singlepulsed stimulation were administered immediately (POST0) and 2 min (POST2) post-task. After the 6th practice set, MEPs were tracked for up to 20 min after task completion. During this phase, 12 TMS stimulus were delivered every 2 min for 10 min and on the 15th and 20th min after POST2 of the last practice set. The whole procedure lasted around 90 min and all subjects returned a week later to repeat the same protocol under a different INT (ITMS or Sham) conditions.

Data and statistical analysis ITMS All subjects received repetitive paired-pulse TMS with an interstimulus interval (ISI) of 1.5 ms delivered every 5 s for 15 min (a total of 180 paired stimuli at 0.2 Hz). In each pair, both stimuli were of the same stimulus intensity and set so that each pair of stimuli would generate a peak-to-peak MEP amplitude of 1 mV. A change in excitability during the intervention was determined by comparing the change in MEPs during the first and last min of the intervention (average of 12 stimuli for each min).

TMS. For each set of 12 single-pulse MEPs collected postINT, peak–peak amplitude was averaged and expressed as a percentage of pre-INT baseline (MEP%). Two-way ANOVAs with repeated measures were used to compare MEP amplitude during and after ITMS and Sham (factor 1 – INT, factor 2 – Time) for each Phase of the experiment (INT, Practice, Tracking).Paired t-tests were employed to test individual time points where indicated.

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W. P. Teo et al. / Neuroscience 220 (2012) 11–18 PRE-INT Baseline

POST-INT Baseline

Tracking Phase

15-min ITMS/ Sham intervention

Intervention Phase

Practice Phase (6 x 10-sec MVR task)

12 single-pulse TMS stimulus 10-sec MVR finger flexion-extension task

Fig. 1. A schematic diagram of the experimental design. At baseline a bout of 12 single-pulsed MEPs were collected and a 10-s MVR task was performed to establish excitability and kinematic measures before TMS intervention and motor practice. The intervention phase consisted of 15 min of either ITMS or single-pulse Sham. 1 min after the end of the intervention phase, a further bout of 12 MEPs were recorded to establish postintervention excitability. Three minutes after the end of the intervention phase, 6 practice sets of the MVR task were commenced, each separated by 5 min of rest. Twelve MEPs were collected immediately (POST0) and at 2 min (POST2) after each practice set. After the last practice set, MEPs continued to be tracked for up to 20 min post-practice.

Fig. 2. MEP% (group mean ± SEM; % pre-intervention baseline) collected during the ITMS and Sham interventions. MEP amplitude increased steadily during ITMS (p < 0.001) but did not change during Sham.

Kinematics. START rate was expressed as a percentage or PRE-INT kinematic baseline. To determine if ITMS influenced START RATE, one-way ANOVA was used to compare any changes across baseline and all practice sets. Any decrements in RATE and AMP were calculated by the ratio between the last 2 s (END) and first 2 s (START) of each set and expressed as a percentage (no change between START and END = 100%; decrease in END = <100%; increase in END = >100%). A twoway ANOVA with repeated measures was used to make comparisons between RATE and AMP (Factor 1 – INT [ITMS vs. Sham]; Factor 2 – Sets [Baseline vs. practice sets]). For all post-hoc analysis of TMS and kinematic measures, t-tests with Bonferroni correction for multiple comparisons were used.

RESULTS CME: INT phase As shown in Fig. 2 there was a significant increase (F(1,70) = 74.7; p < 0.001) in paired-pulse MEPs during ITMS whereas no change was found during Sham. MEPs had increased significantly by the 3rd min of ITMS and continued an upward trend until the 9th min following which no further increments were observed. In the last min of ITMS, MEPs had increased to 252 ± 28.3% of baseline (0.97 ± 0.24 mV vs. 2.52 ± 0.28 mV; 0 min vs. 15th min;

W. P. Teo et al. / Neuroscience 220 (2012) 11–18

POST0 POST2 POST0 POST2 POST0 POST2 POST0 POST2 POST0 POST2 POST0 POST2 POST0 POST2 POST0 POST2 249.4 ± 19%

102.1 ± 18%

ITMS

Sham

– – – –

212.7 ± 10% 188.3 ± 14.7% 129.6 ± 8.9% 121.5 ± 8.7% POST0 POST2 POST0 POST2

– – – –

232.8 ± 11.1% 215.9 ± 16.9% 142.4 ± 9.7% 130.9 ± 8.5%

POST0 POST2 POST0 POST2

– – – –

265.3 ± 32.9% 227.2 ± 23.4% 152.3 ± 7.9% 134.8 ± 11.3%

– – – –

250 ± 21.9% 232.4 ± 20.1% 167.4 ± 9.5% 156 ± 8.3%

Set 5 Set 4 Set 3 Set 2 Set 1 POST-INT

Table 1. MEP% after ITMS and Sham during the Practice phase. All values are expressed as a percentage of PRE-INT baseline

– – – –

248.7 ± 26.9% 242.2 ± 23% 175.8 ± 10% 163.2 ± 8.9%

Set 6

– – – –

247.9 ± 25.4% 221.5 ± 25.3% 179.9 ± 10% 162 ± 8.9%

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p < 0.001). Post-ITMS, single-pulse MEP amplitude increased (1.02 ± 0.18 mV vs. 2.49 ± 0.35 mV; baseline vs. post-ITMS respectively, p < 0.001) but there was no changes with Sham. CME: Practice phase As there was no change in CME induced by the Sham itself, the post-Sham Practice phase represents the effects of practice alone on CME. After the first practice set postSham, MEP% (at the POST0 and POST2 measurement times) was significantly increased compared to baseline (Table 1; Fig. 3; p < 0.001) and at each of these times MEP% continued to increase until the 4th set (p < 0.001), following which no further significant increase occurred. After ITMS, MEP% after the first practice set was again greater than at pre-INT baseline, and increased steadily up to the 4th set (p < 0.001) after which no further increase occurred (Table 1, Fig. 3). However, compared to MEP amplitude measured immediately post-ITMS and before the first practice set, there was a transient decrease in MEP amplitude after practice set 1 (Fig. 3). Overall, MEP% was significantly greater throughout the Practice phase after ITMS compared to Sham (F(1,15) = 35.2; p < 0.001). CME: Tracking phase In the Tracking phase, MEP amplitude in both INT groups was significantly greater than baseline (F(1,15) = 3.13; p < 0.05). MEP amplitude after the final practice set was 225.8 ± 11.6% and 168.7 ± 3.4% (ITMS and Sham respectively) and slowly declined to 191.1 ± 25.9% and 139.6 ± 11% above PRE-INT by the 10th min post-practice and continued its downward trend until the 20th min (178.1 ± 23.6% and 117 ± 7.5%; ITMS and Sham respectively) (Fig. 3). Kinematics: Starting rate Across all practice sets, within-group (F(1,11) = 16.73, p < 0.001) comparison of START RATE after both ITMS and Sham showed an increasing trend with practice (Table 2, Fig. 4). After Sham, START RATE was initially comparable to baseline, but was significantly increased by sets 4–6 (p < 0.001). After ITMS, START RATE was increased over baseline for set 1 and remained significantly higher than baseline for all practice sets (p < 0.001). Betweengroup comparison showed START RATE after ITMS was greater than for Sham (F(1,11) = 9.24, p < 0.05). Kinematics: Rate decrement The decline in RATE during each practice set showed an improvement after both ITMS and Sham (Fig. 5). Initially, no improvements in RATE decline was observed after Sham (practice sets 1–4), however a significant improvement (F(5,119) = 3.14, p < 0.05) was found by sets 5 and 6 (Table 3; Fig. 5). In contrast, there was an improvement in RATE decline for all practice sets (p < 0.001) after ITMS and the improvement that occurred after the first practice set was greater than that for the 6th practice set after Sham

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Fig. 3. MEP% (single-pulse TMS; group mean ± SEM) during the Practice and Tracking phases of the experiment after both ITMS and Sham. Immediately after ITMS MEP amplitude was increased by 250% of baseline, whereas there was no change after Sham. After each practice set, MEP amplitude was greater for POST0 than POST2, and there was an overall increase in excitability across practice sets. During the Tracking phase after the last practice set, MEP amplitude slowly returned toward baseline. Excitability was greater after ITMS compared to Sham throughout the recording period.

Table 2. A comparison of START RATE (Hz) between ITMS and Sham. Crosses (+) indicate significance of p < 0.001 between INTs

ITMS Sham

Set 1+

Set 2+

Set 3+

Set 4

Set 5

Set 6+

6.57 ± 0.4 6.16 ± 0.3

6.66 ± 0.5 6.17 ± 0.3

6.73 ± 0.4 6.22 ± 0.2

6.87 ± 0.5 6.61 ± 0.4

7.0 ± 0.5 6.67 ± 0.4

7.09 ± 0.3 6.66 ± 0.4

Fig. 4. A comparison of MVR START RATE (% baseline MVR; mean ± SEM) after ITMS and Sham and across practice sets. By the end of the practice sets, the starting rate had increased for both Sham and ITMS, but the movement rate was consistently higher across sets after ITMS compared to Sham. Crosses (+) indicate between-group significance; asterisks (  ) indicate within-group significance compared to baseline.

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Fig. 5. A comparison of percentage decrement in movement rate during the MVR task across practice sessions and after ITMS and Sham. The vertical axis plots the end/start rate (first 2 s and last 2 s of movement) expressed as a percentage, and a higher value indicates that less fall-off in rate occurred during the task (improved rate sustainability). By the end of the practice sets, rate sustainability was improved with both Sham and ITMS (p < 0.001). However, sustainability was greater across all practice sets after ITMS compared to Sham, and the improvement in sustainability was greater with just 1 practice set after ITMS than after 6 practice sets after Sham. Crosses (+) indicate between-group significance; asterisks (  ) indicate within-group significance compared to baseline.

Table 3. A comparison of percentage decrement ([last 2 s–first 2 s]  100) in RATE between ITMS and Sham. Crosses (+) indicate significance of p < 0.001 between INT and asterisk (  ) indicates significance of p < 0.05 from baseline

ITMS Sham

Baseline

Set 1+

Set 2+

Set 3+

Set 4+

Set 5+

Set 6+

82.6 ± 0.5% 82.5 ± 0.6%

86.8 ± 0.6%⁄ 82.3 ± 0.4%

87.5 ± 0.6%⁄ 82.8 ± 0.5%

87.5 ± 0.4%⁄ 82.1 ± 0.5%

87 ± 0.5%⁄ 83.1 ± 0.9%

87.5 ± 0.6%⁄ 84.5 ± 0.6%⁄

88.2 ± 0.5%⁄ 84.9 ± 0.6%⁄

(86.8 ± 0.6% vs. 84.9 ± 0.6%, p < 0.001).The decrement in movement RATE within each practice set was also significantly less (F(1,119) = 140.1, p < 0.001) after ITMS than after Sham. Kinematics: AMP Between-set comparisons revealed a significant increase (F(5,119) = 5.23, p < 0.001) in AMP between the 1st and 6th set after ITMS (96.5 ± 2.5% vs. 111.9 ± 2.8%) and Sham (97.1 ± 3.1% vs. 113.5 ± 4.1%) however no differences were found between INTs.

DISCUSSION In the present study we showed that short-term training of the MVR task can improve sustainability of the task. CME increased steadily after each training bout, and this increase was maintained up to 20 min after the last bout. A pre-training priming phase of ITMS further increased CME, and was associated with an increase in both the START rate of the MVR task and its sustainability. The

results implicate central motor processes in the performance and sustainability of the MVR task, and indicate that MVR kinematics can improve with short-term training and with non-invasive neuro-modulation. We have previously shown that, after a single 10-s repetition of the MVR task, there is an initial post-exercise increase in CME that declines after 2 min followed by a decrease in excitability that is maintained for up to 6 min (Teo et al., 2012b). However; the initial increase in CME is not observed after slower, less-demanding tasks in which movement rate can be fully sustained throughout the task. Rather, CME is immediately depressed with these less-demanding tasks, and the depression is stronger and more long-lasting than that observed after the MVR task. On the basis of these findings we concluded that the MVR task is associated with a net post-exercise increase in CME relative to undemanding tasks (Teo et al., 2012a,b). In keeping with these data, CME in the present study was increased immediately after each repetition set (POST0), after both ITMS and Sham, and the increase was less 2 min later (POST2). An interpretation is that the

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increase in CME is somehow related to the demand of the task, and could represent a short-term plasticity-like response. This interpretation is supported by the present findings, which showed that for both POST measurements, there was a steady increase in CME with each set repetition, that was associated with improvement in kinematic parameters and that may indicate the operation of shortterm plasticity-like effects that result in performance gain. Previous studies have reported practice-dependent changes to the cortical motor representation and motor threshold in practiced muscles after a single session(Pascual-Leone et al., 1994, 1995; Latash et al., 2003) and these plasticity-like effects may reflect long-term retention and consolidation of motor memory (Bonato et al., 2002; Rosenkranz et al., 2007). Classen et al. (1998) reported that a single-session of motor practice of thumb abduction increased the likelihood that TMS would induce an abduction movement of the thumb when delivered after the practice session, attributing this to use-dependent neuro-plasticity. Improvements in kinematics were observed for both Sham and ITMS conditions. With the Sham condition, there was no change in CME during or immediately after the ‘intervention’, indicating that the Sham was an effective null condition. Thus improvements in performance with set repetition after Sham are most likely attributable to elementary stages of motor improvements associated with practice. During this process, there was no significant increase in movement rate at the onset of each repetition, however the decline in rate normally observed with MVR tasks was diminished with repetition, and the task became more sustainable. This provides support for our hypothesis that the decline in motor performance during a MVR task represents a demand-associated breakdown in central motor control that can be improved with practice. Although it is plausible that plasticity at the cortical level is responsible for the performance gain and increased excitability after practice, mechanisms at the spinal level cannot be ruled out (Wolpaw, 2007). Several studies have shown changes in the H-reflex after motor training and skill acquisition in both animal and human models (Wolpaw et al., 1994; Wolf et al., 1995; Meunier et al., 2007). Giesebrecht et al. (2012) recently reported an increase in cervicomedullary MEPs after a repeated ballistic finger abduction task, which was maintained for as long as 10 min after practice completion. Furthermore, neuro-plasticity in spinal networks may have improved performance, for example by tuning of reciprocal inhibition (Berardelli et al., 1987; Bertolasi et al., 1998)or by other mechanisms that may have reduced the agonist–antagonist co-contraction (Rodrigues et al., 2009). Whether these considerations, or other mechanisms acting at the spinal level, could exclusively or substantially explain the present improvement in performance with practice cannot easily be determined. However, it seems more likely that there is a contribution at both cortical and spinal levels, and the greater performance gains after ITMS supports a role for supraspinal mechanisms. The ITMS protocol uses I-wave dynamics and shortinterval cortical facilitation (SICF) to target synaptic transmission in inter-neuronal networks responsible for I-wave

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generation (Thickbroom et al., 2006; Di Lazzaro et al., 2007; Hamada et al., 2007), which we have previously argued may be an analog of LTP-like synaptic plasticity. During the ITMS intervention, we observed a steady increase in CME that culminated with a 250% increase in excitability after 15 min that was maintained for 20 min after the intervention. From this higher excitability level (relative to Sham) CME remained greater than that for Sham across all set repetitions, and movement kinematics showed even greater improvement with practice than those which occurred after Sham. After ITMS, we saw a steady improvement in both the maximum movement rate at the onset of each repetition, as well as an improvement in movement rate sustainability. With the first repetition, movement sustainability after ITMS was better than for the 6th training bout after Sham. Furthermore, the increase in sustainability in the presence of an even greater starting rate than at baseline suggests there has been a considerable improvement in the central motor programing for this task. The results indicate that the ITMS intervention can not only increase excitability but also modulate motor performance. These results offer further support to the notion that the breakdown in MVR performance is central in origin and can be improved. As ITMS targets cortical I-wave networks in M1, the results also support a role for cortical plasticity in the performance gain we observe after ITMS. The mechanism by which ITMS could act to lessen performance decline is not certain. However, it is possible that an increase in CME, especially when combined with practice, could increase central motor drive and temporal tuning in inter-neuronal networks involved in the task. The relationship between the modulation of CME and performance with practice will be complex. After each MVR bout there is a transient increase then decrease in CME. With repeated bouts this pattern repeats, but at each time point CME increases relative to preceding bouts. Finally, ITMS (but not Sham) results in an overall increase in CME. While there are performance gains in all of these situations, there is no direct correlation between CME and performance. However, in all cases an increase in CME is associated with an improvement in performance, and it seems likely therefore that modulation in CME can result in performance gain, whether this modulation arises from natural consequences of practicing the task, or is imposed externally by ITMS, with the combination of practice and ITMS resulting in the greatest improvement in function. In conclusion, we have demonstrated that a novel MVR task, one that borders the limit of normal performance, may be improved within a single, repeated-bout practice session. The improvements in motor performance are accompanied by increases to CME that could represent short-term neuro-plastic changes that are the basis for the consolidation of motor memories. Furthermore, we have shown that a priming ITMS protocol leads to a further augmentation of motor performance. Our results suggest that neuro-modulation with ITMS can facilitate motor performance, which could have applications in motor rehabilitation after stroke and in other neurological disorders, as well as in the acquisition of new motor skills in normal individuals.

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Acknowledgement—The authors thank all the participants in the study and Jonathan Green for designing and developing the data acquisition program in Labview. Wei Peng Teo was supported by a Scholarship for International Research Fees, the University of Western Australia Postgraduate Award and the Enid and Arthur Home Memorial Scholarship. We also acknowledge support from the Neuromuscular Foundation and Muscular Dystrophy Association of Western Australia.

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(Accepted 19 June 2012) (Available online 28 June 2012)