In the present study, we examined the role of the cerebellum in temporal adaptive learning during a coincident timing task, i.e., a baseball-like hitting task involving a moving ball presented on a computer monitor. The subjects were required to change the timing of their responses based on imposed temporal perturbations. Using paired-pulse transcranial magnetic stimulation, we measured cerebellar brain inhibition (CBI) before, during, and after the temporal adaptive learning. Reductions in CBI only occurred during and after the temporal adaptive learning, regardless of the direction of the temporal perturbations. In addition, the changes in CBI were correlated with the magnitude of the adaptation. Here, we showed that the cerebellum is essential for learning about and controlling the timing of movements during temporal adaptation. Furthermore, changes in cerebellar-primary motor cortex connectivity occurred during temporal adaptation, as has been previously reported for spatial adaptation.

How dexterous finger movements are acquired by the nervous system is a fundamental question in the neuroscience field. Previous studies have demonstrated that finger movements can be decomposed into finger covariation patterns, and these patterns are represented in the corticospinal system. However, it remains unclear how such covariation patterns represented in the corticospinal system develop during the acquisition of novel finger movements. In this study, each subject learned to perform a novel finger movement, which was mapped to a region outside the movement subspace spanned by common finger movements seen in daily life, through a custom task. After subjects practiced the task, we detected changes in the finger covariation patterns derived from artificially (transcranial magnetic stimulation) evoked finger joint movements. The artificially evoked movement-derived patterns seen after the training period were associated with both the novel and common finger movements. Regarding the patterns extracted from the artificially evoked movements, the number required to explain most of the variance in the data was unchanged after the training period. Our results indicate that novel finger movements are acquired through the reorganization of preexisting finger covariation patterns represented in the corticospinal system rather than the development of new patterns. These findings might have implications for the basic mechanism responsible for the development of movement repertories in the nervous system.NEW & NOTEWORTHY Various types of finger movements involve common finger covariation patterns, and these patterns are represented in the corticospinal system. Here we examined how a novel finger covariation pattern is acquired in that system through training of a novel finger movement that is irrelevant to common finger movements. Using transcranial magnetic stimulation, we found that the preexisting patterns that contribute to finer control of finger movements are rapidly reorganized to encode the novel pattern through the training.

Acquisition of new motor skills induces plastic reorganization in the primary motor cortex (M1). Previous studies have demonstrated the increases in the M1 excitability through motor skill learning. However, this M1 reorganization is highly variable between individuals even though they improve their skill performance through the same training protocol. To reveal the source of this interindividual variability, we examined the relationship between an acquisition of memory-guided feedforward movements and the learning-induced increases in the M1 excitability. Twenty-eight subjects participated in experiment 1. We asked subjects to learn a visuomotor tracking task. The subjects controlled a cursor on a PC monitor to pursue a target line by performing ankle dorsiflexion and plantar flexion. In experiment 1, we removed the online visual feedback provided by the cursor movement once every six trials, which enabled us to assess whether the subjects could perform accurate memory-guided movements. Motor-evoked potentials (MEP) were elicited in the tibialis anterior muscle by transcranial magnetic stimulation of the relevant M1 before and after the learning of the visuomotor tracking task and after half the trials. We found that the MEP amplitude was increased along with the improvement in memory-guided movements. In experiment 2 ( n = 10), we confirmed this relationship by examining whether the improvement in memory-guided movements induces increases in MEP amplitude. The results of this study indicate that the plastic reorganization of the M1 induced by the learning of a visuomotor skill is associated with the acquisition of memory-guided movements. NEW & NOTEWORTHY Acquisition of novel motor skills increases excitability of the primary motor cortex (M1). We recently reported that the amount of increases in the M1 excitability is highly variable between individuals even though they learned the same skill to the similar extent, yet the sources of this interindividual variability still remain unclear. The present study revealed that this interindividual variability is associated with whether individuals acquire a motor memory, which enables them to produce accurate memory-guided movements.

Motor training induces plastic changes in the primary motor cortex (M1). However, it is unclear whether and how the latency of motor-evoked potentials (MEP) and MEP amplitude are affected by implicit and/or explicit motor learning. Here, we investigated the changes in M1 excitability and MEP latency induced by implicit and explicit motor learning. The subjects performed a serial reaction time task (SRTT) with their five fingers. In this task, visual cues were lit up sequentially along with a predetermined order. Through training, the subjects learned the order of sequence implicitly and explicitly. Before and after the SRTT, we recorded MEP at 25 stimulation points around the hot spot for the flexor pollicis brevis (FPB) muscle. Although no changes in MEP amplitude were observed in either session, we found increases in MEP latency and changes in histogram of MEP latency after implicit learning. Our results suggest that reorganization across the motor cortices occurs during the acquisition of implicit knowledge. In contrast, acquisition of explicit knowledge does not appear to induce the reorganization based on the measures we recorded. The fact that the above mentioned increases in MEP latency occurred without any alterations in MEP amplitude suggests that learning has different effects on different physiological signals. In conclusion, our results propose that analyzing a combination of some indices of M1 excitability, such as MEP amplitude and MEP latency, is encouraged in order to understand plasticity across motor cortices.

To examine the factors that influence the inter-individual differences in the changes in primary motor cortex (M1) excitability seen after motor learning, we investigated the relationship between the amplitude of transcranial magnetic stimulation-induced motor evoked potentials (MEP) and short-latency afferent inhibition (SAI) after motor learning, based on the working hypothesis that SAI can be used to evaluate cortical acetylcholine (ACh) activity. To confirm this working hypothesis, we manipulated the arousal state of the subjects using a vigilance task, the outcomes of which might be correlated with cortical ACh activity, and investigated the effects of arousal state on SAI. As a result, we showed that SAI was significantly affected by arousal state. Consequently, we concluded that the subjects' arousal state during motor learning tasks is one of factors to influence on inter-individual differences in the changes in M1 excitability seen after motor learning tasks.

Dexterous finger movements are often characterized by highly coordinated movements. Such coordination might be derived from reorganization of the corticospinal system. In this study, we investigated 1) the manner in which finger movement covariation patterns are acquired, by examining the effects of the implicit and explicit learning of a serial reaction time task (SRTT), and 2) how such changes in finger coordination are represented in the corticospinal system. The subjects learned a button press sequence in both implicit and explicit learning conditions. In the implicit conditions, they were naive about what they were learning, whereas in the explicit conditions the subjects consciously learned the order of the sequence elements. Principal component analysis decomposed both the voluntary movements produced during the SRTT and the passive movements evoked by transcranial magnetic stimulation (TMS) over the primary motor cortex into a set of five finger joint covariation patterns. The structures of the voluntary and passive TMS-evoked movement patterns were reorganized by implicit learning but not explicit learning. Furthermore, in the implicit learning conditions the finger covariation patterns derived from the TMS-evoked and voluntary movements spanned similar movement subspaces. These results provide the first evidence that skilled sequential finger movements are acquired differently through implicit and explicit learning, i.e., the changes in finger coordination patterns induced by implicit learning are accompanied by functional reorganization of the corticospinal system, whereas explicit learning results in faster recruitment of individual finger movements without causing any changes in finger coordination. NEW & NOTEWORTHY Skilled sequential multifinger movements are characterized as highly coordinated movement patterns. These finger coordination patterns are represented in the corticospinal system, yet it still remains unclear how these patterns are acquired through implicit and explicit motor sequence learning. A direct comparison of learning-related changes between actively generated finger movements and passively evoked finger movements by TMS provided evidence that finger coordination patterns represented in the corticospinal system are reorganized through implicit, but not explicit, sequence learning.

Patterned sensory nerve stimulation has been shown to induce plastic changes in the reciprocal Ia inhibitory circuit. However, the mechanisms underlying these changes have not yet been elucidated in detail. The aim of the present study was to determine whether the reactivity of Ia inhibitory interneurons could be altered by patterned sensory nerve stimulation. The degree of reciprocal Ia inhibition, the conditioning effects of transcranial magnetic stimulation (TMS) on the soleus (SOL) muscle H-reflex, and the ratio of the maximum H-reflex amplitude versus maximum M-wave (H(max)/M(max)) were examined in 10 healthy individuals. Patterned electrical nerve stimulation was applied to the common peroneal nerve every 1 s (100 Hz-5 train) at the motor threshold intensity of tibialis anterior muscle to induce activity changes in the reciprocal Ia inhibitory circuit. Reciprocal Ia inhibition, the TMS-conditioned H-reflex amplitude, and H(max)/M(max) were recorded before, immediately after, and 15 min after the electrical stimulation. The patterned electrical nerve stimulation significantly increased the degree of reciprocal Ia inhibition and decreased the amplitude of the TMS-conditioned H-reflex in the short-latency inhibition phase, which was presumably mediated by Ia inhibitory interneurons. However, it had no effect on H(max)/M(max). Our results indicated that patterned sensory nerve stimulation could modulate the activity of Ia inhibitory interneurons, and this change may have been caused by the synaptic modification of Ia inhibitory interneuron terminals. These results may lead to a clearer understanding of the spinal cord synaptic plasticity produced by repetitive sensory inputs.

The modulation of spinal inhibitory circuit induced by visuomotor training have been shown in previous studies. However, it is not clarified that the changes in spinal inhibitory circuit are affected by movement speed. We hypothesized that the activity of spinal inhibitory circuits would show movement speed-dependent changes.

In motor skill learning, time to reach the plateau phase is different among the subjects. However, the details of the inter-individual difference of learning rate are still unknown. Which factors are associated with individual’s learning rate? Previous studies have demonstrated that the reduction of GABA in primary motor cortex (M1) has important role in motor skill learning. Therefore, we hypothesized that the subjects who have weak intracortical inhibition in M1 learn faster than the subjects who have strong intracortical inhibition. Here, we investigated the role of intrinsic intracortical inhibition and the rate of motor skill learning.

Previous studies have shown that spinal neural circuits are modulated by motor skill training. However, the effects of task movement speed on changes in spinal neural circuits have not been clarified. The aim of this research was to investigate whether spinal neural circuits were affected by task movement speed. Thirty-eight healthy subjects participated in this study. In experiment 1, the effects of task movement speed on the spinal neural circuits were examined. Eighteen subjects performed a visuomotor task involving ankle muscle slow (nine subjects) or fast (nine subjects) movement speed. Another nine subjects performed a non-visuomotor task (controls) in fast movement speed. The motor task training lasted for 20 min. The amounts of D1 inhibition and reciprocal Ia inhibition were measured using H-relfex condition-test paradigm and recorded before, and at 5, 15, and 30 min after the training session. In experiment 2, using transcranial magnetic stimulation (TMS), the effects of corticospinal descending inputs on the presynaptic inhibitory pathway were examined before and after performing either a visuomotor (eight subjects) or a control task (eight subjects). All measurements were taken under resting conditions. The amount of D1 inhibition increased after the visuomotor task irrespective of movement speed (P < 0.01). The amount of reciprocal Ia inhibition increased with fast movement speed conditioning (P < 0.01), but was unchanged by slow movement speed conditioning. These changes lasted up to 15 min in D1 inhibition and 5 min in reciprocal Ia inhibition after the training session. The control task did not induce changes in D1 inhibition and reciprocal Ia inhibition. The TMS conditioned inhibitory effects of presynaptic inhibitory pathways decreased following visuomotor tasks (P < 0.01). The size of test H-reflex was almost the same size throughout experiments. The results suggest that supraspinal descending inputs for controlling joint movement are responsible for changes in the spinal neural circuits, and that task movement speed is one of the critical factors for inducing plastic changes in reciprocal Ia inhibition.

We aimed to investigate the effects of the tactile stimulation to an observer's fingertips at the moment that they saw an object being pinched by another person on the excitability of observer's primary motor cortex (M1) using transcranial magnetic stimulation (TMS). In addition, the above effects were also examined during action observation combined with the motor imagery. Motor evoked potentials (MEP) were evoked from the subjects' right first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles. Electrical stimulation (ES) inducing tactile sensation was delivered to the subjects' first and second fingertips at the moment of pinching action performed by another person. Although neither the ES nor action observation alone had significant effects on the MEP amplitude of the FDI or ADM, the FDI MEP amplitude which acts as the prime mover during pinching was reduced when ES and action observation were combined; however, no such changes were seen in the ADM. Conversely, that reduced FDI MEP amplitude was increased during the motor imagery. These results indicated that the M1 excitability during the action observation of pinching action combined with motor imagery could be enhanced by the tactile stimulation delivered to the observer's fingertips at the moment corresponding to the pinching being observed.

In the present study, we used transcranial magnetic stimulation (TMS) to investigate the changes in the excitability of the left primary motor cortex (M1) innervating the hand muscles and in short-interval intracortical inhibition (SICI) during speech describing hand or leg movements. In experiment 1, we investigated the effects of the contents of speech on the amplitude of the motor evoked potentials (MEPs) induced during reading aloud and silent reading. In experiment 2, we repeated experiment 1 with an additional condition, the non-vocal oral movement (No-Voc OM) condition, and investigated the change in SICI induced in each condition using the paired TMS paradigm. The MEP observed in the reading aloud and No-Voc OM conditions exhibited significantly greater amplitudes than those seen in the silent reading conditions, irrespective of the content of the sentences spoken by the subjects or the timing of the TMS. There were no significant differences in SICI between the experimental conditions. Our findings suggest that the increased excitability of the left M1 hand area detected during speech was mainly caused by speech-related oral movements and the activation of language processing-related brain functions. The increased left M1 excitability was probably also mediated by neural mechanisms other than reduced SICI; i.e., disinhibition.

Background: Previous studies have shown that primary motor cortex (M1) excitability is modulated by motor skill learning and that the M1 plays a crucial role in motor memory. However, the following questions remain: 1) At what stage do changes in M1 excitability occur? 2) Are learning-induced changes in leg M1 excitability associated with motor memory? Here, we did two experiments to answer these questions.Methods and results: In experiment 1, subjects learned a visuomotor tracking task over two consecutive days. Before and after the task in Day 1, we recorded input-output curves of the motor evoked potentials (I-O curve) produced in the tibialis anterior muscle by transcranial magnetic stimulation. We found that the changes in M1 excitability were affected by learning stage. In addition, the changes in M1 excitability in Day 1 were correlated with the retention. In experiment 2, we recorded I-O curves before learning, after the fast-learning stage, and after learning. We found no changes in M1 excitability immediately after the fast-learning stage. Furthermore, a significant relationship between the length of slow-learning stage and the changes in M1 excitability was detected.Conclusions: Previous studies have suggested that optimal motor commands are repeatedly used during the slow-learning stage. Therefore, present results indicate that changes in M1 excitability occur during the slow-learning stage and that such changes are proportional to motor skill retention because use-dependent plasticity occur by repetitive use of same motor commands during the slow-learning stage. (C) 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Previous studies have shown that motor skill learning induces the change in the excitability of the primary motor cortex (M1). However, it is still unclear that whether the change in M1 excitability occurs in a certain stage of motor skill learning. Motor skill learning consists of the following stages; fast-learning, slow-learning, and retention. Several previous studies have revealed that a same motor command is used repeatedly during the slow-learning stage. Therefore, we hypothesized the change in M1 excitability induced by motor skill learning occurs in the slow-learning stage.

Performing a complex unimanual motor task markedly increases activation not only in the hemisphere contralateral to the task-performing hand but also in the ipsilateral hemisphere. Transcranial magnetic stimulation studies showed increased motor evoked potential amplitude recorded in resting hand muscles contralateral to the task-performing hand during a unimanual motor task, and transcallosal inputs from the active hemisphere have been suggested to have responsibilities for this phenomenon. In the present study, we used a well-established double-pulse transcranial magnetic stimulation paradigm to measure two phases of interhemispheric inhibition from the active to the resting primary motor cortex during the performance of a complex unimanual motor task. Two different unimanual motor tasks were carried out: a fine-motor manipulation task (using chopsticks to pick up, transport, and release glass balls) as a complex task and a pseudo fine-motor manipulation task as a control task (mimicking the fine-motor manipulation task without using chopsticks and picking glass balls). We found increased short-latency interhemispheric inhibition and decreased long-latency interhemispheric inhibition from the active to the resting primary motor cortex during the fine-motor manipulation task. To the best of our knowledge, the present study is the first to demonstrate different modulation of two phases of interhemispheric inhibition from the active to the resting primary motor cortex during the performance of a complex unimanual motor task. The different modulation of short- and long-latency interhemispheric inhibition may suggest that two phases of interhemispheric inhibition are implemented in distinct circuits with different functional meaning.

Whether a cortical drive to one limb modulates interhemispheric inhibition (IHI) from the active targeting to the non-active motor cortex (M1) remained unclear. The present study using a conditioning-test transcranial magnetic stimulation (TMS) paradigm aimed to directly demonstrate the modulation of IHI during unilateral voluntary or imagined movement in humans. Subjects were asked to actually perform right index-finger abduction (10-70% of the maximum voluntary contraction) or to imagine the movement. Conditioning and test TMS with an interstimulus interval of 5, 10, and 15 ms were applied over the left and right M1, respectively, and the test motor evoked potential (MEP) was recorded from the left first dorsal interosseous (FDI) muscle. The conditioning TMS intensity was adjusted ranging from 0.6 to 1.4 (in 0.2 steps) times the resting motor threshold (rMT). With test TMS alone, MEP in the left FDI muscle significantly increased during voluntary or imagined movement of the right index-finger. MEP amplitude was significantly reduced in proportion to increments of the conditioning TMS intensity at rest (1.2 and 1.4 times the rMT, P < 0.05, respectively). Importantly, the MEP inhibition was markedly enhanced during voluntary or imagined movement in comparison with that at rest. The regression analysis revealed that IHI varied depending on the intensity of the impulses conveyed from left to right M1, but not on the corticospinal excitability of the active right hand. Our results suggest that IHI from the active to non-active M1 is enhanced during unilateral volitional motor activity.

The aim of this study was to investigate the plasticity of M1 innervating the tibialis anterior muscle (TA) induced by the long-term practice of football juggling using a transcranial magnetic stimulation (TMS) technique. Ten football juggling experts and ten novices participated in this study. Motor evoked potentials (MEP) and the H-reflex were recorded from the right TA during isometric dorsiflexion at 10% of maximum voluntary contraction. The MEP input-output curve of the experts was steeper than that of the novices, and reduced short-interval intracortical inhibition and long-interval intracortical inhibition were observed in the experts. In contrast, the ratio of Hmax to Mmax did not differ between the groups. Our results show that football juggling experts displayed enhanced excitability in the M1 innervating the TA, which was induced by the long-term practice of the ankle movements required to perform football juggling well.