Kozo Funase’s research while affiliated with Hiroshima University and other places

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 of the movement subspace spanned by common finger movements seen in daily life, through a custom task. After practicing 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 pre-existing 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.

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 inter-individual 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 6 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.

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.

Introduction A large number of researches have investigated the mechanisms of implicit and explicit motor sequence learning. The functional changes in motor circuits, which involve the primary motor cortex (M1), are thought to play an important role in memory formation of implicit knowledge. However, it is unclear what functions in the motor circuits contribute to formation of implicit knowledge in the M1. The corticospinal neuromuscular system organizes the modular architectures for generating a variety of movements. Therefore, we hypothesized that performance improvement through implicit learning results from reorganization of the modular architectures. Objectives We used transcranial magnetic stimulation (TMS), data-grove system, and principal component analysis (PCA) to test the hypothesis. Materials and methods Seventeen healthy subjects learned a sequence of serial reaction time task (SRTT) implicitly, and explicitly. Before and after a training session, both TMS-evoked finger joint movements and voluntary finger joint movements during the SRTT were recorded. Results PCA extracted a set of principal components (PCs) from TMS-evoked finger joint movements before (pre-PCs) and after (post-PCs) the training session, respectively. To test an idea that post-PCs contain large amount of information on the learned task, we reconstructed the voluntary movements during SRTT in post-training session by linear combination of a selected subset of the PCs. We found that the quality of the movements reconstructed by the post-PCs was superior to that of the pre-PCs in the implicit condition. By contrast, in the explicit condition, there was no significant difference in the reconstruction quality between the pre-PCs and post-PCs. Conclusion Our results suggest that the implicit knowledge is acquired through learning-specific reorganization of the modular architectures in the corticospinal neuromuscular system. On the other hand, the reorganization of the modular architectures does not relate to acquiring the explicit knowledge.

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.

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.

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. 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. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

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. Copyright © 2015. Published by Elsevier Ireland Ltd.