Masato Hirano’s research while affiliated with Sony Computer Science Laboratories and other places

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Publications (30)


The overview of the experiments
A Experimental procedure of the Experiments 1 and 2. Participants underwent either the decomposition training or repetition training of the experimental task. The participants who underwent the decomposition training took a 5-min break every 5 blocks, whereas the participants who underwent the repetition training took a 3-minute break every 5 trials. All participants performed the experimental task before and after the training. B (a) Experimental task. The task required the alternate repetition of two movement patterns. Each pattern consists of synchronous strikes of two keys with releasing another two keys; one using the right index and ring fingers for the strikes (movement pattern A) and another using the right middle and little fingers for the strikes (movement pattern B). I, M, R, and L indicate the index, middle, ring, and little fingers, respectively. (b) Skill decomposition training with visual feedback on the timing error of synchronous key motions with the four fingers. The training required practicing each of the two constituent movement patterns separately. For example, when practicing the pattern A, each participant kept depressing the keys with the middle and ring fingers during the preparation phase. Once the cue was provided, these two fingers lifted the keys whereas both the index and ring fingers depressed the adjacent keys synchronously. Participants in the skilled and non-skilled FB groups received the visual feedback (FB) on the timing of the key depression and key release by each of the four fingers within a time window of 0–100 ms (a sublet). When the difference in the timing between the initial and last key motions (timing error in the sublet) was lower than 10 ms or larger than 20 ms, circles corresponding to each finger displayed in the monitor turned black or blue, respectively; otherwise, it turned red. Each participant was instructed to minimize the timing error.
The results of the Experiment 1
A Box plots of the keypress error across the skilled pianists who underwent the repetition training of the experimental task in the pretest and posttest sessions. The x-axis and y-axis indicate the session and the keypress error, respectively. There was no significant difference between the pretest and posttest, which confirmed no training effect of repeating the experimental task. B Box plots of the keypress error in the pretest and posttest sessions for the skilled FB (black), no-FB (red), and non-skilled FB (blue) groups. The x-axis and y-axis indicate the session and the keypress error, respectively. A horizontal line indicates a significant difference between the pretest and posttest in the group of the same color (P < 0.05). C Box plots of the timing error of each of the two movement patterns (A, B) across 10 blocks in the skilled FB (black), no-FB (red), and non-skilled FB (blue) groups. The x-axis and y-axis indicate the block and the timing error, respectively. Asterisk and hashtag indicate significant differences in the timing error between the FB group and each of the no-FB and non-skilled FB groups, respectively. D Box plots of the timing error of each of the two movement patterns (A, B) in pretest and posttest sessions in the skilled FB (black), no-FB (red), and non-skilled FB (blue) groups. The x-axis and y-axis indicate the session and the timing error, respectively. The timing error derived from the experimental task was higher for the movement pattern B compared with the movement pattern A (P < 0.05), which indicates higher difficulty of executing the movement pattern B. Twenty-four right-handed skilled pianists (12 for each group) and 12 right-handed age-matched non-skilled pianists participated in the Experiment 1.
The results of the Experiment 2
Box plots of the keypress error (A) in the pretest and posttest sessions in the FB (black) and no-FB (red) groups. The x-axis and y-axis indicate the session and the keypress error, respectively. A horizontal line indicates a significant session-wise difference in the group of that color (P < 0.05). Box plots of the timing error (B, C) of each of the two movement patterns (A, B) in pretest and posttest sessions in the FB (black) and no-FB (red) groups. The x-axis and y-axis indicate the session and the timing error, respectively. A horizontal line indicates a significant session-wise difference in the group of that color (P < 0.05). Averaged finger joint angles (D, E) and angular velocities (F, G) across 600 trials in one representative pianist of the FB group (left panel) and in another of the no-FB group (right panel). A solid and dotted line indicate the metacarpophalangeal and proximal interphalangeal joints of each of the index (black), middle (red), ring (blue), little (green) fingers. The x-axis and y-axis indicate the normalized time points and the finger joint angles or the angular velocities, respectively. H Group means of the VI for the movement pattern B obtained from the angular velocity in the FB (block) and no-FB (red) groups. The x-axis and y-axis indicate the training block and VI, respectively. An asterisk indicates group differences in the VI (P < 0.05). A shaded area represents 1 SEM. The delta value was computed by subtracting the values in the earlier blocks from those in later blocks. Note that the FB group but not the no-FB group showed higher values at the initial half of the training blocks, exhibiting the movement exploration. I The scatterplots of differential value of the VI between the blocks 1–2 and 19–20 (x-axis) relative to the differential value of keypress error (y-axis) in the FB and no-FB groups. Black and red lines were derived from a least-squares fitting in the FB and no-FB groups, respectively. There was a significant Pearson’s correlation between the two variables in the FB group (P < 0.05). Twenty-four right-handed skilled pianists participated in Experiment 2 (12 for each group).
Decomposition of a complex motor skill with precise error feedback and intensive training breaks expertise ceiling
  • Article
  • Full-text available

January 2025

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51 Reads

Communications Biology

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Masato Hirano

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Complex motor skills involve intricate sequences of movements that require precise temporal coordination across multiple body parts, posing challenges to mastery based on perceived error or reward. One approach that has been widely used is to decompose such skills into simpler, constituent movement elements during the learning process, thereby aligning the task complexity with the learners’ capacity for accurate execution. Despite common belief and prevalent adoption, the effectiveness of this method remains elusive. Here we addressed this issue by decomposing a sequence of precisely timed coordination of movements across multiple fingers into individual constituent elements separately during piano practice. The results demonstrated that the decomposition training enhanced the accuracy of the original motor skill, a benefit not achieved through mere repetition of movements alone, specifically when skilled pianists received explicit visual feedback on timing error in the order of milliseconds during training. During the training, the patterns of multi-finger movements changed significantly, suggesting exploration of movements to refine the skill. By contrast, neither unskilled pianists who underwent the same training nor skilled pianists who performed the decomposition training without receiving visual feedback on the error showed improved skill through training. These findings offer novel evidences suggesting that decomposing a complex motor skill, coupled with receiving feedback on subtle movement error during training, further enhances motor expertise of skilled individuals by facilitating exploratory refinement of movements.

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Surmounting the ceiling effect of motor expertise by novel sensory experience with a hand exoskeleton

January 2025

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146 Reads

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4 Citations

Science Robotics

For trained individuals such as athletes and musicians, learning often plateaus after extensive training, known as the “ceiling effect.” One bottleneck to overcome it is having no prior physical experience with the skill to be learned. Here, we challenge this issue by exposing expert pianists to fast and complex finger movements that cannot be performed voluntarily, using a hand exoskeleton robot that can move individual fingers quickly and independently. Although the skill of moving the fingers quickly plateaued through weeks of piano practice, passive exposure to otherwise impossible complex finger movements generated by the exoskeleton robot at a speed faster than the pianists’ fastest one enabled them to play faster. Neither a training for fast but simple finger movements nor one for slow but complex movements with the exoskeleton enhanced the overtrained motor skill. The exoskeleton training with one hand also improved the motor skill of the untrained contralateral hand, demonstrating the intermanual transfer effect. The training altered patterns of coordinated activities across multiple finger muscles during piano playing but not in general motor and somatosensory functions or in anatomical characteristics of the hand (range of motion). Patterns of the multifinger movements evoked by transcranial magnetic stimulation over the left motor cortex were also changed through passive exposure to fast and complex finger movements, which accompanied increased involvement of constituent movement elements characterizing the individuated finger movements. The results demonstrate evidence that somatosensory exposure to an unexperienced motor skill allows surmounting of the ceiling effect in a task-specific but effector-independent manner.


Enhanced Somatosensory Inhibition Sharpens Hand Representation and Sensorimotor Skills in Pianists

January 2025

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39 Reads

The Journal of Neuroscience : The Official Journal of the Society for Neuroscience

Dexterous motor skills, like those needed for playing musical instruments and sports, require the somatosensory system to accurately and rapidly process somatosensory information from multiple body parts. This is challenging due to the convergence of afferent inputs from different body parts into a single neuron and the overlapping representation of neighboring body parts in the somatosensory cortices. How do trained individuals, such as pianists and athletes, manage this? Here, a series of five experiments with pianists and nonmusicians (female and male) shows that pianists have enhanced inhibitory function in the somatosensory system, which isolates the processing of somatosensory afferent inputs from each finger. This inhibitory function was assessed using a paired-pulse paradigm of somatosensory evoked potentials in electroencephalography, which measures the suppressive effect of a first stimulus [i.e., conditioning stimulus (CS)] on the response to a subsequent second stimulus. We found that pianists and nonmusicians showed an inhibitory response to the sequential stimuli to the peripheral somatosensory nerve at the wrist when the CS was intense. However, only pianists exhibited an inhibitory response to a weak CS, indicating enhanced inhibitory function in pianists. Additionally, the CS increased the information content segregating individual fingers represented in the cortical activity evoked by passive finger movements and improved the perception of fast multifinger sequential movements, specifically for pianists. Our findings provide the first evidence for experience-dependent plasticity in somatosensory inhibitory function and highlight its role in the expert motor performance of pianists.


Figure 3H illustrates the group mean of the VI in the FB and no-FB groups. A linear mixed effects model (LME: xed effects: group, block, and their interactions; random effects: participant) revealed signicant main (group: χ 2 (1) = 4.0, P = 0.04; block: χ 2 (18) = 69.29, P < 0.01) and interaction effects between the factors (χ 2 (18) = 59.1, P < 0.04). Post hoc tests yielded group differences in the VI at each of the block 1 (t(344) = 3.4, P < 0.01), at the block 2 (t(338) = 3.0, P < 0.01), at the block 7 (t(338) = 3.4, P < 0.01), at the block 8 (t(338) = 2.0, P = 0.03), at the block 9 (t(338) = 3.0, P < 0.01), and at the block 10 (t(338) = 3.0, P < 0.01).
Decomposition of a complex motor skill in learning improves experts' expertise

March 2024

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67 Reads

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1 Citation

Complex motor skills involve intricate sequences of movements that require precise temporal coordination across multiple body parts, posing challenges to mastery based on perceived error or reward. One approach that has been widely used is to decompose such skills into simpler, constituent movement elements during the learning process, thereby aligning the task complexity with the learners' capacity for accurate execution. Despite common belief and prevalent adoption, the effectiveness of this method remains elusive. Here we addressed this issue by decomposing a sequence of precisely timed coordination of movements across multiple fingers into individual constituent elements separately during piano practice. The results demonstrated that the decomposition training enhanced the accuracy of the original motor skill, a benefit not achieved through mere repetition of movements alone, specifically when skilled pianists received explicit visual feedback on timing error in the order of milliseconds during training. During the training, the patterns of multi-finger movements changed significantly, suggesting exploration of movements to refine the skill. By contrast, neither unskilled pianists who underwent the same training nor skilled pianists who performed the decomposition training without receiving visual feedback on the error showed improved skill through training. These findings offer novel evidences suggesting that decomposing a complex motor skill, coupled with receiving feedback on subtle movement error during training, further enhances motor expertise of skilled individuals by facilitating exploratory refinement of movements.


A specialized inhibitory function sharpens somatosensory hand representation and enhances the production and perception of fast multifinger movements in pianists

January 2024

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21 Reads

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1 Citation

Accurate control of fast movements of multiple body parts characterizes experts' skills, such as playing musical instruments. While performing these movements, the somatosensory system is challenged to successively and in parallel process a large amount of somatosensory information originating from different body parts in a short period. Here, we show that pianists possess a unique inhibitory function that isolates the somatosensory processing of different fingers in the somatosensory cortex. Weak electrical stimulation to the ulnar nerve successfully augmented this inhibitory function, which also improved both the perception and production of fast and complex multifinger sequential movements in pianists. In nonmusicians, neither the inhibitory effects on the somatosensory process nor the perception of multifinger movements was enhanced by this stimulation. Together, these findings provide the first evidence of the experience-dependent plasticity of inhibition of the somatosensory system, which underlies the fine control of fast and complex multifinger movements in expert pianists.



(A) Box plots of the differential value of the inter‐keystroke interval between the pretest and posttest sessions (i.e., posttest minus pretest) for the index, middle, ring, and little fingers (x‐axis) in the adult pianists who underwent the passive training using the exoskeleton (i.e., the adult training group in red) and the adult pianists who took rest (i.e., the adult rest group in blue). There was no significant interaction effect between the finger and the group, but a significant main effect of the group was shown. Graphs depict median, quartiles, and maximum and minimum values. **p <0.01. (B) Box plots of the differential value of the inter‐keystroke interval between the pretest and posttest sessions (i.e., posttest minus pretest) in the adult pianists and adolescent pianists who underwent the passive training using the exoskeleton (i.e., adult passive‐training and adolescent passive‐training groups in open red and filled red, respectively), the adult pianists who took rest (i.e., the adult rest group in open blue), and the adolescent pianists who practiced the designated sequence of finger movements with the piano (i.e., adolescent active‐practice group in filled blue). Graphs depict median, quartiles, and maximum and minimum values. *p < 0.05; **p < 0.01.
Passive somatosensory training enhances piano skill in adolescent and adult pianists: A preliminary study

November 2022

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85 Reads

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4 Citations

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Ryuya Tanibuchi

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Hayato Nishioka

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[...]

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Sensory afferent information, such as auditory and somatosensory feedback while moving, plays a crucial role in both control and learning of motor performance across the lifespan. Music performance requires skillful integration of multimodal sensory information for the production of dexterous movements. However, it has not been understood what roles somatosensory afferent information plays in the acquisition and sophistication of specialized motor skills of musicians across different stages of development. In the present preliminary study, we addressed this issue by using a novel technique with a hand exoskeleton robot that can externally move the fingers of pianists. Short‐term exposure to fast and complex finger movements generated by the exoskeleton (i.e., passive movements) increased the maximum rate of repetitive piano keystrokes by the pianists. This indicates that somatosensory inputs derived from the externally generated motions enhanced the quickness of the sequential finger movements in piano performance, even though the pianists did not voluntarily move the fingers. The enhancement of motor skill through passive somatosensory training using the exoskeleton was more pronounced in adolescent pianists than adult pianists. These preliminary results implicate a sensitive period of neuroplasticity of the somatosensory‐motor system of trained pianists, which emphasizes the importance of somatosensory‐motor training in professional music education during adolescence.


The detection threshold to the sensory stimulation in both the somatosensory and auditory modalities in each individual.
Intensity discrimination performance in unimodal and multisensory conditions. (A) and (B) The panels show the psychometric curves obtained from the intensity discrimination task with the five conditions in a representative pianist (A) and a nonmusician (B), respectively. The dashed line indicates the fitted cumulative Gaussian distribution function. The size of each circle represents the number of trials. The vertical axis means the proportion of answering “the intensity of comparing stimulus was larger than that of standard stimulus” at each stimulus intensity defined as a difference in the intensity between the two stimuli.
Group means of the sigma value obtained from the A, S, and A + S conditions in the pianists and nonmusicians. Each circle represents individual data.
Group means of the sigma value obtained from each condition in the pianists and nonmusicians. (A) The multisensory integration (A + S) vs the minimum sigma value of those obtained from the A and S conditions (minimum(A,S)). (B) The unimodal auditory (A) versus auditory selective attention (Aatt) conditions. (C) The unimodal somatosensory (S) versus somatosensory selective attention (Satt) conditions. Each circle represents individual data. *,**: p < 0.05, 0.01.
Multisensory interactions on auditory and somatosensory information in expert pianists

July 2022

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104 Reads

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2 Citations

Fine-tuned sensory functions typically characterize skilled individuals. Although numerous studies demonstrated enhanced unimodal sensory functions at both neural and behavioral levels in skilled individuals, little is known about their multisensory interaction function, especially multisensory integration and selective attention that involve volitional control of information derived from multiple sensory organs. In the current study, expert pianists and musically untrained individuals performed five sets of intensity discrimination tasks at the auditory and somatosensory modalities with different conditions: (1) auditory stimulus, (2) somatosensory stimulus, (3) congruent auditory and somatosensory stimuli (i.e., multisensory integration), (4) auditory and task-irrelevant somatosensory stimuli, and (5) somatosensory and task-irrelevant auditory stimuli. In the fourth and fifth conditions, participants were instructed to ignore a task-irrelevant stimulus and to pay attention to a task-relevant stimulus (i.e., selective attention), respectively. While the discrimination perception was superior in the condition (3) compared to the better one of the individual unimodal conditions only in the pianists, the task-irrelevant somatosensory stimulus worsened the auditory discrimination more in the pianists than the nonmusicians. These findings indicate unique multisensory interactions in expert pianists, which enables pianists to efficiently integrate the auditory and somatosensory information, but exacerbates top-down selective inhibition of somatosensory information during auditory processing.


Multisensory interactions on auditory and somatosensory information in expert pianists

February 2022

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16 Reads

Fine-tuned sensory functions are bases of efficient motor control and learning and typically characterize skilled individuals. Although numerous studies demonstrated enhanced unimodal sensory functions at both neural and behavioral levels in skilled individuals, little is known about their multisensory interaction, especially multisensory integration and selective attention that involve volitional control of information derived from multiple sensory organs. Here, we show unique multisensory interaction functions of expert pianists. Expert pianists and musically untrained individuals performed five sets of intensity discrimination tasks at the auditory and somatosensory modalities with different conditions: (1) auditory stimulus, (2) somatosensory stimulus, (3) congruent auditory and somatosensory stimuli (i.e., multisensory integration), (4) auditory and task-irrelevant somatosensory stimuli, and (5) somatosensory and task-irrelevant auditory stimuli. In the fourth and fifth conditions, participants were instructed to ignore a task-irrelevant stimulus and to pay attention to a task-relevant stimulus (i.e., selective attention). The unimodal intensity discrimination of the pianists was superior to that of the nonmusicians at the auditory modality but not at the somatosensory modality. While the discrimination perception was superior in the condition (3) compared to the better one of the individual unimodal conditions (i.e., conditions 1 and 2) only in the pianists, the task-irrelevant somatosensory stimulus worsened the auditory discrimination more in the pianists than the nonmusicians. These findings indicate efficient processing of multisensory information in expert pianists, which enables to benefit from multisensory integration of the auditory and somatosensory information, but exacerbates top-down selective inhibition of somatosensory information during auditory processing.


Active haptic training improves somatosensory-motor feedback control in the motor skills of experts

February 2022

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20 Reads

We perceive the external world through both externally generated and self-generated sensory stimuli (i.e., passive and active perception). While the performance in passive perception is improved by training or repetition through the functional and structural reorganization of the central nervous system (i.e., perceptual learning), the mechanisms by which perceptual learning occurs in active perception remain unclear. Here, we sought to explore the mechanisms underlying the improvement of active somatosensory perception and sensorimotor skills through active perceptual learning. Because we previously found that active perceptual learning depends on the expertise of the motor task to be performed, this study focused primarily on trained individuals. To this end, active haptic training (AHT) that targets the active somatosensory perception during the piano keystroke was used as a means of inducing active perceptual learning. We found four main results. First, participants actively modulated the muscle coordination patterns to optimize the movements required by the task through AHT without any explicit instruction on it by the experimenter, suggesting the involvement of active exploration in active perceptual learning. Second, AHT increased the relative reliance on afferent sensory information relative to the predicted one during the piano keystroke. Third, perceptual sensitivity of externally generated keystroke motions remained unchanged through AHT. Finally, AHT improved feedback control of repetitive keystroke movements in expert pianists. These results suggest that active perceptual learning involves changes in both the predictive integration process and active exploration and that the improved feedback control of fine movements benefits from the improvement in active perception. Significant statement Our ability to perceive both externally generated and self-generated sensory stimuli can be enhanced through training, known as passive and active perceptual learning. Here, we sought to explore the mechanisms underlying active perceptual learning by using active haptic training (AHT), which has been demonstrated to enhance the somatosensory perception of a finger in a trained motor skill. First, AHT reorganized the muscular coordination during the piano keystroke. Second, AHT increased the relative reliance on afferent sensory information relative to predicted one, in contrast to no increment of overall perceptual sensitivity. Finally, AHT improved feedback movement control of keystrokes. These results suggest that active perceptual learning involves active exploration and adaptation of predictive sensory integration, which underlies the co-enhancement of active perception and feedback control of movements.


Citations (21)


... Moreover, the quick and extreme learning effects could also suggest a ceiling effect. Studies show that trained individuals can experience a plateau in learning after extensive exposure to a task when expertise leaves little room for improvement (Furuya et al., 2025), a ceiling effect. This could be reflected throughout this task, suggesting that the task might have been too easy for the current population (Orvis et al., 2008), especially with the many improvement opportunities, e.g., through short breaks within the game (Johanson et al., 2019). ...

Reference:

HD-tDCS in a Gaming Setting: Effects of Polarity and Timing in a Visuospatial Working-Memory Task
Surmounting the ceiling effect of motor expertise by novel sensory experience with a hand exoskeleton
  • Citing Article
  • January 2025

Science Robotics

... Proses ini memungkinkan siswa melakukan penyesuaian yang diperlukan untuk meningkatkan keterampilan mereka. Penelitian oleh (Kimoto, 2024) juga mendukung pentingnya feedback terutama umpan balik yang disampaikan melalui berbagai modalitas sensorik yang mempercepat akuisisi keterampilan. Penelitian serupa oleh (Zhou et al., 2021) menemukan bahwa feedback terstruktur meningkatkan pembelajaran keterampilan motorik lebih signifikan dibandingkan pembelajaran tanpa feedback. ...

Decomposition of a complex motor skill in learning improves experts' expertise

... Linear potentiometers and force-sensitive resistors are used to measure and detect the finger position and pressure exerted by a musician while playing an instrument [29]. The relationship between the key depression force on an upright piano and the level of loudness of a generated tone is examined in [30] using a force transducer built-in key. To investigate, characterize, and quantify the mechanical impedance characteristics that contribute to the feel of musical keyboard keys, special test rigs are developed, including mechanical design and computer control, in [31,32]. ...

A specialized inhibitory function sharpens somatosensory hand representation and enhances the production and perception of fast multifinger movements in pianists
  • Citing Preprint
  • January 2024

... Also, a functional magnetic resonance imaging study has demonstrated that broader brain areas were recruited when listening and seeing a musical performance in piano players than novices, and the recruitment was observed especially in brain regions known to be related to integration of sensory and motor information [39]. Furthermore, the plastic brain changes related to the function of multisensory integration in piano players contribute to the neural basis of their advanced finger motor control [23,[40][41][42][43]. As precisely synchronizing tapping with both visual and auditory stimuli requires these functions, the high tapping synchronization stability for audiovisual stimuli in piano players, as demonstrated in our study, is believed to be due to the development of sensorimotor processing and fine motor control through piano experience. ...

Multisensory interactions on auditory and somatosensory information in expert pianists

... Communications Biology | (2025) 8:118 and neuromuscular features of the hand 36,37 . In contrast, the non-skilled participants did not undergo such adaptations, which implies that even the decomposed movement elements were too difficult to be executed. ...

Adaptation of the Corticomuscular and Biomechanical Systems of Pianists
  • Citing Article
  • August 2021

Cerebral Cortex

... The (lateral) cerebellum was most often targeted at a point either (1) 3 cm lateral (Daskalakis et al. 2004;Hardwick et al. 2014;Jayaram et al. 2011;Kassavetis et al. 2011;Pinto and Chen 2001;Schlerf et al. 2012Schlerf et al. , 2015Spampinato et al. , 2020aTanaka et al. 2021) or (2) 3 cm lateral and 1 cm inferior relative to the inion on the line joining the external auditory meatus (Fernandez et al. 2018b;Hardwick et al. 2014;Panyakaew et al. 2016;Tanaka et al. 2018). The latter target location corresponds to the cerebellar hand representation in lobule V and VIII which has been verified with MRI-based neuronavigation (Hardwick et al. 2014). ...

Modulation of cerebellar brain inhibition during temporal adaptive learning in a coincident timing task

Experimental Brain Research

... The experimental evidence from human studies suggests that the hand grasp synergies can be decoded from invasive and noninvasive neural recordings [9][10][11]. Transcranial magnetic stimulation (TMS) research has revealed that Sensors 2022, 22, 5349 2 of 16 rather than the development of new patterns, the evoked finger movements were reorganized with pre-existing primitive patterns represented in the corticospinal system [12]. The study on current source (CS) signals derived from electroencephalography (EEG) has shown that the primary motor cortex is the primary area for controlling finger movement, and characteristic differences between various finger movements were reflected in CS synergies patterns [13]. ...

Reorganization of finger covariation patterns represented in the corticospinal system by learning of a novel movement irrelevant to common daily movements
  • Citing Article
  • October 2019

Journal of Neurophysiology

Specialized Somatosensory-Motor Integration Functions in Musicians
  • Citing Article
  • July 2019

Cerebral Cortex

... The direct current component was subtracted from the EMG data, and the peak-to-peak amplitudes of the motor-evoked potentials (MEPs) within this 0.02-0.1 s window from TMS onset were evaluated and averaged offline. Furthermore, the common peroneal nerve was stimulated with supramaximal stimuli (1-ms rectangular pulse) using a constant voltage stimulator (SS-104; Nihon Kohden, Tokyo, Japan) controlled by a pulse-regulating system (SEN7202; Nihon Kohden) to obtain the maximum M-wave (M max ) in the PL muscle and to normalize the MEPs (Hirano et al. 2018;Suzuki et al. 2022;Tazoe et al. 2007). ...

Acquisition of motor memory determines the inter-individual variability of learning-induced plasticity in the primary motor cortex
  • Citing Article
  • July 2018

Journal of Applied Physiology: Respiratory, Environmental and Exercise Physiology

... Another approach that has been widely used in motor training is to decompose intricate movement sequences into a set of simple elements, a method shown to facilitate learning of complex motor skills in untrained individuals [13][14][15] . It has also been documented that the nervous system represents decomposed elements of movements 16 , which changes plastically through learning 17,18 . Furthermore, motor skill acquisition appears to accelerate when a newly learned skill shares common elements with previously learned motor skills 14 , suggesting a possibility that learning constituent skills generalizes acquisition of the original motor skill. ...

The acquisition of skilled finger movements is accompanied by the reorganization of the corticospinal system
  • Citing Article
  • November 2017

Journal of Neurophysiology