Biology subjects

Takiyama, K.

Publications and source records attributed to Takiyama, K..

9 recordsLinked to original sources

bioRxiv2026

Gait speed and surface stiffness interactively modulate selected muscle- but not joint-synergy recruitment during compliant-surface walking

Humans adapt walking to different speeds and compliant surfaces, but whether gait speed and surface stiffness shape joint kinematics and muscle activity independently or interactively remains unclear. We reanalyzed an open variable-stiffness treadmill dataset collected at three speeds and four stiffness levels. Tensor decomposition extracted joint and muscle synergies and condition-specific recruitment coefficients. Stride length and stride time were modulated by speed and stiffness without interactions. Joint-synergy recruitment showed speed effects in all three components and stiffness effects in two components, but no speed-by-stiffness interactions. Among five muscle synergies, three were modulated without interaction, whereas two related to weight acceptance and forward propulsion showed significant speed-by-stiffness interactions. Their recruitment increased with speed, but stiffness-dependent differences decreased at higher speeds. These findings suggest that speed and stiffness largely modulate stride- and joint-level control independently, while interactively shaping selected muscle-synergy recruitment.

neuroscience↗

bioRxiv2024

Distinct optimization of motor control and learning: Self-paced motor learning achieves different motor patterns from overtrained

Self-paced movement, refined through extensive training and optimization, serves as an ideal model for investigating internal objectives within the sensorimotor system without external constraints. Previous studies have demonstrated that self-paced movement is consistent within individuals but variable across individuals, emphasizing a robust and unique optimization in self-paced motor control. While motor learning is also an optimization process, it remains unclear whether the internal objectives overlap between motor control and learning, or, more specifically, whether motor patterns identified in self-paced motor control are replicated in motor learning. Given that optimality principles typically address redundancy, human behavioral experiments were designed to equate movement distances for both motor control and learning in self-paced movements and to thus compare redundant motion parameters, movement velocity and duration. We dissected participants reaching movements at their preferred pace, controlling a visual cursor to a target on a display over specified movement distances, through a detailed analysis that that accommodates nonlinear interaction and significant inter-individual baseline differences of movement velocity and duration. In self-paced motor control, participants adjusted both velocity and duration in response to changes in target distances. However, when visuomotor shift perturbations were applied to the cursor in the longitudinal direction, triggering motor learning, participants adapted their movement distance solely by modulating velocity, while leaving duration unchanged. These results suggest that distinct optimization strategies are employed in motor control and learning to resolve movement redundancy. Significance statementNatural behaviors are thought to be well-optimized. Self-paced movements--an important form of such behaviors--showing significant stability within individuals but variability across individuals. This suggests that the sensorimotor system in the central nervous system operates through a unique and robust optimization process for self-paced motor control. Self-paced motor control is further refined through motor learning. However, it remains unclear whether motor control and learning share a common objective function. Our findings demonstrate that laboratory-based motor learning does not replicate the motor patterns observed in overtrained, self-paced movements performed under natural conditions. This suggests that distinct optimization mechanisms are at play in motor control and learning, indicating that these processes are not contiguous.

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bioRxiv2024

Modulation of cortico-muscular coupling associated with split-belt locomotor adaptation

Humans can adjust their walking patterns according to the demands of their internal and external environments, referred to as locomotor adaptation. Although significant functional coupling (i.e. cortico-muscular coherence [CMC]) has been shown between cortical and lower-limb muscle activity during steady-state walking, little is known about CMC in locomotor adaptation. Therefore, we investigated the adaptation-dependent modulation of the CMC between the sensorimotor region and the tibialis anterior muscle using a split-belt locomotor adaptation paradigm that can impose an asymmetric perturbation. We hypothesized that the CMC would temporarily decrease after exposure to the asymmetric perturbation and removal of the perturbation because of a mismatch between the predicted and actual sensory feedback. We also hypothesized that the CMC would increase as adaptation and de-adaptation to perturbation progressed because the motor system could become able to predict sensory feedback. Our findings revealed that the CMC temporarily decreased after exposure to and removal of the perturbation. Moreover, the CMC increased with adaptation and de-adaptation to perturbation. Although these results depend on the leg, frequency bands, and gait phases, they partially support our hypothesis. These findings suggest that flexible updating of cortico-muscular coupling in the motor system is a key mechanism underlying locomotor adaptation in humans. The results from our study on healthy young individuals contribute to the understanding of neuromuscular control of gait and provide valuable insight for optimising gait rehabilitation. Key pointsO_LILocomotor adaptation plays a crucial role in our daily activities and gait rehabilitation. C_LIO_LIAlthough knowledge regarding the brain and muscle activities associated with locomotor adaptation has been accumulated, little is known about the functional coupling of the brain and muscle activities. C_LIO_LIUsing high-density EEG and lower limb EMG, we demonstrated the modulation of cortico-muscular coherence between the sensorimotor region and the tibialis anterior muscle with adaptation and de-adaptation during a split-belt treadmill walking paradigm. C_LIO_LIOur findings suggest that flexible updating of cortico-muscular coupling in the motor system underlies locomotor adaptation in humans. C_LIO_LIUnderstanding the human brains control of muscles during split-belt locomotor adaptation will deepen our knowledge of neuromuscular control of gait and provide valuable insights for gait rehabilitation. C_LI

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bioRxiv2024

Shifts in neural tuning systematically alter sensorimotor learning ability

Sensorimotor learning can change the tuning of neurons in motor-related brain areas and rotate their preferred directions (PDs). These PD rotations are commonly interpreted as reflecting motor command changes; however, cortical neurons that display PD rotations also contribute to sensorimotor learning. Sensorimotor learning should, therefore, alter not only motor commands but also the tuning of neurons responsible for this learning, and thus impact subsequent learning ability. Here, we investigate this possibility with computational modeling and by directly measuring adaptive responses during sensorimotor learning in humans. Modeling shows that the PD rotations induced by sensorimotor learning, predict specific anisotropic changes in PD distributions that in turn predict a specific spatial pattern of changes in learning ability. Remarkably, experiments in humans then reveal large, systematic changes in learning ability in a spatial pattern that precisely reflects these model-predicted changes. We find that this pattern defies conventional wisdom and implements Newtons method, a learning rule where the step size is inversely proportional rather than proportional to the learning gradients amplitude, limiting overshooting in the adaptive response. Our findings indicate that PD rotation provides a mechanism whereby the motor system can simultaneously learn how to move and learn how to learn.

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bioRxiv2019

Larger, but not better, implicit motor adaptation ability inherent in medicated Parkinson’s disease patients: a smart-device-based study

Generating appropriate motor commands is an essential brain function. To achieve proper motor control in diverse situations, predicting future states of the environment and body and modifying the prediction are indispensable. The internal model is a promising hypothesis about brain function for generating and modifying the prediction. Although several findings support the involvement of the cerebellum in the internal model, recent results support the influence of other related brain regions on the internal model. A representative example is the motor adaptation ability in Parkinsons disease (PD) patients. Although this ability provides some hints about how dopamine deficits affect the internal model, previous findings are inconsistent; some reported a deficit in the motor adaptation ability in PD patients, but others reported that the motor adaptation ability of PD patients is comparable to that of healthy controls. A possible factor causing this inconsistency is the difference in task settings, which yield different cognitive strategies in each study. Here, we demonstrate a larger, but not better, motor adaptation ability in PD patients than healthy controls while reducing the involvement of cognitive strategies and concentrating on implicit motor adaptation abilities. This study utilizes a smart-device-based experiment that enables motor adaptation experiments anytime and anywhere with less cognitive strategy involvement. The PD patients showed a significant response to insensible environmental changes, but the response was not necessarily suitable for adapting to the changes. Our findings support compensatory or paretic cerebellar functions in PD patients from the perspective of motor adaptation.

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bioRxiv2019

Detecting task-dependent modulation of spatiotemporal module via tensor decomposition: application to kinematics and EMG data for walking and running at various speed

How the central nervous system (CNS) controls many joints and muscles is a fundamental question in motor neuroscience and related research areas. An attractive hypothesis is the module hypothesis: the CNS controls groups of joints or muscles (i.e., spatial modules) while providing time-varying motor commands (i.e., temporal modules) to the spatial modules rather than controlling each joint or muscle separately. Another fundamental question is how the CNS generates numerous repertories of movement patterns. One hypothesis is that the CNS modulates the spatial and/or temporal modules depending on the required tasks. It is thus essential to quantify the spatial module, the temporal module, and the task-dependent modulation of those modules. Although previous methods attempted to quantify these aspects, they considered the modulation in only the spatial or temporal module. These limitations were possibly due to the constraints inherent to conventional methods for quantifying the spatial and temporal modules. Here, we demonstrate the effectiveness of tensor decomposition in quantifying the spatial module, the temporal module, and the task-dependent modulation of these modules without such limitations. We further demonstrate that the tensor decomposition provides a new perspective on the task-dependent modulation of spatiotemporal modules: in switching from walking to running, the CNS modulates the peak timing in the temporal module while recruiting proximal muscles in the corresponding spatial module.\n\nAuthor summaryThere are at least two fundamental questions in motor neuroscience and related research areas: 1) how does the central nervous system (CNS) control many joints and muscles and 2) how does the CNS generate numerous repertories of movement patterns. One possible answer to question 1) is that the CNS controls groups of joints or muscles (i.e., spatial modules) while providing time-varying motor commands (i.e., temporal modules) to the spatial modules rather than controlling each joint or muscle separately. One possible answer to question 2) is that the CNS modulates the spatial and/or temporal module depending on the required tasks. It is thus essential to quantify the spatial module, the temporal module, and the task-dependent modulation of those modules. Here, we demonstrate the effectiveness of tensor decomposition in quantifying the modules and those task-dependent modulations while overcoming the shortcomings inherent to previous methods. We further show that the tensor decomposition provides a new perspective on how the CNS switches between walking and running. The CNS modulated the peak timing in the temporal module while recruiting proximal muscles in the corresponding spatial module.

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bioRxiv2018

Optimal motor decision-making through competition with opponents

Although optimal decision-making is essential for sports performance and fine motor control, it has been repeatedly confirmed that humans show a strong risk-seeking bias, selecting a risky strategy over an optimal solution. Despite such evidence, the ideal method to promote optimal decision-making remains unclear. Here, we propose that interactions with other people can influence motor decision-making and improve risk-seeking bias. We developed a competitive reaching game (a variant of the "chicken game") in which aiming for greater rewards increased the risk of no reward and subjects competed for the total reward with their opponent. The game resembles situations in sports, such as a penalty kick in soccer, service in tennis, the strike zone in baseball, or take-off in ski jumping. In five different experiments, we demonstrated that, at the beginning of the competitive game, the subjects robustly switched their risk-seeking strategy to a risk-averse strategy. Following the reversal of the strategy, the subjects achieved optimal decision-making when competing with risk-averse opponents. This optimality was achieved by a non-linear influence of an opponents decisions on a subjects decisions. These results suggest that interactions with others can alter human motor decision strategies and that competition with a risk-averse opponent is key for optimizing motor decision-making.

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bioRxiv2018

Detection of task-relevant and task-irrelevant motion sequences: application to motor adaptation in goal-directed and whole-body movements

Motor variability is inevitable in our body movements and is discussed from several various perspectives in motor neuroscience and biomechanics; it can originate from the variability of neural activities, it can reflect a large degree of freedom inherent in our body movements, it can decrease muscle fatigue, or it can facilitate motor learning. How to evaluate motor variability is thus a fundamental question in motor neuroscience and biomechanics. Previous methods have quantified (at least) two striking features of motor variability; the smaller variability in the task-relevant dimension than in the task-irrelevant dimension and the low-dimensional structure that is often referred to as synergy or principal component. However, those previous methods were not only unsuitable for quantifying those features simultaneously but also applicable in some limited conditions (e.g., a method cannot consider motion sequence, and another method cannot consider how each motion is relevant to performance). Here, we propose a flexible and straightforward machine learning technique that can quantify task-relevant variability, task-irrelevant variability, and the relevance of each principal component to task performance while considering the motion sequence and the relevance of each motion sequence to task performance in a data-driven manner. We validate our method by constructing a novel experimental setting to investigate goal-directed and whole-body movements. Furthermore, our setting enables the induction of motor adaptation by using perturbation and evaluating the modulation of task-relevant and task-irrelevant variabilities through motor adaptation. Our method enables the identification of a novel property of motor variability; the modulation of those variabilities differs depending on the perturbation schedule. Although a gradually imposed perturbation does not increase both task-relevant and task-irrelevant variabilities, a constant perturbation increases task-relevant variability.

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bioRxiv2018

Influence of switching rule on motor learning

Humans and animals can flexibly switch rules to generate appropriate motor commands; for example, actions can be flexibly produced toward a sensory stimulus (e.g., pro-saccade or pro-reaching) or away from a sensory stimulus (e.g., anti-saccade or anti-reaching). Distinct neural activities are related to pro- and anti-movement actions; however, the effects of switching rules on motor learning are unclear. Here, we study the effect of switching rules on motor learning using pro- and anti-arm-reaching movements and a visuomotor rotation task. Although previous results support the perfect availability of learning effects under the same required movements, we show that the learning effects trained in pro-reaching movements are partially rather than perfectly available in anti-reaching movements even under the same required movement direction between those two conditions. The partial transfer is independent of the difference in the visual cue, the cognitive demand, and the actual movement direction between the pro- and anti-reaching movements. We further demonstrate that the availability of learning effects trained with pro-reaching movements is partial not only in anti-reaching movements but in reaching movements with other rules and the availability of learning effects trained with anti-reaching movements is also partial in pro-reaching movements. We thus conclude that the switching rule causes the availability of learning effects to be partial rather than perfect even under same planned movements.\n\nNew & Noteworthy\n\nMost motor learning experiments supported the involvement of planned movement directions in motor learning; the learning effects trained in a movement direction can be available at movement directions close to the trained one. Here, we show that the availability of motor learning effects is partial rather than perfect even under the same planned movements when rule is switched, which indicates that sports training and rehabilitation should include various situations under the same required motions.

neuroscience↗