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Funato, T.

Publications and source records attributed to Funato, T..

3 recordsLinked to original sources

Multi-timescale neural adaptation underlying long-term musculoskeletal reorganization.

The central nervous system (CNS) can effectively control body movements despite environmental changes. While much is known about adaptation to external environmental changes, less is known about responses to internal bodily changes. This study investigates how the CNS adapts to long-term alterations in the musculoskeletal system using a tendon transfer model in non-human primates. We surgically relocated finger flexor and extensor muscles to examine how the CNS adapts its strategy for finger movement control by measuring muscle activities during grasping tasks. Two months post-surgery, the monkeys demonstrated significant recovery of grasping function despite the initial disruption. Our findings suggest a two-phase CNS adaptation process: an initial phase enabling function with the transferred muscles, followed by a later phase abandoning this enabled function and restoring a control strategy that, while potentially less conflicted than the maladaptive state, resembled the original pattern, possibly representing a good enough solution. These results highlight a multi-phase CNS adaptation process with distinct time constants in response to sudden bodily changes, offering potential insights into understanding and treating movement disorders. SIGNIFICANCE STATEMENTAfter major changes to the bodys mechanics, the nervous system adapts using strategies on multiple timescales. Our primate tendon transfer study shows that core muscle synergy groupings remain stable, reflecting a default to modular control. However, the activation of these synergies changes dramatically; an initial, rapid swap of their timing proves to be maladaptive, impairing motor function. This conflict is only resolved through the gradual development of slower, compensatory strategies over several weeks. This process highlights the fundamental tension the CNS faces when its reliance on stable motor modules conflicts with the need for flexible control, offering insights into neural plasticity and staged rehabilitation.

neuroscience↗

Bayesian estimation of trunk-leg coordination during walking using phase oscillator models

In human walking, the legs and other body parts coordinate to produce a rhythm with appropriate phase relationships. From the point of view for rehabilitating gait disorders, such as Parkinson Disorders, it is important to understand the control mechanism of the gait rhythm. A previous study showed that the antiphase relationship of the two legs during walking is not strictly controlled using the reduction of the motion of the legs during walking to coupled phase oscillators. However, the control mechanisms other than those of the legs remains unknown. In particular, the trunk moves in tandem with the legs and must play an important role in stabilizing walking because it is above the legs and accounts for more than half of the mass of the human body. This study aims to uncover the control mechanism of the leg-trunk coordination in the sagittal plane using the coupled phase oscillators model and Bayesian estimation. We demonstrate that the leg-trunk coordination is not strictly controlled, as well as the interleg coordination.

bioengineering↗

Interleg coordination is not strictly controlled during walking

In human walking, the left and right legs move alternately, half a stride out of phase with each other. Although various parameters, such as stride frequency, stride length, and duty factor, vary with walking speed, the antiphase relationship of the leg motion remains unchanged. This is the case even during running. However, during walking in left-right asymmetric situations, such as walking with unilateral leg loading, walking along a curved path, and walking on a split-belt treadmill, the relative phase between left and right leg motion shifts from the antiphase condition to compensate for the asymmetry. In addition, the phase relationship fluctuates significantly during walking of elderly people and patients with neurological disabilities, such as those caused by stroke or Parkinsons disease. These observations suggest that appropriate interleg coordination is important for adaptive walking and that interleg coordination is strictly controlled during walking of healthy young people. However, the control mechanism of interleg coordination remains unclear. In the present study, we derive a quantity that models the control of interleg coordination during walking of healthy young people by taking advantage of a state-of-the-art method that combines big data science with nonlinear dynamics. This is done by modeling this control as the interaction between two coupled oscillators through the phase reduction theory and Bayesian inference method. However, the results were not what we expected. Specifically, we found that the relative phase between the motion of the legs is not actively controlled until the deviation from the antiphase condition exceeds a certain threshold. In other words, the control of interleg coordination has a dead zone like that in the case of the steering wheel of an automobile. Such forgoing of control presumably enhances energy efficiency and maneuverability during walking. Furthermore, the forgoing of control in specific situations, where we expect strict control, also appears in quiet standing. This suggests that interleg coordination in walking and quiet standing have a common characteristic strategy. Our discovery of the dead zone in the control of interleg coordination not only provides useful insight for understanding gait control in humans, but also should lead to the elucidation of the mechanisms involved in gait adaptation and disorders through further investigation of the dead zone.

bioengineering↗