Computational theory on cerebello-spinal dynamics during gait

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Brain control and human musculo-skeletal system and interaction with the environment through the ground reaction force provide a basis of dynamic stability during human gait We studied possible strategies used by the human central nervous system during maintenance of gait stability. Our study includes two sub-topics. In one topic, we studied the phase-dependent dynamic responses of human gait to impulsive force perturbations. This was conducted based on comparison between our theoretical modeling and experimental human motion measurements. We showed that phase-dependent modification of gait rhythm called phase retting could be optimally controlled to maximize the gait stability. The other topic was conducted on the coordinated gait pattern generation during a pedaling movement. The experiment was performed by healthy subjects and by patients with Parkinson's disease. The latter subjects showed various impaired (disordered) coordination. We proposed a nonlinear dynamical system model that could reproduce almost all observed patterns depending on a value of a single parameter of the model, implying that the emergence of the disordered coordination patterns was closely related to the bifurcation phenomena in the underlying dynamical system. These results suggested that, for the better maintenance of dynamic gait stability, the human brain needs some intelligent control strategies that take into account the nonlinear and oscillatory dynamics of the spinal cord and musculo-skeletal system.