Bipedal locomotion is a basic motor activity that requires simultaneous control of multiple muscles. Physiological experiments suggest that the nervous system controls bipedal locomotion efficiently by using motor modules of synergistic muscle activations. If these modules were merged, abnormal locomotion patterns would be realized as observed in patients with neural impairments such as chronic stroke. However, sub-acute patients have been reported not to show such merged motor modules. Therefore, in this study, we examined what conditions in the nervous system merges motor modules. we built a two-dimensional bipedal locomotion model that included a musculoskeletal model with 7 segments and 18 muscles, a neural system with a hierarchical central pattern generator (CPG), and various feedback inputs from reflex organs. The CPG generated synergistic muscle activations comprising 5 motor modules to produce locomotion phases. Our model succeeded to acquire stable locomotion by using the motor modules and reflexes. Next, we examined how a pathological condition altered motor modules. Specifically, we weakened neural inputs to muscles on one leg to simulate a stroke condition. Immediately after the simulated stroke, the model did not walk. Then, internal parameters were modified to recover stable locomotion. We refitted either (a) reflex parameters or (b) CPG parameters to compensate the locomotion by adapting (a) reflexes or (b) the controller. Stable locomotion was recovered in both conditions. However the motor modules were merged only in (b). These results suggest that light or sub-acute stroke patients, who can compensate stable locomotion by just adapting reflexes, would not show merge of motor modules, whereas severe or chronic patients, who needed to adapt the controller for compensation, would show the merge, as consistent with experimental findings.

中文翻译：

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病理状况影响双足运动模型中的电机模块。

双足运动是一项基本的运动活动，需要同时控制多条肌肉。生理实验表明，神经系统通过使用协同肌肉激活的运动模块来有效控制双足运动。如果将这些模块合并，则会在患有神经功能障碍（例如慢性中风）的患者中观察到异常的运动模式。然而，据报道，亚急性患者没有显示出这种合并的运动模块。因此，在这项研究中，我们检查了神经系统中哪些条件合并了运动模块。我们建立了一个二维双足运动模型，其中包括具有7段和18条肌肉的肌肉骨骼模型，具有分层中央模式发生器（CPG）的神经系统以及来自反射器官的各种反馈输入。CPG产生包括5个运动模块的增效肌肉激活，以产生运动阶段。我们的模型通过使用电机模块和反射器成功获得了稳定的运动。接下来，我们检查了病理状况如何改变运动模块。具体来说，我们减弱了一条腿上肌肉的神经输入以模拟中风情况。模拟行程之后，模型立即不走动。然后，修改内部参数以恢复稳定的运动。我们调整了（a）反射参数或（b）CPG参数，以通过调整（a）反射或（b）控制器来补偿运动。在两种情况下都恢复了稳定的运动。但是，仅在（b）中合并了电机模块。这些结果表明，轻度或亚急性中风患者，