Hyper-adaptability is an ability of humans and animals to adapt to large-scale changes in the nervous system or the musculoskeletal system, such as strokes and spinal cord injuries. Although this adaptation may involve similar neural processes with normal adaptation to usual environmental and body changes in daily lives, it can be fundamentally different because it requires ‘construction’ of the neural structure itself and ‘reconstitution’ of sensorimotor control rules to compensate for the changes in the nervous system. In this survey paper, we aimed to provide an overview on how the brain structure changes after brain injury and recovers through rehabilitation. Next, we demonstrated the recent approaches used to apply computational and neural network modeling to recapitulate motor control and motor learning processes. Finally, we discussed future directions to bridge the gap between conventional physiological and modeling approaches to understand the neural and computational mechanisms of hyper-adaptability and its applications to clinical rehabilitation.

超适应能力是人类和动物适应神经系统或肌肉骨骼系统大规模变化的能力，例如中风和脊髓损伤。尽管这种适应可能涉及与日常生活中通常环境和身体变化的正常适应相似的神经过程，但它可能有根本的不同，因为它需要“构建”神经结构本身和“重建”感觉运动控制规则来补偿这些变化在神经系统中。在这篇调查论文中，我们旨在概述脑损伤后大脑结构如何变化并通过康复恢复。接下来，我们展示了最近用于应用计算和神经网络建模来概括运动控制和运动学习过程的方法。最后，