High-level motor computations reflect abstract components far apart from the mere motor performance. Neural correlates of these computations have been explored both in nonhuman and human primates, supporting the idea that our brain recruits complex nodes for motor representations. Of note, these computations have exciting implications for social cognition, and they also entail important challenges in the context of autism. Here, we focus on these challenges benefiting from recent studies addressing motor interference, motor resonance, and high-level motor planning. In addition, we suggest new ideas about how one maps and shares the (motor) space with others. Taken together, these issues inspire intriguing and fascinating questions about the social tendency of our high-level motor computations, and this tendency may indicate that we are “motorically” wired to others. Thus, after furnishing preliminary insights on putative neural nodes involved in these computations, we focus on how the hypothesized social nature of high-level motor computations may be anomalous or limited in autism, and why this represents a critical challenge for the future.

高级电动机计算所反映的抽象成分与单纯的电动机性能相去甚远。已经在非人类和人类灵长类动物中探索了这些计算的神经相关性，支持了我们的大脑募集复杂的节点用于运动表征的想法。值得注意的是，这些计算对于社会认知具有令人兴奋的意义，并且在自闭症的背景下也带来了重要的挑战。在这里，我们将重点关注这些挑战，这些挑战得益于针对电机干扰，电机共振和高级电机计划的最新研究。此外，我们建议有关一个人如何映射和共享（运动）空间的新想法。综上所述，这些问题激发了人们对我们高级运动计算的社会趋势的兴趣，并产生了令人着迷的问题，这种趋势可能表明我们“机动”地与他人联系。因此，在对这些计算中涉及的假定神经节点提供了初步的见识之后，我们将重点研究高级运动计算的假设社会性质如何可能在自闭症中异常或受到限制，以及为什么这代表着对未来的严峻挑战。