We discuss a new framework for understanding the structure of motor control. Our approach integrates existing models of motor control with the reality of hierarchical cortical processing and the parallel segregated loops that characterize cortical–subcortical connections. We also incorporate the recent claim that cortex functions via predictive representation and optimal information utilization. Our framework assumes that each cortical area engaged in motor control generates a predictive model of a different aspect of motor behavior. In maintaining these predictive models, each area interacts with a different part of the cerebellum and BG. These subcortical areas are thus engaged in domain-appropriate system identification and optimization. This refocuses the question of division of function among different cortical areas. What are the different aspects of motor behavior that are predictively modeled? We suggest that one fundamental division is between modeling of task and body whereas another is the model of state and action. Thus, we propose that the posterior parietal cortex, somatosensory cortex, premotor cortex, and motor cortex represent task state, body state, task action, and body action, respectively. In the second part of this review, we demonstrate how this division of labor can better account for many recent findings of movement encoding, especially in the premotor and posterior parietal cortices.

我们讨论了一个用于理解电机控制结构的新框架。我们的方法将现有的运动控制模型与分层皮层处理的现实以及表征皮层 - 皮层下连接的并行隔离环相结合。我们还结合了最近的说法，即皮层通过预测表示和最佳信息利用发挥作用。我们的框架假设参与运动控制的每个皮层区域都会生成运动行为不同方面的预测模型。在维护这些预测模型时，每个区域都与小脑和 BG 的不同部分相互作用。因此，这些皮层下区域从事适合领域的系统识别和优化。这重新聚焦了不同皮质区域之间的功能划分问题。预测性建模的运动行为有哪些不同方面？我们建议一个基本的划分是在任务和身体的建模之间，而另一个是状态和动作的模型。因此，我们提出后顶叶皮层、躯体感觉皮层、前运动皮层和运动皮层分别代表任务状态、身体状态、任务动作和身体动作。在本综述的第二部分，我们展示了这种分工如何更好地解释运动编码的许多最新发现，尤其是在运动前和顶叶后皮层。前运动皮层和运动皮层分别代表任务状态、身体状态、任务动作和身体动作。在本综述的第二部分，我们展示了这种分工如何更好地解释运动编码的许多最新发现，尤其是在运动前和顶叶后皮层。前运动皮层和运动皮层分别代表任务状态、身体状态、任务动作和身体动作。在本综述的第二部分，我们展示了这种分工如何更好地解释运动编码的许多最新发现，尤其是在运动前和顶叶后皮层。