Imamizu Hiroshi, Kawato Mitsuo
Biological Information and Communications Technology Group, National Institute of Information and Communications Technology, 2-2-2, Hikaridai, Keihanna Science City, Kyoto, 619-0288, Japan.
Psychol Res. 2009 Jul;73(4):527-44. doi: 10.1007/s00426-009-0235-1. Epub 2009 Apr 4.
Humans can guide their actions toward the realization of their intentions. Flexible, rapid and precise realization of intentions and goals relies on the brain learning to control its actions on external objects and to predict the consequences of this control. Neural mechanisms that mimic the input-output properties of our own body and other objects can be used to support prediction and control, and such mechanisms are called internal models. We first summarize functional neuroimaging, behavioral and computational studies of the brain mechanisms related to acquisition, modular organization, and the predictive switching of internal models mainly for tool use. These mechanisms support predictive control and flexible switching of intentional actions. We then review recent studies demonstrating that internal models are crucial for the execution of not only immediate actions but also higher-order cognitive functions, including optimization of behaviors toward long-term goals, social interactions based on prediction of others' actions and mental states, and language processing. These studies suggest that a concept of internal models can consistently explain the neural mechanisms and computational principles needed for fundamental sensorimotor functions as well as higher-order cognitive functions.
人类能够引导自身行为以实现其意图。灵活、快速且精确地实现意图和目标依赖于大脑学会控制其对外部物体的行为，并预测这种控制的后果。模仿我们自身身体和其他物体的输入输出特性的神经机制可用于支持预测和控制，此类机制被称为内部模型。我们首先总结主要针对工具使用的与内部模型的获取、模块化组织以及预测性切换相关的大脑机制的功能神经影像学、行为学和计算研究。这些机制支持有意行为的预测性控制和灵活切换。然后，我们回顾近期的研究，这些研究表明内部模型不仅对即时行为的执行至关重要，而且对高阶认知功能也至关重要，包括针对长期目标的行为优化、基于对他人行为和心理状态的预测的社会互动以及语言处理。这些研究表明，内部模型的概念能够连贯地解释基本感觉运动功能以及高阶认知功能所需的神经机制和计算原理。
