Grafton Scott T
UCSB Brain Imaging Center, The Sage Center for Study of Mind, University of California, Santa Barbara, California 93105, USA.
Ann N Y Acad Sci. 2009 Mar;1156:97-117. doi: 10.1111/j.1749-6632.2009.04425.x.
Understanding the goals or intentions of other people requires a broad range of evaluative processes including the decoding of biological motion, knowing about object properties, and abilities for recognizing task space requirements and social contexts. It is becoming increasingly evident that some of this decoding is based in part on the simulation of other people's behavior within our own nervous system. This review focuses on aspects of action understanding that rely on embodied cognition, that is, the knowledge of the body and how it interacts with the world. This form of cognition provides an essential knowledge base from which action simulation can be used to decode at least some actions performed by others. Recent functional imaging studies or action understanding are interpreted with a goal of defining conditions when simulation operations occur and how this relates with other constructs, including top-down versus bottom-up processing and the functional distinctions between action observation and social networks. From this it is argued that action understanding emerges from the engagement of highly flexible computational hierarchies driven by simulation, object properties, social context, and kinematic constraints and where the hierarchy is driven by task structure rather than functional or strict anatomic rules.
理解他人的目标或意图需要广泛的评估过程，包括对生物运动的解码、了解物体属性以及识别任务空间要求和社会背景的能力。越来越明显的是，这种解码部分基于我们自身神经系统对他人行为的模拟。本综述聚焦于依赖具身认知的动作理解方面，即关于身体及其与世界如何相互作用的知识。这种认知形式提供了一个基本的知识库，从中动作模拟可用于解读他人至少某些行为。近期关于动作理解的功能成像研究旨在定义模拟操作发生的条件，以及它如何与其他结构相关联，包括自上而下与自下而上的加工以及动作观察和社交网络之间的功能区别。由此认为，动作理解源于由模拟、物体属性、社会背景和运动学约束驱动的高度灵活的计算层次结构的参与，并且该层次结构由任务结构而非功能或严格的解剖学规则驱动。
