Hogan Neville, Sternad Dagmar
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, USA.
Exp Brain Res. 2007 Jul;181(1):13-30. doi: 10.1007/s00221-007-0899-y. Epub 2007 May 26.
At present, rhythmic and discrete movements are investigated by largely distinct research communities using different experimental paradigms and theoretical constructs. As these two classes of movements are tightly interlinked in everyday behavior, a common theoretical foundation spanning across these two types of movements would be valuable. Furthermore, it has been argued that these two movement types may constitute primitives for more complex behavior. The goal of this paper is to develop a rigorous taxonomic foundation that not only permits better communication between different research communities, but also helps in defining movement types in experimental design and thereby clarifies fundamental questions about primitives in motor control. We propose formal definitions for discrete and rhythmic movements, analyze some of their variants, and discuss the application of a smoothness measure to both types that enables quantification of discreteness and rhythmicity. Central to the definition of discrete movement is their separation by postures. Based on this intuitive definition, certain variants of rhythmic movement are indistinguishable from a sequence of discrete movements, reflecting an ongoing debate in the motor neuroscience literature. Conversely, there exist rhythmic movements that cannot be composed of a sequence of discrete movements. As such, this taxonomy may provide a language for studying more complex behaviors in a principled fashion.
目前,有节奏的运动和离散运动主要由不同的研究群体使用不同的实验范式和理论框架进行研究。由于这两类运动在日常行为中紧密相连,跨越这两种运动类型的共同理论基础将很有价值。此外,有人认为这两种运动类型可能构成更复杂行为的基本要素。本文的目标是建立一个严谨的分类基础,这不仅能促进不同研究群体之间更好地交流,还有助于在实验设计中定义运动类型,从而阐明运动控制中有关基本要素的基本问题。我们提出了离散运动和有节奏运动的形式化定义,分析了它们的一些变体,并讨论了一种平滑度度量在这两种运动类型中的应用,该度量能够量化离散性和节奏性。离散运动定义的核心是它们由姿势分隔。基于这个直观的定义,有节奏运动的某些变体与一系列离散运动无法区分,这反映了运动神经科学文献中正在进行的一场争论。相反,存在一些无法由一系列离散运动组成的有节奏运动。因此,这种分类法可能为以有原则的方式研究更复杂的行为提供一种语言。