Kodama Kentaro, Shimizu Daichi, Dale Rick, Sekine Kazuki
University Education Center, Tokyo Metropolitan University, Tokyo, Japan.
Department of Integrated Educational Sciences, Graduate School of Education, University of Tokyo, Tokyo, Japan.
Front Psychol. 2021 Apr 16;12:614431. doi: 10.3389/fpsyg.2021.614431. eCollection 2021.
An emerging perspective on human cognition and performance sees it as a kind of self-organizing phenomenon involving dynamic coordination across the body, brain and environment. Measuring this coordination faces a major challenge. Time series obtained from such cognitive, behavioral, and physiological coordination are often complicated in terms of non-stationarity and non-linearity, and in terms of continuous vs. categorical scales. Researchers have proposed several analytical tools and frameworks. One method designed to overcome these complexities is recurrence quantification analysis, developed in the study of non-linear dynamics. It has been applied in various domains, including linguistic (categorical) data or motion (continuous) data. However, most previous studies have applied recurrence methods individually to categorical or continuous data. To understand how complex coordination works, an integration of these types of behavior is needed. We aimed to integrate these methods to investigate the relationship between language (categorical) and motion (continuous) directly. To do so, we added temporal information (a time stamp) to categorical data (i.e., language), and applied joint recurrence analysis methods to visualize and quantify speech-motion coordination coupling during a rap performance. We illustrate how new dynamic methods may capture this coordination in a small case-study design on this expert rap performance. We describe a case study suggesting this kind of dynamic analysis holds promise, and end by discussing the theoretical implications of studying complex performances of this kind as a dynamic, coordinated phenomenon.
一种关于人类认知与表现的新观点认为，它是一种自组织现象，涉及身体、大脑和环境之间的动态协调。测量这种协调面临着重大挑战。从这种认知、行为和生理协调中获得的时间序列在非平稳性和非线性方面，以及在连续尺度与分类尺度方面往往很复杂。研究人员已经提出了几种分析工具和框架。一种旨在克服这些复杂性的方法是递归量化分析，它是在非线性动力学研究中发展起来的。它已被应用于各个领域，包括语言（分类）数据或运动（连续）数据。然而，以前的大多数研究都将递归方法单独应用于分类数据或连续数据。为了理解复杂的协调是如何工作的，需要对这些行为类型进行整合。我们旨在整合这些方法，以直接研究语言（分类）和运动（连续）之间的关系。为此，我们在分类数据（即语言）中添加了时间信息（时间戳），并应用联合递归分析方法来可视化和量化说唱表演期间的言语 - 运动协调耦合。我们通过一个关于这种专家级说唱表演的小案例研究设计来说明新的动态方法如何捕捉这种协调。我们描述了一个案例研究，表明这种动态分析具有前景，并在最后讨论了将这种复杂表演作为一种动态、协调现象进行研究的理论意义。
