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Windowed Multiscale Synchrony: Modeling Time-Varying and Scale-Localized Interpersonal Coordination Dynamics
Social Cognitive and Affective Neuroscience ( IF 4.2 ) Pub Date : 2020-09-30 , DOI: 10.1093/scan/nsaa130
Aaron D Likens 1 , Travis J Wiltshire 2
Affiliation  

Social interactions are pervasive in human life with varying forms of interpersonal coordination emerging and spanning different modalities (e.g., behaviors, speech/language, and neurophysiology). However, during social interactions, as in any dynamical system, patterns of coordination form and dissipate at different scales. Historically, researchers have used aggregate measures to capture coordination over time. While those measures (e.g., mean relative phase, cross-correlation, coherence) have provided a wealth of information about coordination in social settings, some evidence suggests that multiscale coordination may change over the time course of a typical empirical observation. To address this gap, we demonstrate an underutilized method, windowed multiscale synchrony, that moves beyond quantifying aggregate measures of coordination by focusing on how the relative strength of coordination changes over time and the scales that comprise social interaction. This method involves using a wavelet transform to decompose time series into component frequencies (i.e., scales), preserving temporal information and then quantifying phase synchronization at each of these scales. We apply this method to both simulated and empirical interpersonal physiological and neuromechanical data. We anticipate that demonstrating this method will stimulate new insights on the mechanisms and functions of synchrony in interpersonal contexts using neurophysiological and behavioral measures.

中文翻译:

窗口化多尺度同步:时变和尺度局部人际协调动力学建模

社会互动在人类生活中无处不在,出现了各种形式的人际协调并跨越了不同的方式(例如行为,言语/语言和神经生理学)。但是,在社会互动过程中,就像在任何动力系统中一样,协调模式在不同的规模上形成并消散。从历史上看,研究人员一直使用汇总指标来捕获一段时间内的协调性。这些措施(例如,平均相对相位,互相关,一致性)已提供了大量有关社会环境中协调的信息,但一些证据表明,多尺度协调可能会随着典型经验观察的时间而变化。为了解决这一差距,我们展示了一种未充分利用的方法,即窗口多尺度同步,通过集中于协调的相对强度如何随时间变化以及构成社会互动的规模,这一方法超越了量化协调的总体指标。该方法涉及使用小波变换将时间序列分解为分量频率(即标度),保留时间信息,然后在这些标度的每一个处量化相位同步。我们将这种方法应用于模拟和经验的人际生理和神经力学数据。我们预计,演示这种方法将激发使用神经生理学和行为学方法在人际环境中同步机制和功能的新见解。该方法涉及使用小波变换将时间序列分解为分量频率(即标度),保留时间信息,然后在这些标度的每一个处量化相位同步。我们将这种方法应用于模拟和经验的人际生理和神经力学数据。我们预计,演示这种方法将激发使用神经生理学和行为学方法在人际环境中同步机制和功能的新见解。该方法涉及使用小波变换将时间序列分解为分量频率(即标度),保留时间信息,然后在这些标度的每一个处量化相位同步。我们将这种方法应用于模拟和经验的人际生理和神经力学数据。我们预计,演示这种方法将激发使用神经生理学和行为学方法在人际环境中同步机制和功能的新见解。
更新日期:2020-09-30
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