Department of Biomechanics, University of Nebraska at Omaha, 6001 Dodge Street Omaha, NE 68182.
Department of Cognitive Science & Artificial Intelligence, Tilburg University, (Room D104) Warandelaan 2, 5037 AB, Tilburg, The Netherlands.
Soc Cogn Affect Neurosci. 2021 Jan 18;16(1-2):232-245. doi: 10.1093/scan/nsaa130.
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.
社会互动在人类生活中无处不在，各种形式的人际协调不断涌现，并跨越不同的模式（例如行为、言语/语言和神经生理学）。然而，在社会互动中，与任何动力系统一样，协调模式会在不同的尺度上形成和消散。历史上，研究人员曾使用综合指标来捕捉随时间的协调。虽然这些指标（例如平均相对相位、互相关、相干性）为社会环境中的协调提供了丰富的信息，但一些证据表明，多尺度协调可能会随典型实证观察的时间进程而变化。为了解决这一差距，我们展示了一种未被充分利用的方法，即窗口化多尺度同步，它超越了通过关注协调的相对强度随时间的变化以及构成社会互动的尺度来量化协调的综合指标。该方法涉及使用小波变换将时间序列分解为组成频率（即尺度），保留时间信息，然后在每个尺度上量化相位同步。我们将该方法应用于人际生理和神经力学的模拟和实证数据。我们预计，演示这种方法将使用神经生理学和行为学测量手段，激发人们对人际背景下同步的机制和功能的新见解。
