Human interaction is often accompanied by synchronized bodily rhythms. Such synchronization may emerge spontaneously as when a crowd's applause turns into a steady beat, be encouraged as in nursery rhymes, or be intentional as in the case of playing music together. The latter has been extensively studied using joint finger-tapping paradigms as a simplified version of rhythmic interpersonal synchronization. A key finding is that synchronization in such cases is multifaceted, with synchronized behaviour resting upon different synchronization strategies such as mutual adaptation, leading–following and leading–leading. However, there are multiple open questions regarding the mechanism behind these strategies and how they develop dynamically over time. Here, we propose a metastable attractor model of self–other integration (MEAMSO). This model conceptualizes dyadic rhythmic interpersonal synchronization as a process of integrating and segregating signals of self and other. Perceived sounds are continuously evaluated as either being attributed to self-produced or other-produced actions. The model entails a metastable system with two particular attractor states: one where an individual maintains two separate predictive models for self- and other-produced actions, and the other where these two predictive models integrate into one. The MEAMSO explains the three known synchronization strategies and makes testable predictions about the dynamics of interpersonal synchronization both in behaviour and the brain.

This article is part of the theme issue ‘Synchrony and rhythm interaction: from the brain to behavioural ecology’.

人类互动通常伴随着同步的身体节律。当人群的掌声变成稳定的节拍时，这种同步可能会自然而然地出现，像童谣那样受到鼓励，或者像一起演奏音乐那样是有意识的。后者已被广泛研究，使用联合手指敲击范例作为节奏人际同步的简化版本。一个关键发现是，这种情况下的同步是多方面的，同步行为取决于不同的同步策略，例如相互适应、领先-跟随和领先-领先。然而，关于这些策略背后的机制以及它们如何随着时间的推移动态发展，存在多个悬而未决的问题。在这里，我们提出了一个自我-其他整合的亚稳态吸引子模型（MEAMSO）。该模型将二元节奏人际同步概念化为整合和分离自我和他人信号的过程。感知到的声音被持续评估为归因于自己产生的或其他产生的动作。该模型需要一个具有两种特定吸引子状态的亚稳态系统：一种是个人为自己和其他人产生的行为维护两个独立的预测模型，另一种是这两个预测模型整合为一个。MEAMSO 解释了三种已知的同步策略，并对行为和大脑中的人际同步动态做出可测试的预测。

这篇文章是主题问题“同步和节奏交互：从大脑到行为生态学”的一部分。