二元协调过程中联合脑状态的符号动力学
Symbolic dynamics of joint brain states during dyadic coordination
AI总结：
本文提出用联合符号动力学分析双人协调任务中的脑状态演化，发现交互条件主要通过改变联合符号的驻留时间、序列基序长度和状态网络拓扑来影响同步与切分协调的稳定性。
摘要：
我们提出了一种新方法来研究支持个体间行为协调的脑机制。由脑区之间功能连接模式定义的单个个体脑状态被用来创建两个或更多个体共同执行任务时脑状态演化的联合符号表征。这些符号动力学可以被分析，以揭示与协调或其他交互行为相关的联合脑状态动力学方面。我们将该方法应用于来自成对被试的同步脑电图（EEG）数据，这些被试在三种不同交互条件（无耦合、领导者-跟随者、相互）下从事两种不同的手指敲击协调任务模式（同步和切分），以探索多人运动协调的神经机制。我们的结果表明，在不同交互条件下，二元组大多表现出相同的联合符号——最重要的差异反映在符号动力学中。递归分析表明，交互影响特定联合符号中的驻留时间以及联合符号序列的结构（基序长度）。在同步中，增加反馈通过更长的驻留时间和基序长度促进稳定性。在切分中，领导者-跟随者交互增强稳定性（增加驻留时间和基序长度），但相互反馈显著降低稳定性。网络分析揭示了随任务和反馈而发生的不同拓扑变化。在同步中，更强的耦合稳定了少数状态，限制了状态间流动的模式，保持了联合脑状态的核心-边缘结构。在切分中，在更大的一组联合脑状态之间更分散的流动降低了核心联合脑状态的主导性。
英文摘要：
We propose a novel approach to investigate the brain mechanisms that support coordination of behavior between individuals. Brain states in single individuals defined by the patterns of functional connectivity between brain regions are used to create joint symbolic representations of the evolution of brain states in two or more individuals performing a task together. These symbolic dynamics can be analyzed to reveal aspects of the dynamics of joint brain states that are related to coordination or other interactive behaviors. We apply this approach to simultaneous electroencephalographic (EEG) data from pairs of subjects engaged in two different modes of finger-tapping coordination tasks (synchronization and syncopation) under different interaction conditions (Uncoupled, Leader-Follower, and Mutual) to explore the neural mechanisms of multi-person motor coordination. Our results reveal that the dyads exhibit mostly the same joint symbols in different interaction conditions - the most important differences are reflected in the symbolic dynamics. Recurrence analysis shows that interaction influences the dwell time in specific joint symbols and the structure of joint symbol sequences (motif length). In synchronization, increasing feedback promotes stability with longer dwell times and motif length. In syncopation, Leader-Follower interactions enhance stability (increase dwell time and motif length), but Mutual feedback dramatically reduces stability. Network analysis reveals distinct topological changes with task and feedback. In synchronization, stronger coupling stabilizes a few states restricting the pattern of flow between states, preserving a core-periphery structure of the joint brain states. In syncopation, a more distributed flow amongst a larger set of joint brain states reduces the dominance of core joint brain states.
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