协同舞蹈即兴中的涌现性共处：神经与运动同步揭示耦合-解耦悖论
Emergent togetherness in collaborative dance improvisation: neural and motor synchronization reveal a coupling-decoupling paradox
AI总结：
研究通过舞蹈即兴探索神经-运动耦合系统的涌现协调，发现训练使脑内同步增强但人际运动同步降低，揭示共处源于共享神经意图而非相同动作。
摘要：
舞蹈即兴为研究耦合神经-运动系统涌现协调提供了丰富自然实验室。本文探讨训练如何塑造合作表演中运动与脑信号的自发同步模式。通过整合3D动作捕捉与超扫描EEG的双记录协议，参与者在生成式舞蹈训练前后进行自由互动式即兴。运动行为通过从运动元素分解中衍生出的时序α指数建模，揭示能量策略和自由度的波动。同步事件通过生物力学数据的Motif同步和神经数据的多层时变图进行量化，检测到非平凡的领先滞后依赖关系。结果表明，训练导致矛盾的分离：脑间同步增强，尤其在额叶，而人际运动同步降低。这种相反趋势表明，增强的参与感知促进神经对齐，同时扩大个体运动探索，从而减少运动耦合。我们的发现将协同即兴定位为一种复杂动态制度，在其中共处不源于相同运动输出，而源于分布于多层交互网络中的共享神经意图，体现了耦合-解耦悖论，即增加脑间同步支持更广泛且相互分歧的运动轨迹探索。这些结果突显了社会协调的非线性本质，为人类系统中创造性联合行动的建模提供了新途径。
英文摘要：
Collective improvisation in dance provides a rich natural laboratory for studying emergent coordination in coupled neuro-motor systems. Here, we investigate how training shapes spontaneous synchronization patterns in both movement and brain signals during collaborative performance. Using a dual-recording protocol integrating 3D motion capture and hyperscanning EEG, participants engaged in free, interaction-driven, and rule-based improvisation before and after a program of generative dance, grounded in cellular-automata. Motor behavior was modeled through a time-resolved α-exponent derived from Movement Element Decomposition scaling between mean velocity and displacement, revealing fluctuations in energetic strategies and degrees of freedom. Synchronization events were quantified using Motif Synchronization (biomechanical data) and multilayer Time-Varying Graphs (neural data), enabling the detection of nontrivial lead-lag dependencies beyond zero-lag entrainment. Results indicate that training produced an intriguing dissociation: inter-brain synchronization increased, particularly within the frontal lobe, while interpersonal motor synchrony decreased. This opposite trend suggests that enhanced participatory sense-making fosters neural alignment while simultaneously expanding individual motor explorations, thereby reducing coupling in movement. Our findings position collaborative improvisation as a complex dynamical regime in which togetherness emerges not from identical motor outputs but from shared neural intentionality distributed across multilayer interaction networks, exemplifying the coupling-decoupling paradox, whereby increasing inter-brain synchrony supports the exploration of broader and mutually divergent motor trajectories. These results highlight the nonlinear nature of social coordination, offering new avenues for modeling creative joint action in human systems.
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