Neuroscience has uncovered a fundamental mechanism of our social nature: human brain activity becomes synchronized with others in many social contexts involving interaction. Traditionally, social minds have been regarded as an exclusive property of living beings. Although large language models (LLMs) are widely accepted as powerful approximations of human behavior, with multi-LLM system being extensively explored to enhance their capabilities, it remains controversial whether they can be meaningfully compared to human social minds. In this work, we explore neural synchrony between socially interacting LLMs as an empirical evidence for this debate. Specifically, we introduce neural synchrony during social simulations as a novel proxy for analyzing the sociality of LLMs at the representational level. Through carefully designed experiments, we demonstrate that it reliably reflects both social engagement and temporal alignment in their interactions. Our findings indicate that neural synchrony between LLMs is strongly correlated with their social performance, highlighting an important link between neural synchrony and the social behaviors of LLMs. Our work offers a new perspective to examine the "social minds" of LLMs, highlighting surprising parallels in the internal dynamics that underlie human and LLM social interaction.

翻译：神经科学揭示了人类社交本质的一个基本机制：在涉及互动的多种社交情境中，人脑活动会与他人同步。传统上，社交心智被视为生物体的专属属性。尽管大型语言模型（LLMs）被广泛认为是人类行为的强大近似，并且多LLM系统已被广泛探索以增强其能力，但它们是否能在有意义程度上与人类社交心智相媲美，仍存在争议。在本工作中，我们探索社交互动的LLMs之间的神经同步性，作为这一辩论的实证证据。具体而言，我们引入社交模拟过程中的神经同步性，作为一种在表征层面分析LLMs社交性的新代理指标。通过精心设计的实验，我们证明该指标可靠地反映了它们互动中的社交参与度和时间对齐性。我们的研究结果表明，LLMs之间的神经同步性与其社交表现高度相关，突显了神经同步性与LLMs社交行为之间的重要联系。本工作为检验LLMs的“社交心智”提供了一个新视角，揭示了人类与LLM社交互动背后内部动态的惊人相似性。