标题： 金融连接组：一种模拟潜在市场动态的脑启发框架 显示英文标题

标题： The Financial Connectome: A Brain-Inspired Framework for Modeling Latent Market Dynamics

摘要： 我们提出了金融连接组学，这是一门新的科学学科，它通过大脑功能结构的视角来建模金融市场。 受神经科学中群体独立成分分析（groupICA）基础工作的启发，我们将市场重新想象为由潜在市场模块组成的高维动态系统，而不是资产的集合。 将股票视为功能节点，其共同波动视为集体认知的表现，我们引入了动态市场网络连通性（dMNC），这是动态功能连通性（dFNC）的金融类比。 这一受生物学启发的框架揭示了结构上持久的市场子网络，捕捉了状态变化，并在不依赖预测标签的情况下发现了系统性的早期预警信号。 我们的结果表明，市场像大脑一样，表现出模块化、自组织和随时间演化的架构。 这项工作开创了金融连接组学领域，这是系统神经科学和量化金融的原理性综合，旨在揭示复杂经济的隐藏逻辑。 显示英文摘要

摘要： We propose the Financial Connectome, a new scientific discipline that models financial markets through the lens of brain functional architecture. Inspired by the foundational work of group independent component analysis (groupICA) in neuroscience, we reimagine markets not as collections of assets, but as high-dimensional dynamic systems composed of latent market modules. Treating stocks as functional nodes and their co-fluctuations as expressions of collective cognition, we introduce dynamic Market Network Connectivity (dMNC), the financial analogue of dynamic functional connectivity (dFNC). This biologically inspired framework reveals structurally persistent market subnetworks, captures regime shifts, and uncovers systemic early warning signals all without reliance on predictive labels. Our results suggest that markets, like brains, exhibit modular, self-organizing, and temporally evolving architectures. This work inaugurates the field of financial connectomics, a principled synthesis of systems neuroscience and quantitative finance aimed at uncovering the hidden logic of complex economies.