BrainNet Studio：脑网络构建、智能分析与可视化的统一工具包
BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization
- College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics（南京航空航天大学人工智能学院）
- School of Computer Science and Technology, Harbin Institute of Technology（哈尔滨工业大学计算机科学与技术学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
BrainNet Studio是一个统一工具包，集成27种算法与大型语言模型，支持静态和动态脑网络的构建、分析、可视化及解释，为脑连接组研究提供可扩展平台。
AI中文摘要：
脑网络刻画了脑区之间的结构和功能关系，并支持对认知、脑疾病和脑机接口的研究。其时变拓扑和高阶时空依赖性无法被传统的静态网络充分表征。现有工具主要关注静态连接组，并且对动态网络建模与现代图学习和序列学习方法的集成有限。我们提出了BrainNet Studio，一个用于静态和动态脑网络分析的集成工具包。它提供了一个统一的工作流程，涵盖网络构建、特征提取、预测建模、候选生物标志物识别、可视化和辅助解释。该工具包集成了27种算法，包括深度学习、图神经网络和时空序列模型，以支持分类以及判别性脑区和连接的识别。一个大型语言模型在个体和群体水平上生成可被研究者验证的功能连接、结构连接和结构-功能耦合的摘要。在一个一致的计算框架内，用户可以配置分析任务、比较方法、检查输出并扩展功能，而无需重复组装特定应用的流程。BrainNet Studio为认知神经科学中的连接组分析、脑疾病的探索性研究以及脑机接口提供了一个实用且可扩展的平台。该工具包可在https URL公开获取。
英文摘要：
Brain networks characterize structural and functional relationships among brain regions and support research on cognition, brain disorders, and brain-computer interfaces. Their time-varying topology and higher-order spatiotemporal dependencies are not adequately represented by conventional static networks. Existing tools primarily focus on static connectomes and provide limited integration of dynamic network modeling with modern graph and sequence learning methods. We present BrainNet Studio, an integrated toolkit for static and dynamic brain network analysis. It provides a unified workflow encompassing network construction, feature extraction, predictive modeling, candidate biomarker identification, visualization, and assisted interpretation. The toolkit integrates 27 algorithms, including deep learning, graph neural networks, and spatiotemporal sequence models, to support classification and the identification of discriminative brain regions and connections. A large language model generates researcher-verifiable summaries of functional connectivity, structural connectivity, and structure-function coupling at individual and group levels. Within a consistent computational framework, users can configure analytical tasks, compare methods, inspect outputs, and extend functionality without repeatedly assembling application-specific pipelines. BrainNet Studio provides a practical and extensible platform for connectome analysis in cognitive neuroscience, exploratory studies of brain disorders, and brain-computer interfaces. The toolkit is publicly available at https://github.com/xbrainnet/Brainnet-Studio.
