Abstract
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.
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Publication details
- Journal
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- Open access
- Green open access
Cite this article
APA 7
Zeng, X., Li, S., Liu, Y., Tian, C., Zhang, D., & Zhu, Q. (2026). BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization. https://omanscience.com/en/articles/brainnet-studio-a-unified-toolkit-for-brain-network-construction-intelligent-analysis-and-visualization
MLA 9
Zeng, Xiwei, et al. "BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization." https://omanscience.com/en/articles/brainnet-studio-a-unified-toolkit-for-brain-network-construction-intelligent-analysis-and-visualization.
Chicago (author–date)
Zeng, Xiwei, Shengrong Li, Yiheng Liu, Chunwei Tian, Daoqiang Zhang, and Qi Zhu. 2026. "BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization." https://omanscience.com/en/articles/brainnet-studio-a-unified-toolkit-for-brain-network-construction-intelligent-analysis-and-visualization.
Harvard
Zeng, X., Li, S., Liu, Y., Tian, C., Zhang, D. and Zhu, Q. (2026) 'BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization', Available at: https://omanscience.com/en/articles/brainnet-studio-a-unified-toolkit-for-brain-network-construction-intelligent-analysis-and-visualization.
Vancouver
Zeng X, Li S, Liu Y, Tian C, Zhang D, Zhu Q. BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization. https://omanscience.com/en/articles/brainnet-studio-a-unified-toolkit-for-brain-network-construction-intelligent-analysis-and-visualization
IEEE
X. Zeng, S. Li, Y. Liu, C. Tian, D. Zhang, and Q. Zhu, "BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization," https://omanscience.com/en/articles/brainnet-studio-a-unified-toolkit-for-brain-network-construction-intelligent-analysis-and-visualization.