128-channel resting-state recordings24 Major Depressive Disorder subjects and 29 Healthy Control subjectsAge range : 16-52 years oldIncludes: 1) demographic data, 2) psychological assessmentsFile size: 2.2GMd5sum: 7f5ea8c89c550443dc740c5c9e9d3867 Latest publication based on this dataset:Cai, H., Gao, Y., Sun, S., Li, N., Tian, F., Xiao, H., Li, J., Yang, Z., Li, X., Zhao, Q., Liu, Z., Yao, Z., Yang, M., Peng, H., Zhu, J., Zhang, X., Hu, X., & Hu, B. (2020). MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis. arXiv preprint arXiv:2002.09283 Download
Sun, S., Li, J., Chen, H., Gong, T., Li, X., & Hu, B. (2020). A study of resting-state EEG biomarkers for depression recognition. arXiv preprint arXiv:2002.11039.Download
Related references:Sun, S., Li, X., Zhu, J., Wang, Y., La, R., Zhang, X., ... & Hu, B. (2019). Graph Theory Analysis of Functional Connectivity in Major Depression Disorder With High-Density Resting State EEG Data. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(3), 429-439. Download
Peng, H., Xia, C., Wang, Z., Zhu, J., Zhang, X., Sun, S., ... & Li, X. (2019). Multivariate Pattern Analysis of EEG-Based Functional Connectivity: A Study on the Identification of Depression. IEEE Access, 7, 92630-92641. Download
Li, X., Jing, Z., Hu, B., Zhu, J., Zhong, N., Li, M., ... & Majoe, D. (2017). A resting-state brain functional network study in MDD based on minimum spanning tree analysis and the hierarchical clustering. Complexity, 2017. Download
Resting state:Download