Publications

✱ co-first author

  1. Wang Y, Li S, He J, Peng L, Wang Q, Zou X, Tudorascu DL, Schaeffer DJ, Schaeffer L, Szczupak D, Park JE, Rizzo SJS, Carter GW, Silva AC, and Zhang T (2025). Analysis of Functional Connectivity Changes from Childhood to Old Age: A Study Using HCP-D, HCP-YA, and HCP-A Datasets. Imaging Neuroscience, 3: imag_a_00503. DOI: https://doi.org/10.1162/imag_a_00503.

  2. Corliss B, Wang Y, Driscoll F, Shakeri H, and Bourne PE (2024). MAD-FC: A Fold Change Visualization with Readability, Proportionality, and Symmetry. PLOS One, 19(5). DOI: https://doi.org/10.1371/journal.pone.0304632.

  3. Li S, Wang Y✱, Peng L, Tudorascu DL, Yan G, He J, and Zhang T (2023). Whole-Brain Directed Network Analysis of fMRI Data. In press, Statistics and Its Interface.

  4. Wang Y, Yan G, Wang X, Li S, Peng L, Tudorascu DL, and Zhang T (2022). A Variational Bayesian Approach to Identifying Whole-Brain Directed Networks with fMRI Data. The Annals of Applied Statistics, 17(1): 518-538. DOI: https://doi.org/10.1214/22-AOAS1640.

  5. Li H, Wang Y✱, Yan G, Sun Y, Tanabe S, Liu C-C, Quigg M, and Zhang T (2021). A Bayesian State-Space Approach to Mapping Directional Brain Networks. Journal of the American Statistical Association, 116(536): 1637-1647. DOI: https://doi.org/10.1080/01621459.2020.1865985.

  6. Li H, Wang Y✱, Tanabe S, Sun Y, Yan G, Quigg M, and Zhang T (2021). Mapping Epileptic Directional Brain Networks Using Intracranial EEG Data. Biostatistics, 22(3): 613-628. DOI: https://doi.org/10.1093/biostatistics/kxz056.

  7. Zhang T, Pham M, Yan G, Wang Y, Medina-Devilliers S, and Coan JA (2021). Spatial-Temporal Analysis of Multi-Subject Functional Magnetic Resonance Imaging Data. Econometrics and Statistics. DOI: https://doi.org/10.1016/j.ecosta.2021.02.006.

  8. Zhang T, Sun Y, Li H, Yan G, Tanabe S, Miao R, Wang Y, Caffo B, and Quigg M (2020). Bayesian Inference of a Directional Brain Network for Intracranial EEG Data. Computational Statistics and Data Analysis, 144: 106847. DOI: https://doi.org/10.1016/j.csda.2019.106847.

Under review

  1. Wang Y, Wang W, and Guo Y (2025). Statistical AI Modeling of Whole-Brain Effective Connectivity Reveals Sex-Specific Neurodevelopment of Directed Connectome. Under review.

  2. Wang Y, Lukemire J, Ran J, and Guo Y (2025). Uncovering Reliable Neural Circuitry in the Developing Connectome Using a Bayesian Blind Source Separation Framework. Under review.

  3. Yang G, Wang Y, Lukemire J, and Guo Y (2025). Multi-View LOCUS: A Novel Joint Decomposition Method for Investigating Latent Neurocircuitry Traits Underlying Multi-View Brain Connectome. Under review.

  4. Lukemire J, Wang Y, and Guo Y (2025). A General Framework for Investigating Neurodevelopment of Brain Functional Networks Using Multi-Site and Longitudinal Neuroimaging. Under review.

  5. Cho H, Wang Y, and Yu S (2025). Distributed Multivariate Spline Estimation for Longitudinal Image-on-Scalar Regression. Under review.

Preprints

  1. Wang Y, Yan G, Tanabe S, Liu C-C, Moosa S, Quigg M, and Zhang T. High-Dimensional Directional Brain Network Analysis for Focal Epileptic Seizures. arXiv: https://arxiv.org/abs/2208.07991.

  2. Peng L, Wang Q, Wang Y, He J, Zou X, Li S, Tudorascu DL, Schaeffer DJ, Schaeffer L, Szczupak D, Rothwell ES, Rizzo SJS, Carter GW, Silva AC, and Zhang T. Random Effects Models for Understanding Variability and Association between Brain Functional and Structural Connectivity. arXiv: https://arxiv.org/abs/2508.02908.