Publications
Journal Publications
Submitted
Zhang, A., Zhang, G., Cai, B., Xiao, L., Hu, W., Stephen, J.M., Wilson, T.W., Calhoun, V.D. and Wang, Y.P. Functional Connectivity Estimation using Correlation-guided Bayesian Network to Understand Cognitive Ability Variations. Major revision for Human Brain Mapping. arxiv , Appendix , Code
Zhang, A., Pagliaccio, D., Marsh, R., Lee, S. Decoding Age specific Changes in Brain Functional Connectivity Using a Sliding window Based Clustering Method. bioRxiv , Code
Under Preparation
Zhang, A., Wang, Y., Hu, N., Ye, C. ConnectMVR: A Supervised Multimodal Brain Connectivity Analysis Tool for Predicting Clinical Outcomes and Identifying Associated Connectivity Patterns
Qu, G., Zhang, A. , Wang, Y-P. Harmonizing Structural and Functional Brain Connectivity: A Graph Neural Network Approach
2024
Sun, L., Zhang, A., Liang, F. Time-varying dynamic Bayesian network learning for an fMRI study of emotion processing. Statistics in Medicine.
Zhang, A., Zhu, X., Wrengler, K., Horga, G., Goldberg, T., Lee, S. Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer's disease. Journal of Neuroscience.
Zhang, A., Zhang, G., Cai, B., Stephen, J.M., Wilson, T.W., Calhoun, V.D. and Wang, Y.P. A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence. Network Neuroscience. Code
2022
Zhang, G., Cai, B., Zhang, A., Tu, Z., Xiao, L., Stephen, J. M., Wilson, T. W., Calhoun, V. D. and Wang, Y. P. (2022). Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model. NeuroImage, 260, 119451. Code
Cai, B., Zhou, Z., Zhang, A., Zhang, G., Xiao, L., J. M., Wilson, T. W., Calhoun, V. D. and Wang, Y.P. (2022) Functional connectomes incorporating phase synchronization for the characterization and prediction of individual differences. Journal of Neuroscience Methods, 372, 109539.
2021
Cai, B., Zhang, G., Zhang, A., Xiao, L., Hu, W., Stephen, J. M., Wilson, T. W., Calhoun, V. D. and Wang, Y.P. (2021) Functional connectome fingerprinting: identifying individuals and predicting cognitive functions via autoencoder. Human Brain Mapping 42.9, 26912705. Awarded "Top Downloaded Article" by Wiley
Hu, W., Meng, X., Bai, Y., Zhang, A., Cai, B., Stephen, J. M., Wilson, T. W., Calhoun, V. D. and Wang, Y.P. (2021) Interpretable multimodal fusion networks reveal mechanisms of brain cognition. IEEE Transactions on Medical Imaging, vol. 40, no. 5, pp. 14741483.
2020
Zhou, Z., Cai, B., Zhang, G., Zhang, A., Calhoun, V.D. and Wang, Y.P., 2020. Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI. NeuroImage, p.117190.
Xiao, L., Zhang, A., Cai, B., Stephen, J. M., Wilson, T. W., Calhoun, V. D. and Wang, Y.P. (2020) Correlation Guided Graph Learning to Estimate Functional Connectivity Networks from fMRI Data. IEEE Transactions on Biomedical Engineering, vol. 68, no. 4, pp. 11541165.
Cai, B., Zhang, G., Zhang, A., Hu, W., Stephen, J. M., Wilson, T. W., Calhoun, V. D. and Wang, Y.P. (2020). A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity. Journal of Neuroscience Methods, 332, p.108531.
2019
Hu, W., Cai, B., Zhang, A., Calhoun, V.D., and Wang, Y.P. (2019). Deep collaborative learning with application to multimodal brain development study. IEEE Transactions on Biomedical Engineering, 66(12), 3346-3359.
Zhang, A., Cai, B., Hu, W., Jia, B., Liang, F., Wilson, T.W., Stephen, J.M., Calhoun, V.D. and Wang, Y.P., 2019. Joint Bayesian-incorporating estimation of multiple Gaussian graphical models to study brain connectivity development in adolescence. IEEE transactions on medical imaging, 39(2), 357-365.
Zhang, A., Fang, J., Hu, W., Calhoun, V. and Wang, Y.P., 2019. A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging Genetics. IEEE/ACM transactions on computational biology and bioinformatics. DOI: 10.1109/TCBB.2019. 2950904 Appendix , Code
Hu, W., Zhang, A., Cai, B., Calhoun, V. and Wang, Y.P., 2019. Distance canonical correlation analysis with application to an imaging-genetic study. Journal of Medical Imaging, 6(2), p.026501.
Zhang, G., Cai, B., Zhang, A., Stephen, J.M., Wilson, T.W., Calhoun, V.D. and Wang, Y.P., 2019. Estimating dynamic functional brain connectivity with a sparse hidden Markov model. IEEE transactions on medical imaging, 39(2), 488-498.
Cai, B., Zhang, G., Hu, W., Zhang, A., Zille, P., Zhang, Y., Stephen, J.M., Wilson, T.W., Calhoun, V.D. and Wang, Y.P., 2019. Refined measure of functional connectomes for improved identifiability and prediction. Human brain mapping, 40(16), pp.4843-4858.
2018
Cai, B., Zhang, G., Zhang, A., Stephen, J.M., Wilson, T.W., Calhoun, V.D. and Wang, Y.P., 2018. Capturing dynamic connectivity from resting state fMRI using time-varying graphical LASSO. IEEE Transactions on Biomedical Engineering, 66(7), pp.1852-1862.
Zhang, A., Fang, J., Liang, F., Calhoun, V.D. and Wang, Y.P., 2018. Aberrant Brain Connectivity in Schizophrenia Detected via a Fast Gaussian Graphical Model. IEEE journal of biomedical and health informatics, 23(4), pp.1479-1489. Appendix
Conference Publications
Mutu, D., Ji, K., He, X., Lee, S., Sequeira S. and Zhang, A. 2024, May. Associations Between Brain Connectivity and Psychiatric Symptoms in Children: Insights into Adolescent Mental Health. Student Presentation at 2024 Systems and Information Engineering Design Symposium (SIEDS)(pp. 36-41). IEEE.
Zhang, A., Jia, B. and Wang, Y.P., 2018, March. Tracking the development of brain connectivity in adolescence through a fast Bayesian integrative method. In Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications (Vol. 10579, p. 105790O). International Society for Optics and Photonics.
Zhang, A., Fang, J., Calhoun, V.D. and Wang, Y.P., 2018, April. High dimensional latent Gaussian copula model for mixed data in imaging genetics. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)(pp. 105-109). IEEE.
Zhang, A., Calhoun, V.D. and Wang, Y.P., 2019, March. Joint Gaussian copula model for mixed data with application to imaging epigenetics study of schizophrenia. In Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications (Vol. 10954, p. 109540R). International Society for Optics and Photonics.
Zhang, A., Zhang, G., Calhoun, V.D. and Wang, Y.P. (2020, March). Causal brain network in schizophrenia by a two-step Bayesian network analysis. In Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications (Vol. 11318, p. 1131817). International Society for Optics and Photonics.
Zhang, G., Zhang, A., Calhoun, V.D. and Wang, Y.P. (2020, February). A causal brain network estimation method leveraging Bayesian analysis and the PC algorithm. In Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging (Vol. 11317, p. 113170X). International Society for Optics and Photonics.