NeuroBioInformatics Lab

In this research topic, we leverage multiple MRI modalities such as fMRI, DTI, and T1-weighted structural MRI, together with additional behavioral and demographic factors, to investigate how the brain influences human behavior. By combining complementary neuroimaging data, we aim to provide a more comprehensive understanding of brain function and structure.

• Gang Qu, Ziyu Zhou, Vince D. Calhoun, Aiying Zhang, Yu-Ping Wang. Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks. Medical Image Analysis, Volume 103, 2025, 103570. ISSN 1361-8415. https://doi.org/10.1016/j.media.2025.103570
• Weifeng Yu, Gang Qu, Young-geun Kim, Lei Xu, Aiying Zhang. A Novel GNN Framework Integrating Neuroimaging and Behavioral Information to Understand Adolescent Psychiatric Disorders. [PDF]

This research theme applies statistical inference to investigate how brain activity measures, such as intrinsic neural timescales (INT), Structural Functional Coupling (SFC), and Functional Connectivity (FC), relate to atypical brain development and mental health conditions. Our goal is to identify population-level differences and potential biomarkers that link altered brain dynamics with neurodevelopmental and neurodegenerative disorders.

• Aiying Zhang, Wengler, K., Zhu, X., Horga, G., Goldberg, T. E., Lee, S., & Alzheimer’s Disease Neuroimaging Initiative. (2024). Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer's disease. Journal of Neuroscience, 44(25).
• Solomon, A., Weifeng Yu, Rasero, J., & Aiying Zhang. (2025, April). Altered hierarchical rank in intrinsic neural time-scales in autism spectrum disorder. In Medical Imaging 2025: Clinical and Biomedical Imaging (Vol. 13410, pp. 157-163). SPIE.

This research theme integrates genomic data with brain imaging measures using approaches such as Mendelian Randomization and imaging-genetics frameworks, aiming to uncover biomarkers and improve diagnostic strategies for psychiatric disorders. For example, in Attention-Deficit/Hyperactivity Disorder (ADHD), this integrative analysis enables us to link genetic risk variants with alterations in brain networks, providing insights into causal mechanisms of atypical brain function and supporting early diagnosis and personalized treatment.

• C. Ji, S. Lee, S. Sequeira, J. Jin, Aiying Zhang. (2025). Leverage multimodal neuro-imaging and genetics to identify causal relationship between structural and functional connectivity and ADHD with Mendelian randomization. In Medical Imaging 2025: Imaging Informatics (Vol. 13411, pp. 187–193).