May 21, 2026 Webinar
A Regularized Blind Source Separation Framework for Unveiling Hidden Sources of Brain Connectome
Ying Guo, PhD
Abstract:
Brain connectomics has become a central tool in neuroimaging for advancing our understanding of neural circuits and their roles in neurodevelopment, mental illness, and aging. However, these analyses face major challenges, including the high dimensionality of brain networks, the presence of latent sources underlying observed connectivity, and the large number of connections that can lead to spurious findings. In this talk, we introduce a regularized blind source separation (BSS) framework for reliable mapping of neural circuits from both static and dynamic functional connectomes, and for integrative analysis of multi-view connectomes across multiple imaging modalities and cognitive states. The proposed methods leverage low-rank factorization, a novel angle-based sparsity control, and regularizations to achieve efficient and robust source separation of connectivity matrices. We develop highly efficient algorithms to solve the non-convex optimization problem for learning the proposed models. Applications to large-scale neuroimaging studies demonstrate substantially improved reproducibility in identifying neural circuits and their associations with demographic and clinical phenotypes. The proposed framework further uncovers dynamic expression profiles of neural circuits and their synchronization patterns, identifies cohesive structural–functional connections, and reveals both shared circuits consistently engaged across resting-state and task conditions as well as circuits specific to particular cognitive tasks or modalities. These results provide new insights into network organization, dynamics and adaptations.
Short Bio:
Ying Guo is Professor in the Department of Biostatistics and Bioinformatics at Emory University and an appointed Graduate Faculty of the Emory Neuroscience Program. She is a Founding Member and current Director of the Center for Biomedical Imaging Statistics (CBIS) at Emory. Dr. Guo's main research areas include brain network and connectome analysis, blind source separation, multimodal neuroimaging, imaging-based prediction methods, and agreement/reproducibility methods.
Hope to see you at the webinar!