3 citations · 5 across the 7 of their papers we have counts for
7 papers
Personalized Federated Dictionary Learning for Modeling Heterogeneity in Multi-site fMRI Data
Yipu Zhang, Chengshuo Zhang, Ziyu Zhou +5
Data privacy constraints pose significant challenges for large-scale neuroimaging analysis, especially in multi-site functional magnetic resonance imaging (fMRI) studies, where sit…
A Deep Spatio-Temporal Architecture for Dynamic Effective Connectivity Network Analysis Based on Dynamic Causal Discovery
Faming Xu, Yiding Wang, Chen Qiao +5
Dynamic effective connectivity networks (dECNs) reveal the changing directed brain activity and the dynamic causal influences among brain regions, which facilitate the identificati…
A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds
Anton Orlichenko, Gang Qu, Ziyu Zhou +7
Objective: fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinic…
An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis
Ziyu Zhou, Anton Orlichenko, Gang Qu +4
Both functional and structural magnetic resonance imaging (fMRI and sMRI) are widely used for the diagnosis of mental disorder. However, combining complementary information from th…
Exploring General Intelligence via Gated Graph Transformer in Functional Connectivity Studies
Gang Qu, Anton Orlichenko, Junqi Wang +5
Functional connectivity (FC) as derived from fMRI has emerged as a pivotal tool in elucidating the intricacies of various psychiatric disorders and delineating the neural pathways…
Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results
Anton Orlichenko, Gang Qu, Kuan-Jui Su +4
Functional magnetic resonance (fMRI) is an invaluable tool in studying cognitive processes in vivo. Many recent studies use functional connectivity (FC), partial correlation connec…
Angle Basis: a Generative Model and Decomposition for Functional Connectivity
Anton Orlichenko, Gang Qu, Ziyu Zhou +2
Functional connectivity (FC) is one of the most common inputs to fMRI-based predictive models, due to a combination of its simplicity and robustness. However, there may be a lack o…