A constrained coefficient ica algorithm for group difference enhancement. - Jing Sui; Jingyu Liu 001; Lei Wu 013; Andrew Michael; Lai Xu 002; Tülay Adali; Vince D. Calhoun (ICASSP, 2008)

Reactivity of hemodynamic responses and functional connectivity to different states of alpha synchrony: A concurrent EEG-fMRI study. - Lei Wu 013; Tom Eichele; Vince D. Calhoun (NeuroImage, 2010)

Parallel independent component analysis using an optimized neurovascular coupling for concurrent EEG-fMRI sources. - Lei Wu 013; Tom Eichele; Vince D. Calhoun (EMBC, 2011)

MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics. - William R. Gray Roncal; Zachary H. Koterba; Disa Mhembere; Dean M. Kleissas; Joshua T. Vogelstein; Randal C. Burns; Anita R. Bowles; Dimitrios K. Donavos; Sephira Ryman; Rex E. Jung; Lei Wu 013; Vince D. Calhoun; et al. (GlobalSIP, 2013)

The spatiospectral characterization of brain networks: Fusing concurrent EEG spectra and fMRI maps. - David A. Bridwell; Lei Wu 013; Tom Eichele; Vince D. Calhoun (NeuroImage, 2013)

Gradient artifact removal in concurrently acquired EEG data using independent vector analysis. - Partha Pratim Acharjee; Ronald Phlypo; Lei Wu 013; Vince D. Calhoun; Tülay Adali (ICASSP, 2014)

Dynamic default mode network connectivity diminished in patients with schizophrenia. - Yuhui Du; Hao He 002; Lei Wu 013; Qingbao Yu; Jing Sui; Vince D. Calhoun (ISBI, 2015)

Identifying brain dynamic network states via GIG-ICA: Application to schizophrenia, bipolar and schizoaffective disorders. - Yuhui Du; Godfrey D. Pearlson; Hao He 002; Lei Wu 013; Jiayu Chen 003; Vince D. Calhoun (ISBI, 2015)

Independent Vector Analysis for Gradient Artifact Removal in Concurrent EEG-fMRI Data. - Partha Pratim Acharjee; Ronald Phlypo; Lei Wu 013; Vince D. Calhoun; Tülay Adali (IEEE Trans. Biomed. Eng., 2015)

An approach to directly link ICA and seed-based functional connectivity: Application to schizophrenia. - Lei Wu 013; Arvind Caprihan; Juan R. Bustillo; Andy R. Mayer; Vince D. Calhoun (NeuroImage, 2018)

On self-supervised multi-modal representation learning: An application to Alzheimer's disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (CoRR, 2020)

Taxonomy of multimodal self-supervised representation learning. - Alex Fedorov; Tristan Sylvain; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (CoRR, 2020)

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. - Alex Fedorov; Tristan Sylvain; Eloy Geenjaar; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (ICHI, 2021)

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (ISBI, 2021)

Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Thomas P. DeRamus; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

Tracking spatial dynamics of functional connectivity during a task. - Lei Wu 013; Arvind Caprihan; Vince D. Calhoun (NeuroImage, 2021)

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

Joint Structural and Functional Connectivity Learning Based Independent Component Analysis. - Mahshid Fouladivanda; Armin Iraji; Lei Wu 013; Vince D. Calhoun (MLSP, 2023)

Coupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks. - Souvik Phadikar; Krishna Pusuluri; Kyle M. Jensen; Lei Wu 013; Armin Iraji; Vince D. Calhoun (ISBI, 2024)

Physics-Guided Multi-view Graph Neural Network for Schizophrenia Classification via Structural-Functional Coupling. - Badhan Mazumder; Ayush Kanyal; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (PRIME@MICCAI, 2024)

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. - Zening Fu; Ishaan Batta; Lei Wu 013; Anees Abrol; Oktay Agcaoglu; Mustafa S. Salman; Yuhui Du; Armin Iraji; Sarah Shultz; Jing Sui; Vince D. Calhoun (NeuroImage, 2024)

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; Girish Mittapalle; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (NeuroImage, 2024)

Genetics Encoded Joint Embedding of Multimodal Connectomes with Explainable Graph Neural Network for Schizophrenia Classification. - Badhan Mazumder; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (ISBI, 2025)

Dynamic Fusion: Merging Structural and Functional Connectivity Dynamics Via Joint CMICA. - Lei Wu 013; Marlena Duda; Armin Iraji; Vince D. Calhoun (ISBI, 2025)

Unified Cross-Modal Attention-Mixer Based Structural-Functional Connectomics Fusion for Neuropsychiatric Disorder Diagnosis. - Badhan Mazumder; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (CoRR, 2025)