The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets. - Anees Abrol; Charlotte Chaze; Eswar Damaraju; Vince D. Calhoun (EMBC, 2016)

Replicability of time-varying connectivity patterns in large resting state fMRI samples. - Anees Abrol; Eswar Damaraju; Robyn L. Miller; Julia M. Stephen; Eric D. Claus; Andrew R. Mayer; Vince D. Calhoun (NeuroImage, 2017)

Prediction of Progression to Alzheimer's disease with Deep InfoMax. - Alex Fedorov; R. Devon Hjelm; Anees Abrol; Zening Fu; Yuhui Du; Sergey M. Plis; Vince D. Calhoun (BHI, 2019)

Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression. - Anees Abrol; Zening Fu; Yuhui Du; Vince D. Calhoun (EMBC, 2019)

Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data. - Anees Abrol; Hooman Rokham; Vince D. Calhoun (EMBC, 2019)

Selection of Efficient Clustering Index to Estimate the Number of Dynamic Brain States from Functional Network Connectivity. - Victor M. Vergara; Anees Abrol; Flor A. Espinoza; Vince D. Calhoun (EMBC, 2019)

Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data. - Debbrata K. Saha; Anees Abrol; Eswar Damaraju; Barnaly Rashid; Sergey M. Plis; Vince D. Calhoun (ISBI, 2019)

Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. - Bradley T. Baker; Anees Abrol; Rogers F. Silva; Eswar Damaraju; Anand D. Sarwate; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2019)

Varying Information Complexity in Functional Domain Interactions in Schizophrenia. - Ishaan Batta; Anees Abrol; Zening Fu; Vince D. Calhoun (BIBE, 2020)

Fully automated ordering and labeling of ICA components. - Mustafa S. Salman; Tor D. Wager; Eswar Damaraju; Anees Abrol; Vince D. Calhoun (BIBM, 2020)

Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels. - Armin Iraji; Noah Lewis; Ashkan Faghiri; Zening Fu; Thomas DeRamus; Anees Abrol; Shile Qi; Vince D. Calhoun (ISBI, 2020)

Deep learning in resting-state fMRI*. - Anees Abrol; Reihaneh Hassanzadeh; Sergey M. Plis; Vince D. Calhoun (EMBC, 2021)

Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (EMBC, 2021)

A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia. - Ishaan Batta; Anees Abrol; Zening Fu; Vince D. Calhoun (ISBI, 2021)

A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States. - Debbrata K. Saha; Eswar Damaraju; Barnaly Rashid; Anees Abrol; Sergey M. Plis; Vince D. Calhoun (Brain Connect., 2021)

Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity. - Reihaneh Hassanzadeh; Anees Abrol; Vince D. Calhoun (BHI, 2022)

A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction. - Giorgio Dolci; Md Abdur Rahaman; Jiayu Chen 003; Kuaikuai Duan; Zening Fu; Anees Abrol; Gloria Menegaz; Vince D. Calhoun (BIBE, 2022)

Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI Datasets. - Anees Abrol; Vince D. Calhoun (EMBC, 2022)

Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learning. - Anees Abrol; Ihab Hajjar; Vince D. Calhoun (EMBC, 2022)

Learning Active Multimodal Subspaces in the Brain. - Ishaan Batta; Anees Abrol; Zening Fu; Vince D. Calhoun (EMBC, 2022)

Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study. - Yuda Bi; Anees Abrol; Zening Fu; Vince D. Calhoun (EMBC, 2022)

An Approach to Automatically Label and Order Brain Activity/Component Maps. - Mustafa S. Salman; Tor D. Wager; Eswar Damaraju; Anees Abrol; Victor M. Vergara; Zening Fu; Vince D. Calhoun (Brain Connect., 2022)

Pipeline-Invariant Representation Learning for Neuroimaging. - Xinhui Li; Alex Fedorov; Mrinal Mathur; Anees Abrol; Gregory Kiar; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study. - Ishaan Batta; Anees Abrol; Zening Fu; Adrian Preda; Theo G. M. van Erp; Vince D. Calhoun (Neuroinformatics, 2022)

Deep Learning in Neuroimaging: Promises and challenges. - Weizheng Yan; Gang Qu 002; Wenxing Hu; Anees Abrol; Biao Cai; Chen Qiao; Sergey M. Plis; Yu-Ping Wang 002; Jing Sui; Vince D. Calhoun (IEEE Signal Process. Mag., 2022)

Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data. - Giorgio Dolci; Md Abdur Rahaman; Ilaria Boscolo Galazzo; Federica Cruciani; Anees Abrol; Jiayu Chen 003; Zening Fu; Kuaikuai Duan; Gloria Menegaz; Vince D. Calhoun (ICASSP Workshops, 2023)

A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (ISBI, 2023)

MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data. - Yuda Bi; Anees Abrol; Zening Fu; Vince D. Calhoun (ISBI, 2023)

Constrained Source-based Salience: Network-based Visualization of Deep Learning Neuroimaging Models. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (BHI, 2024)

A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (CISS, 2024)

A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals. - Yuxiang Wei 008; Anees Abrol; James J. Lah; Deqiang Qiu; Vince D. Calhoun (EMBC, 2024)

Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers. - Reihaneh Hassanzadeh; Anees Abrol; Hamid Reza Hassanzadeh; Vince D. Calhoun (EMBC, 2024)

Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. - Yuda Bi; Anees Abrol; Jing Sui; Vince D. Calhoun (ICASSP, 2024)

Voxelwise Intensity Projection for the Spatial Representation of Resting State Functional MRI Networks and Multimodal Deep Learning. - Vaibhavi S. Itkyal; Anees Abrol; Theodore J. LaGrow; Vince D. Calhoun (ISBI, 2024)

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease. - Giorgio Dolci; Federica Cruciani; Md Abdur Rahaman; Anees Abrol; Jiayu Chen 003; Zening Fu; Ilaria Boscolo Galazzo; Gloria Menegaz; Vince D. Calhoun (CoRR, 2024)

Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum. - Giorgio Dolci; Charles A. Ellis; Federica Cruciani; Lorenza Brusini; Anees Abrol; Ilaria Boscolo Galazzo; Gloria Menegaz; Vince D. Calhoun (CoRR, 2024)

Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis. - Yuxiang Wei 008; Anees Abrol; Reihaneh Hassanzadeh; Vince D. Calhoun (CoRR, 2024)

Editorial: Computational modeling and machine learning methods in neurodevelopment and neurodegeneration: from basic research to clinical applications. - Noemi Montobbio; Roberto Maffulli; Anees Abrol; Pablo Martínez-Cañada (Frontiers Comput. Neurosci., 2024)

Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. - Yuda Bi; Anees Abrol; Sihan Jia; Jing Sui; Vince D. Calhoun (NeuroImage, 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)

Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment. - Sahithi Kolla; Haleh Falakshahi; Anees Abrol; Zening Fu; Vince D. Calhoun (Sensors, 2024)

Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis. - Yuxiang Wei 004; Anees Abrol; Vince D. Calhoun (RECOMB, 2025)

MultiViT2: A Data-augmented Multimodal Neuroimaging Prediction Framework via Latent Diffusion Model. - Yuda Bi; Sihan Jia; Yutong Gao 002; Anees Abrol; Zening Fu; Vince D. Calhoun (CoRR, 2025)