Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach. - Martin A. Lindquist; Yuting Xu; Mary Beth Nebel; Brian S. Caffo (NeuroImage, 2014)

Reduction of motion-related artifacts in resting state fMRI using aCompCor. - John Muschelli; Mary Beth Nebel; Brian S. Caffo; Anita D. Barber; James J. Pekar; Stewart H. Mostofsky (NeuroImage, 2014)

Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI. - Haochang Shou; Ani Eloyan; Mary Beth Nebel; Amanda F. Mejia; James J. Pekar; Stewart H. Mostofsky; Brian S. Caffo; Martin A. Lindquist; Ciprian M. Crainiceanu (NeuroImage, 2014)

Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators. - Amanda F. Mejia; Mary Beth Nebel; Haochang Shou; Ciprian M. Crainiceanu; James J. Pekar; Stewart H. Mostofsky; Brian Caffo; Martin A. Lindquist (NeuroImage, 2015)

A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. - Archana Venkataraman; Nicholas F. Wymbs; Mary Beth Nebel; Stewart Mostofsky (CNI@MICCAI, 2017)

Comparing test-retest reliability of dynamic functional connectivity methods. - Ann S. Choe; Mary Beth Nebel; Anita D. Barber; Jessica R. Cohen; Yuting Xu; James J. Pekar; Brian Caffo; Martin A. Lindquist (NeuroImage, 2017)

A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart Mostofsky; Archana Venkataraman (MICCAI (3), 2018)

Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage. - Amanda F. Mejia; Mary Beth Nebel; Anita D. Barber; Ann S. Choe; James J. Pekar; Brian S. Caffo; Martin A. Lindquist (NeuroImage, 2018)

A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart Mostofsky; Archana Venkataraman (IPMI, 2019)

Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart Mostofsky; Archana Venkataraman (MICCAI (3), 2019)

Parsing Heterogeneity in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder with Individual Connectome Mapping. - Dina R. Dajani; Catherine A. Burrows; Mary Beth Nebel; Stewart H. Mostofsky; Kathleen M. Gates; Lucina Q. Uddin (Brain Connect., 2019)

A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Nicholas F. Wymbs; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (MICCAI (7), 2020)

Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge. - Markus D. Schirmer; Archana Venkataraman; Islem Rekik; Minjeong Kim; Stewart Mostofsky; Mary Beth Nebel; Keri Rosch; Karen Seymour; Deana Crocetti; Hassna Irzan; Michael Hütel; Sébastien Ourselin; et al. (CoRR, 2020)

A joint network optimization framework to predict clinical severity from resting state functional MRI data. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart H. Mostofsky; Archana Venkataraman (NeuroImage, 2020)

A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (MICCAI (7), 2021)

M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (MIDL, 2021)

A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Nicholas F. Wymbs; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (CoRR, 2021)

Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. - Markus D. Schirmer; Archana Venkataraman; Islem Rekik; Minjeong Kim; Stewart H. Mostofsky; Mary Beth Nebel; Keri Rosch; Karen Seymour; Deana Crocetti; Hassna Irzan; Michael Hütel; Sébastien Ourselin; et al. (Medical Image Anal., 2021)

Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Joshua Robinson; Nicholas F. Wymbs; Stewart H. Mostofsky; Archana Venkataraman (NeuroImage, 2021)

Which multiband factor should you choose for your resting-state fMRI study? - Benjamin B. Risk; Raphiel J. Murden; Junjie Wu; Mary Beth Nebel; Arun Venkataraman; Zhengwu Zhang; Deqiang Qiu (NeuroImage, 2021)

Group linear non-Gaussian component analysis with applications to neuroimaging. - Yuxuan Zhao; David S. Matteson; Stewart H. Mostofsky; Mary Beth Nebel; Benjamin B. Risk (Comput. Stat. Data Anal., 2022)

Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity. - Andrew Gaddis; Daniel E. Lidstone; Mary Beth Nebel; Roland R. Griffiths; Stewart H. Mostofsky; Amanda F. Mejia; Frederick Streeter Barrett (NeuroImage, 2022)

Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder? - Mary Beth Nebel; Daniel E. Lidstone; Liwei Wang; David C. Benkeser; Stewart H. Mostofsky; Benjamin B. Risk (NeuroImage, 2022)

Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference. - Amanda F. Mejia; David Bolin; Yu Ryan Yue; Jiongran Wang; Brian S. Caffo; Mary Beth Nebel (J. Comput. Graph. Stat., 2023)

Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing. - Damon D. Pham; Daniel J. McDonald; Lei Ding; Mary Beth Nebel; Amanda F. Mejia (NeuroImage, 2023)

Corrigendum to 'Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity': Neuroimage 2022 Oct 15;260:119434. - Andrew Gaddis; Daniel E. Lidstone; Mary Beth Nebel; Roland R. Griffiths; Stewart H. Mostofsky; Amanda F. Mejia; Frederick Streeter Barrett (NeuroImage, 2023)