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2020 – today
- 2023
[j17]Amanda F. Mejia, David Bolin, Yu Ryan Yue, Jiongran Wang, Brian S. Caffo, Mary Beth Nebel:
Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference. J. Comput. Graph. Stat. 32(2): 413-433 (2023)- [j16]Damon D. Pham
, Daniel J. McDonald, Lei Ding, Mary Beth Nebel, Amanda F. Mejia:
Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing. NeuroImage 270: 119972 (2023) - [j15]Andrew Gaddis, Daniel E. Lidstone, Mary Beth Nebel, Roland R. Griffiths, Stewart H. Mostofsky, Amanda F. Mejia, Frederick Streeter Barrett:
Corrigendum to 'Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity': Neuroimage 2022 Oct 15;260:119434. NeuroImage 274: 120130 (2023) - 2022
- [j14]Yuxuan Zhao, David S. Matteson, Stewart H. Mostofsky, Mary Beth Nebel, Benjamin B. Risk:
Group linear non-Gaussian component analysis with applications to neuroimaging. Comput. Stat. Data Anal. 171: 107454 (2022) - [j13]Mary Beth Nebel, Daniel E. Lidstone, Liwei Wang, David C. Benkeser, Stewart H. Mostofsky, Benjamin B. Risk:
Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder? NeuroImage 257: 119296 (2022) - [j12]Andrew Gaddis, Daniel E. Lidstone, Mary Beth Nebel, Roland R. Griffiths, Stewart H. Mostofsky, Amanda F. Mejia, Frederick Streeter Barrett:
Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity. NeuroImage 260: 119434 (2022) - 2021
- [j11]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, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jennings Zhang, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung:
Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. Medical Image Anal. 70: 101972 (2021) - [j10]Benjamin B. Risk, Raphiel J. Murden, Junjie Wu, Mary Beth Nebel, Arun Venkataraman, Zhengwu Zhang, Deqiang Qiu:
Which multiband factor should you choose for your resting-state fMRI study? NeuroImage 234: 117965 (2021) - [j9]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations. NeuroImage 241: 118388 (2021) - [c7]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. MICCAI (7) 2021: 625-636 - [c6]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations. MIDL 2021: 119-130 - [i7]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. CoRR abs/2105.14409 (2021) - 2020
- [j8]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
A joint network optimization framework to predict clinical severity from resting state functional MRI data. NeuroImage 206 (2020) - [c5]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. MICCAI (7) 2020: 437-447 - [i6]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, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung:
Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge. CoRR abs/2006.03611 (2020) - [i5]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. CoRR abs/2007.01929 (2020) - [i4]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. CoRR abs/2007.01930 (2020) - [i3]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. CoRR abs/2007.01931 (2020) - [i2]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart H. Mostofsky, Archana Venkataraman:
Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations. CoRR abs/2008.12410 (2020) - [i1]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data. CoRR abs/2009.03238 (2020)
2010 – 2019
- 2019
- [j7]Dina R. Dajani, Catherine A. Burrows, Mary Beth Nebel, Stewart H. Mostofsky, Kathleen M. Gates, Lucina Q. Uddin:
Parsing Heterogeneity in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder with Individual Connectome Mapping. Brain Connect. 9(9): 673-691 (2019) - [c4]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. IPMI 2019: 605-616 - [c3]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. MICCAI (3) 2019: 709-717 - 2018
- [j6]Amanda F. Mejia, Mary Beth Nebel, Anita D. Barber, Ann S. Choe, James J. Pekar, Brian S. Caffo, Martin A. Lindquist:
Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage. NeuroImage 172: 478-491 (2018) - [c2]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. MICCAI (3) 2018: 163-171 - 2017
- [j5]Ann S. Choe, Mary Beth Nebel, Anita D. Barber, Jessica R. Cohen, Yuting Xu, James J. Pekar, Brian Caffo, Martin A. Lindquist:
Comparing test-retest reliability of dynamic functional connectivity methods. NeuroImage 158: 155-175 (2017) - [c1]Archana Venkataraman, Nicholas F. Wymbs, Mary Beth Nebel, Stewart Mostofsky:
A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. CNI@MICCAI 2017: 60-69 - 2015
- [j4]Amanda F. Mejia, Mary Beth Nebel, Haochang Shou, Ciprian M. Crainiceanu, James J. Pekar, Stewart H. Mostofsky, Brian Caffo, Martin A. Lindquist:
Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators. NeuroImage 112: 14-29 (2015) - 2014
- [j3]John Muschelli, Mary Beth Nebel, Brian S. Caffo, Anita D. Barber, James J. Pekar, Stewart H. Mostofsky:
Reduction of motion-related artifacts in resting state fMRI using aCompCor. NeuroImage 96: 22-35 (2014) - [j2]Martin A. Lindquist, Yuting Xu, Mary Beth Nebel, Brian S. Caffo:
Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach. NeuroImage 101: 531-546 (2014) - [j1]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:
Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI. NeuroImage 102: 938-944 (2014)
Coauthor Index
aka: Stewart Mostofsky
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