Mary Beth Nebel
Orcid: 0000-0003-0185-3382
According to our database1,
Mary Beth Nebel
authored at least 26 papers
between 2014 and 2023.
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Bibliography
2023
Corrigendum to 'Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity': Neuroimage 2022 Oct 15;260:119434.
NeuroImage, July, 2023
Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing.
NeuroImage, April, 2023
Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference.
J. Comput. Graph. Stat., April, 2023
2022
Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?
NeuroImage, 2022
Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity.
NeuroImage, 2022
Comput. Stat. Data Anal., 2022
2021
NeuroImage, 2021
Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations.
NeuroImage, 2021
Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge.
Medical Image Anal., 2021
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes.
CoRR, 2021
M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
A joint network optimization framework to predict clinical severity from resting state functional MRI data.
NeuroImage, 2020
Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge.
CoRR, 2020
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Parsing Heterogeneity in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder with Individual Connectome Mapping.
Brain Connect., 2019
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces.
Proceedings of the Information Processing in Medical Imaging, 2019
2018
Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage.
NeuroImage, 2018
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
2017
NeuroImage, 2017
A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort.
Proceedings of the Connectomics in NeuroImaging - First International Workshop, 2017
2015
Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators.
NeuroImage, 2015
2014
NeuroImage, 2014
NeuroImage, 2014
Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach.
NeuroImage, 2014