130 citations
- Johns Hopkins UniversityUS20 papers
- Johns Hopkins MedicineUS8 papers
- Athinoula A. Martinos Center for Biomedical ImagingUS2 papers
- Harvard UniversityUS2 papers
- Indiana UniversityUS2 papers
- Indiana University BloomingtonUS2 papers
- Massachusetts General HospitalUS2 papers
- NeuroDevelopment CenterUS2 papers
- Southwestern Medical CenterUS2 papers
- The University of Texas Southwestern Medical CenterUS2 papers
- University of BaltimoreUS2 papers
- University of British ColumbiaCA2 papers
7 papers · 1 filter
Evaluating phase synchronization methods in fMRI: a comparison study and new approaches
Hamed Honari, Ann S. Choe, Martin A. Lindquist
In recent years there has been growing interest in measuring time-varying functional connectivity between different brain regions using resting-state functional magnetic resonance…
A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas Wymbs +2
We propose a novel optimization framework to predict clinical severity from resting state fMRI (rs-fMRI) data. Our model consists of two coupled terms. The first term decomposes th…
Learned Proximal Networks for Quantitative Susceptibility Mapping
Kuo-Wei Lai, Manisha Aggarwal, Peter van Zijl +2
Quantitative Susceptibility Mapping (QSM) estimates tissue magnetic susceptibility distributions from Magnetic Resonance (MR) phase measurements by solving an ill-posed dipole inve…
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas Wymbs +2
The problem of linking functional connectomics to behavior is extremely challenging due to the complex interactions between the two distinct, but related, data domains. We propose…
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 +4
We propose an integrated deep-generative framework, that jointly models complementary information from resting-state functional MRI (rs-fMRI) connectivity and diffusion tensor imag…
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas Wymbs +2
We propose a unified optimization framework that combines neural networks with dictionary learning to model complex interactions between resting state functional MRI and behavioral…