5 papers
Bayesian brain mapping: a population-informed framework for personalized functional network topography and connectivity
Nohelia Da Silva Sanchez, Diego Derman, Damon D. Pham +3
The spatial topography of functional brain organization is increasingly recognized to play an important role in cognition and disease. Accounting for individual differences in func…
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…
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 +4
We propose a novel integrated framework that jointly models complementary information from resting-state functional MRI (rs-fMRI) connectivity and diffusion tensor imaging (DTI) tr…
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…