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02/28/2022
Fast Bayesian estimation of brain activation with cortical surface and subcortical fMRI data using EM
Analysis of brain imaging scans is critical to understanding the way the...
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07/31/2021
Projection scrubbing: a more effective, data-driven fMRI denoising method
Functional MRI (fMRI) data are subject to artifacts from a myriad of sou...
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05/30/2021
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes
We propose a novel matrix autoencoder to map functional connectomes from...
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01/13/2021
Group Linear non-Gaussian Component Analysis with Applications to Neuroimaging
Independent component analysis (ICA) is an unsupervised learning method ...
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08/27/2020
Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characteri
We propose a novel integrated framework that jointly models complementar...
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08/27/2020
A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data
We propose a novel optimization framework to predict clinical severity f...
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07/03/2020
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism
We propose an integrated deep-generative framework, that jointly models ...
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07/03/2020
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data
We propose a unified optimization framework that combines neural network...
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07/03/2020
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces
The problem of linking functional connectomics to behavior is extremely ...
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05/27/2020
A spatial template independent component analysis model for subject-level brain network estimation and inference
ICA is commonly applied to fMRI data to extract independent components (...
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06/17/2019
