29 citations · 40 across the 28 of their papers we have counts for
9 papers · 1 filter
Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis
Yuxiang Wei, Anees Abrol, Vince Calhoun
Recent advances in deep learning structured state space models, especially the Mamba architecture, have demonstrated remarkable performance improvements while maintaining linear co…
A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals
Yuxiang Wei, Anees Abrol, James Lah +2
Alzheimer's disease (AD) progresses from asymptomatic changes to clinical symptoms, emphasizing the importance of early detection for proper treatment. Functional magnetic resonanc…
Multi-modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification
Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun +1
Schizophrenia (SZ) is a severe brain disorder marked by diverse cognitive impairments, abnormalities in brain structure, function, and genetic factors. Its complex symptoms and ove…
Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging
Bradley T. Baker, Vince D. Calhoun, Sergey M. Plis
Neural networks, whice have had a profound effect on how researchers study complex phenomena, do so through a complex, nonlinear mathematical structure which can be difficult for h…
Multimodal MRI Accurately Identifies Amyloid Status in Unbalanced Cohorts in Alzheimer's Disease Continuum
Giorgio Dolci, Charles A. Ellis, Federica Cruciani +5
Amyloid- (A) plaques in conjunction with hyperphosphorylated tau proteins in the form of neurofibrillary tangles are the two neuropathological hallmarks of Alzheimer's diseas…
An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease
Giorgio Dolci, Federica Cruciani, Md Abdur Rahaman +6
\textbf{Objective:} Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as Mild Cognitive Impairment (MCI), where patien…
A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds
Anton Orlichenko, Gang Qu, Ziyu Zhou +7
Objective: fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinic…
Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers
Reihaneh Hassanzadeh, Anees Abrol, Hamid Reza Hassanzadeh +1
Generative approaches for cross-modality transformation have recently gained significant attention in neuroimaging. While most previous work has focused on case-control data, the a…
Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization
M. Moein Esfahani, Hossein Sadati, Vince D Calhoun
Brain-computer interface systems and the recording of brain activity has garnered significant attention across a diverse spectrum of applications. EEG signals have emerged as a mod…