5 papers
FM-fMRI: Event Conditioned Flow Matching for Rest-to-Task fMRI Time-Series Synthesis
Peiyu Duan, Jiyao Wang, Nicha C. Dvornek +4
Task-based fMRI provides a direct readout of task-evoked neural dynamics, but it is expensive and difficult to acquire at scale, motivating rest-to-task synthesis from widely avail…
Learning Robust and Task-Invariant Functional Representation from fMRI through Siamese Self-Supervised Learning
Jiyao Wang, Peiyu Duan, Nicha C. Dvornek +4
Functional magnetic resonance imaging (fMRI) is a powerful tool for investigating human brain function. However, the high cost of data acquisition and the inherent subjectivity of…
STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FC
Jiyao Wang, Nicha C. Dvornek, Peiyu Duan +3
In recent years, graph neural networks (GNNs) have been widely applied in the analysis of brain fMRI, yet defining the connectivity between ROIs remains a challenge in noisy fMRI d…
Causal Modeling of fMRI Time-series for Interpretable Autism Spectrum Disorder Classification
Peiyu Duan, Nicha C. Dvornek, Jiyao Wang +2
Autism spectrum disorder (ASD) is a neurological and developmental disorder that affects social and communicative behaviors. It emerges in early life and is generally associated wi…
Towards Zero-Shot Task-Generalizable Learning on fMRI
Jiyao Wang, Nicha C. Dvornek, Peiyu Duan +2
Functional MRI measuring BOLD signal is an increasingly important imaging modality in studying brain functions and neurological disorders. It can be acquired in either a resting-st…