Obada Al Zoubi

This study uses Bayesian and frequentist methods to analyze resting-state fMRI data from females with GAD, finding reduced functional connectivity in specific brain regions.

This study investigates neural responses to gastrointestinal sensations using a vibrating capsule, showing improved perceptual accuracy and correlated neural activity.

This paper predicts sex from resting-state fMRI using machine learning across multiple datasets, achieving high accuracy with low-frequency BOLD signal features.

This study examines the relationship between EEG microstate dynamics and fMRI signals, finding that activity regressors are mostly anticorrelated with fMRI in specific brain networks.

The paper identifies a functional connectivity locus associated with rumination symptoms and optimizes a neurofeedback signal for real-time fMRI intervention.