Robert L Barry

This paper evaluates a PCA-based denoising method for spinal cord fMRI using a noise ROI, finding that it may not consistently improve group-level activation maps compared to physiological recording-derived regressors.

This paper demonstrates that functional connectivity patterns in the human cervical spinal cord exhibit individual-specific properties, suggesting the existence of a spinal cord 'fingerprint' similar to brain fingerprints.

This study benchmarks four cervical spinal cord RF coils at 7 T MRI across multiple centers, identifying performance differences and proposing a standardized evaluation protocol.

The paper introduces EPISeg, a deep learning model for automated spinal cord segmentation on gradient-echo EPI data, showing improved performance over existing methods.

This study shows body size parameters significantly correlate with brain and spinal cord MRI metrics and should be included in neuroimaging studies.

Neptune is a MATLAB-based toolbox for spinal cord fMRI data processing and quality assurance, offering a 19-step preprocessing pipeline and 4-step post-processing pipeline with enhanced quality control features.

This study compares hemodynamic response functions from resting-state fMRI and invasive electrophysiological recordings in rats, finding similar HRF parameters between ground truth and estimated values.

This study investigates how scan length affects motor cortex activation during upper limb movements in fMRI, finding diminishing returns with more runs and proposing variable run assignments for different movements.

This study uses 7T fMRI to identify disrupted functional connectivity in ALS patients, particularly in cerebellar lobule VI, suggesting its involvement in ALS pathology.