Inter-group Heterogeneity of Regional Homogeneity (REHO)

Abstract

Regional Homogeneity (REHO) measures the similarity between the time series of a given voxel and those of its neighbors. First discovered in a task-activation paradigm, REHO was considered as a complementary method to model driven analysis of fMRI time series. With the increased popularity of resting-state paradigms, REHO has become a widely used method for inferring neural activity in the resting state. However, the neural/physiological processes that give rise to REHO are poorly understood. Differences in REHO across groups may not be indicative of differences in neuronal activity. Here, we investigate physiological contributions to REHO across 412 subjects in 9 separate datasets downloaded from OpenNeuro where both physiological signals (respiratory rate, heart rate, and motion) and resting state data are available. Overall, we find an inverse correlation between heart rate and REHO across subjects, an inverse correlation between respiratory rate and REHO across time, and differences in REHO across groups is driven primarily by FWHM of data and motion. We conclude that, due to REHO's highly significant correlation with motion, heart rate, and respiratory rate, REHO should be used with caution to infer differences in neuronal activity across groups.

Applying Unet for extraction of vascular metrics from T1-weighted and T2-weighted MRI

“…The development of diagnostic imaging techniques, such as Magnetic Resonance Angiography (MRA) and Computed Tomography Angiography (CTA), enable to generate volumetric angiographic data whose post-processing provide a 3D reconstruction of vascular networks. Despite the existence of many neuroimaging tools for segmenting and quantifying the gray and white mat-ter of the brain, few publicly available methods exist for noninvasive investigation of cerebral vasculature (Butler et al, 2017(Butler et al, , 2019(Butler et al, , 2020Cote et al, 2021;Forouhandehpour et al, 2021;Jiang et al, 2022).…”