Back

Inter-group Heterogeneity of Regional Homogeneity (REHO)

Jiang, Y.; Mhamdi, M. A. A.; Butler, R.

2022-09-01 bioinformatics
10.1101/2022.08.29.505722 bioRxiv
Show 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 REHOs highly significant correlation with motion, heart rate, and respiratory rate, REHO should be used with caution to infer differences in neuronal activity across groups.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.