Normalization for ReHo analysis

Hi all,

About the spatial normalization for ReHo analysis, I wonder which one is better, T1 image unified segmentation or EPI template, for the spatial normalization of ReHo? Cause my findings show significant differences between T1 and EPI template. Since the ReHo-KCC algorithm computes the neighborhood voxels, it is intuitively that simple spatial transformation should not have resulted in distinct patterns.

In the same vein, what template (EPI-MNI vs T1-MNI) should be the most optimal one for seed-based and graph-based functional connectivity analyses? Thank you~~

Best,

Cherry

Forums:

Disputes exist on this topic.

Usually we use DARTEL.