生成Reho, degree centrality, fALFF,ALFF先后次序

Submitted by Jie123 on Wed, 07/23/2014 - 06:39

 I will type in English this time and hopefully it is readable...

1) In the preprocessing, rigid-body6 is the default one. Would Friston24 be a better choice?

2) My impression is that Reho and degree centrality can not be derived from smoothed data and therefore they have to be dealt separately. In calculating Reho and degree centrality, should I unselect the smooth, unselect the fALFF+ALFF, but keep Filter selected, before I choose the ReHo, smooth ReHo, and Degree Centrality (see fig attached)?

3) as the next step to calculate fALFF/ALFF, should I make a copy of the FunImgARCW folder, point the 'starting directory name' to the newly copied folder, and choose smooth, fALFF+ALFF, and Filter (see fig attached)?

thanks a lot!
AttachmentSize
Image icon Reho1.jpg225.07 KB
Image icon alff1.jpg212.89 KB

Submitted by ZangYF on Wed, 07/23/2014 - 08:14

1. I guess you mean the head motion. In multiple regression analysis, more regressors will reduce the residual, i.e., account for more. But it is difficult to say better because, in most cases, we do not know the ground truth.
2. Firstly, I am sorry that I am very sure about how to use it. For ReHo, we strongly recommend to smooth before ReHo computation because it dramatically increase the ReHo value. However, we do not know the ground truth, i.e., we do not know if it is really better. For centrality, I guess most papers do centrality calculation after smoothing. One possible reason is the increased neighboring similarity has no such high effect on the total correlation value with all the voxels in the brain.