严老师：

您好！最近有一篇文章返回来大修，审稿人对于fALFF提出了一个问题，由于自己可能对这个问题理解的不太深入，不知道怎么回答比较好，所以需要您的帮助。

问题如下：

What is the point of band pass filtering to reduce drift and cardiac/respiratory noise AFTER you've calculated fALFF? Shouldn't dealing with drift and physiologic noise be done prior to calculating fALFF?

Dear Chao-Gan,

I have read some ALFF papers, and found that only ALFF with positive  value was shown in the statistical map of one-sample t-test. Does ALFF with negative value make no sense? If so, should I use the mask containing voxels with positive value while analyzing data?

Thank you in advance.

Best,

Vincent

Dear all, 

I was considering about the possibility of perform a REHO analysis inside different masks (RSN masks, like DMN) 

For example, in the step default mask/No mask/ user mask.  introduce the DMN mask and then run a REHO analysis. Will I obtain the activation inside this mask only?

It has sense? or I'm double dipping the data! 
 

Thank you so much!

Dear Chao-Gan,

Dear Dr.Yan,

I am sorry to bother you again. Last time after I used your advice for TR,  and starts from FunImgCore, it ran again, however it went wrong again. The report error is as follows, I think when move to nuisance covariates regression, especially for white matter and CSF, the original mask in DPARSFA is different from my data, so how can I solve the problem?

  Dear Dr. Yan,

Recently I used DPARSFA to process the resting data. It went wrong when I moved to New Segment+Dartel, after I went through realign, reorient fun, crop t1, reorient t1, t1 coreg to fun. You can see the report of error as below, I want to know what's the problem. Furthermore, how can I solve the problem of time points if I calculate other steps such as FunImgR or T1ImgCoreg instead of FunImg, because DPARSFA always report the time points do not meet the requirement of nii. data.

I am looking forwad to your replies.

Best

Fish

Hello everyone,

I have seen several published articles that used diffusion tensor imaging (DTI) data and the Brain Connectivity Toolbox to study graph theory (so no fMRI data whatsoever). Does Graphvar allow for studying graph theory using DTI data only or it necessarily requires some resting-state timeseries? It seems to me, according to the user guides and the recently published article by Kruschwitz et al (2015), that it sounds possible if some matrix were to be created first. It's only that most of the tutorials are explained through resting-state example, so I'm not sure.