NBS for two 'mean' graphs

Good Afternoon,

I have a quick question regarding the use of the NBS statistics toolbox within Graphvar. If I have two groups and from each have calculated a mean network for each group, can I use the NBS package to compare the two mean graphs. I worry that this wouldnt be statistically valid in the sense that the sample would effectively be two. 

Instead would I need to run a test like the hamming distance to compare two individual mean networks? If so is this within the scope of the Graphvar program?

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error when performing mixed effect analysis

Hi Yan,

An error occured when I am performing mixed effect analysis using DPABI.  There are 2 groups of subjects (19 control and 19 patient) in my data and each group underwent 2 fMRI scan in 2 different times.  I chose grey matter density as covariate images and FD as txt covariates. Should I perform ANCOVA (repeat) or mixed effect analysis to see the difference between the two groups and within two patient conditions? How do I perform post-hoc analysis after mixed effect analysis since there is no post hoc analysis to cho0se in mixed effect analysis? 

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Wiley 的版权协议在哪里签署

各位老师:

          最近投了一篇 文章到Wiley 旗下的杂志,已经接受了,给我发proof的邮件里面说 “please log in into Author Services (https://authorservices.wiley.com) and click on "My Dashboard." When you locate your article on the Dashboard, please click the button that says "Sign License" to use the Wiley Author Licensing Service (WALS) to complete your license agreement。”

How to calculate the global correlation between two contrasts

Dear Chao-Gan,

Recently I have done a study which includes two datasets (30 patients and 30 controls, and 20 patients and 21 controls, respectively), and the second is the subset of the first. The reviewer required me to report the globle correlation between these two contrasts. However, I have never done such analysis before. Can I use dpabi or any other software to achieve it?

Best,

Vincent 

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Checking the quality of coregistration

Hi,

I was wondering if it is possible with DPABI to check the quality of the coregistration somehow? I could only find pictures for checking the quality of the Normalization.

greetings

David

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Values of sm* ReOh maps

Dear experts,

I computed ReOh maps for some patients and controls in DPARSFA (running the participants all together, hence with the same processing settings) and got maps where the values are not between [0 1], is this correct? I expect having values between 0 and 1 due to the computation of KCC. I obtain values between 0 and 1.6/1.8.

Please advice if correct,

Thank you,

Kind regards,

Bianca De Blasi

Covariable file

Dear experts.

I am looking for csf and white matter signal covariates and find the attached file in ...globalCovs folder.

However, the file contained 30 columns and perhaps the last three columns would be meaningful to me.

Please let me know which comumn represents csf, white matter, and global signal.

Best regards,

tetsuya

 

Forums:

Which mask to use for smoothness estimation (FWHMx,y,z)?

Dear Chaogan,

My study is to use voxel-based rs-FC measure to perform statistical analysis. That rs-FC measure was generated within a GM mask, so that FC was calculated between any two voxels within the GM.

After statistical analysis,  however, I consider that the whole brain mask, instead of the GM mask, should be used for smoothness estimation (FWHMx,y,z) with 4D residuals.

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Gissian random field (GRF) in DPABI for multiple correction

Dear experts,

I used Gissian random field (GRF) in DPABI  for multiple correction when comparing rs FC maps differences between patient groups.

Forums:

Gissian random field for multiple correction

Dear experts,

I used Gissian random field (GRF) in DPABI  for multiple correction when comparing rs FC maps differences between patient groups.

However, a reviewer suggested "this method (GRF) is based upon the hypothesis that the spatial smoothness of BOLD signal in the whole brain is consistent and the distribution of the spatial autocorrelation function in accordance with specific curve. Practically, the BOLD data is hardly accord with the hypothesis".

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