Dear Jeehye,
z-maps of functional connectivity were used in one-sample t test, two-sample t test or paired t test. This is called Fisher's r-to-z transformation in order to improve the data normality for t tests.
Usually, t maps were created by t tests but not functional connectivity (Pierson's correlation) directly.
You can find the z-map in lots of Resting-State fMRI functional connectivity studies.
Hope this informaiton helpful, best wishes for you!

Dear Jeehye,
Is your connectivity map Pierson's correlation across subjects?
Do you just want to interpret the correlation coefficient r?
If so, please find a program from http://www.restfmri.net/forum/node/81 (the forth), it will help you to convert r value to p value, you will know if your correlation is significant.

I have a question about the multi-seed resting analysis.

First, I analyzed only one seed for two regions, respectively.
Second, I analyzed the two seed that were avalyzed in first, and I merged the two seeds in one ROI file.

The question I wondered is that how the two seeds are working in program?

Hi! Jeehye!
If you merged the two seeds into one ROI file, then the mean time courses was averaged from these two regions. The functional connectivity map was the Pierson's correlation between the mean time course and the time course of all the voxels in the brain.

YAN Chao-Gan

Tue, 06/30/2009 - 00:51

Permalink

## Re

Dear Jeehye,

z-maps of functional connectivity were used in one-sample t test, two-sample t test or paired t test. This is called Fisher's r-to-z transformation in order to improve the data normality for t tests.

Usually, t maps were created by t tests but not functional connectivity (Pierson's correlation) directly.

You can find the z-map in lots of Resting-State fMRI functional connectivity studies.

Hope this informaiton helpful, best wishes for you!

YAN Chao-Gan

Tue, 06/30/2009 - 01:06

Permalink

## Re

Dear Jeehye,

Is your connectivity map Pierson's correlation across subjects?

Do you just want to interpret the correlation coefficient r?

If so, please find a program from http://www.restfmri.net/forum/node/81 (the forth), it will help you to convert r value to p value, you will know if your correlation is significant.

YAN Chao-Gan

Tue, 06/30/2009 - 13:33

Permalink

## Thank, I understand ^^ And

Dear Jeehye,

You need to merge the two seeds in one ROI file.

please try

[Data1, Vox, Head]=rest_readfile('Seed1.img');

Data=(Data1+Data2)>0

rest_WriteNiftiImage(Data,

Then perform FC analysis depend on MergedROI.img.

You also can write programs to convert r to p, by using rest_readfile and rest_WriteNiftiImage.

Jeehye Seo

Thu, 07/09/2009 - 01:57

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## Hi, Chao-Gan

I'm Jeehye

I have a question about the multi-seed resting analysis.

First, I analyzed only one seed for two regions, respectively.

Second, I analyzed the two seed that were avalyzed in first, and I merged the two seeds in one ROI file.

The question I wondered is that how the two seeds are working in program?

Are the two seeds independent? Or dependent?

How is working?

YAN Chao-Gan

Fri, 07/10/2009 - 04:45

Permalink

## Hi! Jeehye! If you merged the

Hi! Jeehye!

If you merged the two seeds into one ROI file, then the mean time courses was averaged from these two regions. The functional connectivity map was the Pierson's correlation between the mean time course and the time course of all the voxels in the brain.