I am very sorry that I did not make myself clear. I mean I want to know how trac-all –stat does it.

(1)how to determine the first position and last position of all subjects' pathways when converting all pathstats.byvoxel.txt files to a table for group analyses?

In the tabel , The first position and last position of all subjects' pathways are determined by the longest pathway.

(2)how to complete correspondence of points between subjects?

In the course slides, it said"Correspondence of points between subjects based on Euclidean distance in MNI space".This sentence is so vague that I can't understand it.

(3)what is values in table for group analyses,diffusion measure of center or something else?

I am very sorry that my question is a bit more, but I still hope that you can answer my doubts. Thanks!

Qianwen

------------------ 原始邮件 ------------------

发件人: "Yendiki, Anastasia"<AYENDIKI@mgh.harvard.edu>;

发送时间: 2018年9月12日(星期三) 晚上10:40

收件人: "Freesurfer support list"<freesurfer@nmr.mgh.harvard.edu>;

主题: Re: [Freesurfer] questions about trac-all -stat

Hi Qianwen – You don’t have to do (1) and (2), trac-all –stat does that for you. For a description of the measures, see the tutorial:

http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/TraculaStatistics

and the course slides:

http://surfer.nmr.mgh.harvard.edu/pub/docs/tracula,fs.ppt

Best,

a.y

From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of 薛倩雯 <627611631@qq.com>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Wednesday, September 12, 2018 at 1:13 AM
To: freesurfer <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] questions about trac-all -stat

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Dear experts,

I have some questions about along-path analysis:

(1)how to determine the first position and last position of all subjects' pathway when converting all pathstats.byvoxel.txt files to a table for group analyses?

(2)how to complete correspondence of points between subjects?

(3)what is values in table for group analyses,diffusion measure of center or something else?

Thanks!

Qianwen