Hi Yolanda,
 
the new files contain some minor bug fixes and mainly some extensions, e.g. additional parameters to compute percent changes with respect to the first time point as estimated from the linear fit. Although I think the old version will work fine, it may be easier to use the newer version to prevent you from running into a problem that I already fixed.

So simply grab the files from here:
http://www.nmr.mgh.harvard.edu/~mreuter/long/

backup your old ones and replace them with these.
 
Now, you need to pass the subjects directory explicitly (--sd flag), the flags for naming the within subject outputs has change, (--name-pc1 instead of out-pc1, because it can also be an input, when one wants to stack only the results without recomputing them). There is an option in connection with --qcache to stack the final results into a single file on the target geometry (e.g. fsaverage). This is helpful for people who want to run glmfit directly on the results.

Best, Martin

----- Original Message -----
From: Yolanda Vives
To: Martin Reuter
Cc: freesurfer
Sent: Wednesday, July 04, 2012 4:20 AM
Subject: Re: [Freesurfer] Extraction Longitudinal Stats

Hi Martin,
 
Thank you for your answer. I am also interested in testing your new scripts, if it is possible.
 
Regards,
Yolanda

2012/7/3 Martin Reuter <mreuter@nmr.mgh.harvard.edu>
Hi Yolanda,

take a look at the longitudinal tutorial:
http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial

There is a section that hints at the post-processing as far as we have
implemented it. Based on a longitudinal qdec table you can run
long_mris_slopes to create rate or percent change maps for each subject
and then run qdec on these for the cross sectional comparison.

Also I can make available a newer version of that script as lots of
small things have changed since last year, let me know.

Best, Martin


On Tue, 2012-07-03 at 15:58 +0200, Yolanda Vives wrote:
> Hi Martin,
>
> I would like to compare also a Control vs. an Experimental group
> (pre-post), but instead of using ROIs, I am interested in a
> whole-brain paired t-test analysis between the two groups. Which data
> should I take? Would it be possible to process ?.long.base with qcache
> and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could
> I use QDEC with ?.long.base after qcache?
>
> Thank you,
> Yolanda
>
> 2012/4/12 Martin Reuter <mreuter@nmr.mgh.harvard.edu>
>         Yes, just extract the stats on each time point as done in a
>         cross
>         sectional analysis (but instead on the ?.long.base
>         directories) do a
>         paired t (or a t on the difference) to see if there is
>         increase or
>         decrease.
>
>         If you look at one of the reported ROI's (e.g. caudate volume,
>         or
>         pre-central thickness) you can directly get the values from
>         the stats
>         files. If you have your own ROI's you need to use segstats to
>         get the
>         stats for them.
>
>         Cheers, Martin
>
>         On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote:
>         > Hi everybody,
>         > I have a question about FS longitudinal post-processing.
>         Currently I
>         > obtained some corrected results comparing a Control vs. an
>         > Experimental group (pre-post).
>         > What i would like to know is if there's a thinning in the
>         control
>         > group or a increase in the thickness of the experimental
>         group.
>         > I tought in create a label and extract the individual values
>         of both
>         > timepoints and then do a t test in order to see if the mean
>         differs to
>         > 0.
>         > How I can do that?; There is an easier way to do it?
>         > Thanks in advance
>         >
>         > --
>         > Dídac Vidal Piñeiro
>         >
>         > Dept. Psychiatry and Clinical Psychobiology
>         > Faculty of Medicine
>         > University of barcelona
>         >
>         >
>
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