Hi Donald and all,

thank you, I understand better now and think I got something wrong in my preprocessing.

I'll describe my preprocessing steps in more detail, since I'm a still a little bit confused right now :):

My data consists of 34 testsubjects, each with 3 sessions (34 x 3).

1. I slice-timed the three sessions per subject so I got slice-timed files for every session per subject (3 x 34)

2. I used those files to do my realignment and got realigned files for every session per subject (3 x 34) and one mean image for all session of a subject (34 mean images, one per subject). In the spm manual it writes that the sessions are first realigned to each other, by aligning the first
scan from each session to the first scan of the first session and then the images within each session are aligned to the first image of the session.

3. Then I used this mean image to coregister with the structural scan

4. I used the coregistered image for segmentation

5. Then I used Dartel to warp grey and white matter images and after that created the normalized smoothed images

In the end I got 34 normalized, smoothed images to use for the GLM.

I think you meant that I need to have 34 x 3 normalized smoothed images (34 scans for each session of a subject) to include in the first level model, right?

This makes sense, since I want to include the movement parameters for every session and also am confused about how to define my conditions and onsets for each session when I have only 34 scans per subject, but condition onsets for three sessions.

I hope this is more clear.

greetings

David

2014-07-14 9:11 GMT+02:00 MCLAREN, Donald <[log in to unmask]>:

See below.

On Sun, Jul 13, 2014 at 12:42 PM, David Hofmann <[log in to unmask]> wrote:

Hi Donald,

thanks for the answer and sorry for the late reply. In deed between-session effects are not of interest.

I'm not sure if I understood you correctly: Do I need to pre-process every session for every subject seperately?

Slice-timing is performed separately for each session.

Motion correction should be performed across all sessions to make sure all the images are aligned.

 

In other words, do I need to have three different mean functional images (one per session) for every subject for the first level model? 

The first level model does not use mean functional images. You want to use the smoothed warped images. In the first level model for each subject, you will setup 3 sessions. Each session will include the ALL the smoothed/warped images for that session (note: its common not to use the first few images of the scan to allow for magnetization equilibrium to be reached - the images are removed before pre-processing). At the level of generating the contrasts, you will form a contrast across the three sessions. Thus, you will get one con_ image per subject for each contrast you are interested in investigating.

If your contrast weights in each run are divided by 3, then the contrast will be the average of the contrast across sessions. Otherwise it will be the sum of the contrasts. As long as all subjects have all sessions, both methods will give you the identical second-level results. If subjects are missing sessions, then the results will differ and you will want to make sure your contrast represents the average across sessions.

 

Because up to now I created one mean image over all sessions per subject by using three session tabs per subject in the slice-timing and realignment. 

I'm not sure how you got to "one" mean image per over all sessions, I think my above answer will help clarify any issues.

 

greetings

David

2014-07-03 15:21 GMT+02:00 MCLAREN, Donald <[log in to unmask]>:

Put all 3 sessions into your first level model, create a single contrast across the three sessions, and then use this contrast in the 2nd-level model. This assumes that you don't care about any session effects or that you plan to ignore the session effect. This may or may not be good depending on your question and study design.

Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Thu, Jul 3, 2014 at 9:17 AM, David Hofmann <[log in to unmask]> wrote:

Hi @all,

I have some fMRI data consisting of 30 testsubject where each subject has been tested three times. So there are multiple sessions.

Now I don't know how to combine/merge those three session per subject in order to do my 2nd-level analysis. Can someone give me some tips how to proceed in such a case?

greetings

David