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

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.

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
>>
>>
>>
>>
>>