Hi FSL-List,

I have a basic question about mid-level (cross-session) analysis with FEAT. My problem is, that I read different information on the FSL FEAT User Guide,
so I don't know which applies to me.

I have ~20 subjects on whom two fMRI-scans were run within one appointment. (One before intervention, one after intervention, they stayed in the MRI-scanner the hole time.)
They came a second time about a week later when the experiment was repeated with another intervention.

Now I want to compare the two scans for intervention 1 for each participant.

In the FSL FEAT User Guide it sais:

"If you are carrying out a mid-level analysis (e.g., cross-sessions) and will be feeding this into an even higher-level analysis (e.g., cross-subjects), then you should not use the FLAME 1+2 option, as it is not possible for FLAME to know in advance of the highest-level analysis what voxels will ultimately be near threshold. With respect the question of whether to use fixed-effects or mixed-effects for such mid-level analyses, it could be argued that a mixed-effects analysis should be done at the mid-level. A mixed-effects analysis would assume that the sessions are randomly sampled from a "population" of sessions that that subject could produce. This includes estimation of each subject's session-to-session variance. However, it is common for only a small number of sessions to be collected for each subject, making estimation of each subject's session-to-session variance impractical. One solution to this is to assume a common session-to-session variance for all subjects, thereby providing enough data for the session-to-session variance to be estimated. However, this has a downside in that you lose information about which subjects are good (i.e. low variance) and which subjects are bad (i.e. high variance). Hence, when only a small number of sessions has been collected for each subject (say, less than 10), it is recommended that you use a fixed-effects analysis at the mid-level."

However, later on the same page it sais:

"5 subjects each have three sessions. For the reasons described above, we will combine across sessions to create COPEs for the subject means of each subject, using a fixed-effects analysis. In the stats GUI, we select Fixed effects. Then we setup the second-level analysis with 5 EVs, where each EV picks out the 3 sessions that correspond to a particular subject. We also need 5 contrasts to represent the 5 subject means, as follows: "

And they show a pic that shows that all participants are added to one design matrix.

So now I wonder if I should add all my participants to one design matrix for this mid-level analysis or if I should do one individual mid-level analysis for every participant.
I already did both and the results differ.

I would appreciate your recommendations.

Thank you
Pia