Hello,
I am attempting to run an analysis for 10 subjects with four runs per subject. Each single subject has 30 COPEs. I have tried to follow the instructions listed on the FSL webpage: http://www.fmrib.ox.ac.uk/fsl/feat5/detail.html#MultiSessionMultiSubject listed under the section entitled Multi-Session & Multi-Subject (Repeated Measures - Three Level Analysis).
Following the instructions to the best of my ability, I did the following:
1) Ran a lower-level FEAT for each run for each subject.
2) Constructed a higher-level FEAT where the inputs were lower-level FEATs for each run for each subject (i.e. 40 FEATs corresponding to 40 runs). In the stats tab, I selected the Fixed Effects option and set up the design with 40 EVs, where each EV picks out the 4 sessions that correspond to a particular subject. I also included 10 contrasts to represent the 10 subject means.
Rather than output something like subject_N.gfeat/cope1.feat, this second level analysis output 30 cope.feat directories, each with 10 cope.nii.gz files in its stats directory. The file structure was as follows: Group_Ana/cope[n].feat/stats/cope[j], where n = 1:30 lower level contrasts and j = 1:10 subjects. This is different from what the instructions implied would be output.
From an earlier post by Lara on 16 Mar 2011, it was advised to:
1. Analyze each session separately for each subject (including registration).
2. Use a higher-level analysis to combine a subject’s sessions using the fixed-effects stats option, selecting GROUP MEAN model (single EV, with all 1’s in that EV and a single contrast with a single “1” in it), making sure that inputs are lower level FEAT’s.
3. Once I have #1 and #2 completed for each subject, I then run a separate higher-level analysis to look at effects at the group level. For this, I select the option “Inputs are 3D cope images” in the “Data” tab. For the input, I select the [subject].gfeat/cope[n].feat/stats/cope1 image. The rest of the higher-level settings I leave as normal...
If I were to adopt this second approach, I think it would mean selecting 300 inputs (30 3D cope images x 10 subjects), which would be very time-consuming. Is there a simpler way to do this?
Any help regarding which approach to adopt and how to implement it would be greatly appreciated.
Kind regards,
-Erie Boorman
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