help > RE: Concatenation problem (spm_fmri_concatena
Aug 24, 2017  06:08 AM
RE: Concatenation problem (spm_fmri_concatena
See inline responses below.
Originally posted by Dmit Filin:
Dear gPPI users,

I have 2 sessions with 3 conditions. In the session#1 there are conditionA1, conditionB1, conditionC1. In in the session#2 there are conditionA2, condtitionB2, conditionC2. I want to compare conditions: A1 vs A2, B1 vs B2, C1 vs C2.

1) When I use one SPM model with two sessions gPPI works properly. Should I use P.ConcatR=1 if I have >40 trial by condition? (manual says: "use concatenated approach to deal with low # trials (<10 events)/event type").

RESPONSE: There is no need to concatenate the model in your case.

For this SPM model: "nscans = [450 470]" and "Sess=[1x2 struct]".

2) When I use one SPM model with concatenated sessions gPPI gives me this error message:

"VOI has 7 voxels in 3x3x3 space. This is in the the same space as the input data and functional mask.
ERROR: VOI timeseries is not the correct size. Must either be N same size as SPM.nscan or SPM.nscan*NT"

To concatenate two sessions I changed the onsets and rp*.txt files. And also I used this function:
"scans = [450 470];
spm_fmri_concatenate('SPM.mat', scans);"

It made two Constant regressors for two sessions.
According to the description of this function: "This will change your GLM in several respects. It will replace the usual mean column in the design matrix with regressors modelling each session - you can check this using the 'Review' button in the main SPM window. It will also correct the high-pass filter and temporal non-sphericity calculations to account for the original session lengths."

But after "spm_fmri_concatenate" gPPI doesnt work properly.

For this new SPM model: "nscans = [450 470]" and "Sess=[1x1 struct]".

When I change in SPM.mat "nscan" from [450 470] to [920] gPPI works well. But in the gPPI model I can see only one Constant regressor instead of two.

As I can understand the problem is in Sess=[1x1 struct]. How to solve this problem?

>> The solution to this problem is not to concatenate the first level model, but to use the 2 session SPM model and have gPPI do the concatenation on its own. Otherwise the input fields aren't correct.


Thank you in advance
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TitleAuthorDate
Concatenation problem (spm_fmri_concatenate)Dmit FilinAug 14, 2017
      Following up on this problemHaeme ParkAug 24, 2017
            RE: Following up on this problemDonald McLarenAug 24, 2017
                  RE: Following up on this problemDmit FilinAug 24, 2017
                        RE: Following up on this problemDonald McLarenAug 24, 2017
                              RE: Following up on this problemDmit FilinAug 24, 2017
      RE: Concatenation problem (spm_fmri_concatenaDonald McLarenAug 24, 2017