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help > Concatenation problem (spm_fmri_concatenate)
Aug 14, 2017 09:08 AM | Dmit Filin
Concatenation problem (spm_fmri_concatenate)
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").
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?
Thank you in advance
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").
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?
Thank you in advance
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Title | Author | Date |
---|---|---|
Dmit Filin | Aug 14, 2017 | |
Robin P | Jan 25, 2021 | |
Haeme Park | Aug 24, 2017 | |
Donald McLaren | Aug 24, 2017 | |
Dmit Filin | Aug 24, 2017 | |
Donald McLaren | Aug 24, 2017 | |
Dmit Filin | Aug 24, 2017 | |
Donald McLaren | Aug 24, 2017 | |