"I defined the contrast with "1" for conditions of interest (e.g., reward anticipation in each run) and "0" for other conditions (including error trials, if exist)"
his is correct if you wish to examine a main effect of your conditions of interest. If you wish to compare conditions, the best approach is to contrast them at the first level, and carry that con file to the second level.
e.g. if you have two events of interest and a simple model (HRF only), the cotnrast is 1 -1 to compare condition A > B, and then add a zero for the thirst condition if it is present.
I frequently use "dummy" events are you have proposed, and think it is a good approach in many circumstances.
Colin Hawco, PhD
Neuranalysis Consulting
Neuroimaging analysis and consultation
www.neuranalysis.com
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-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On Behalf Of Vincent Yeo
Sent: January-30-18 8:04 AM
To: [log in to unmask]
Subject: [SPM] Question about modeling error trials
Dear all,
I am currently analyzing some fMRI data of a 2-run monetary incentive delayed task. I found that about 1/2 subjects showed no response (error) in at least 1 trial, and I would like to add a new condition of error trial(s) to the 1st-level model to account for the effect. However, since the other 1/2 subjects made no mistakes during the task, the 1st-level model for different subjects or different runs of the same subject may be different. I defined the contrast with "1" for conditions of interest (e.g., reward anticipation in each run) and "0" for other conditions (including error trials, if exist) and used the contrast files for the 2rd-level analysis, did I specify the 1st-level model correctly?
Thanks in advance.
Vincent
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