This may be a basic question but I've run into some trouble and I need help completing my first SPM analysis.
We have performed an experiment that investigates appraisals of peer relationships using fMRI and a social network questionnaire (SNQ). So during the first-level analysis specification I want to include the values given by the SNQ in the model as a regressor.
There were 48 trials in the session and 150 scans. There was 1 regressor value for each trial. SPM says that the length of the regressor vector must match the length of the scans vector. Each trial took 9 seconds on average (range = 8 - 10 seconds).
So I have a problem with creating a regressor vector that I can input into SPM.
What I have done to resolve this problem is write a function that repeats each regressor value 3 times (TR = 3; 3xTR = ~9 second trial). I have also input null values in relevant areas between trials.
However, this generally gives me a regressor vector length that does not quite match the scan vector length because the trial times are not consistent or perfectly divisible by TR; the overall length is usually out by 1-5 values.
So right now to resolve this the function adds or removes 0 values in areas of the vector that are not important i.e. outside of trial times.
This method is not perfect and will still lead to regressor values being slightly out of place but I can't think of an alternative method.
QUESTION:
Is this a good way of creating a regressor vector? Is there a better way that I am missing? Am I even thinking of the issue in the correct way as I am trying to marry scan data and regressor data (are they both similar enough data i.e. should I think of the scans as sequential like the regressors?).
Please let me know if you have any questions or if my question is unintelligible.
Cheers,
Dave
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