Hi,
I have a question related to how to make an appropriate design
matrix using fs-fast 5.3. Subjects’ eye
movement was collected during an experiment. Then, the data has been
transformed to a continuous
variable with a number for each TR. The
better fixation performance has higher number.
For example, a number would be 0 if subjects look away from a target
within a TR. In ideal situation,
subjects should keep his eyes on target all the time, so the variable should be
1 for all TR. According to
mkanalysis-sess documents, it seems that there are three different ways to take
into account of eye fixation performance: 1) use it as an external task
regressor;
2) use it as a weight in the paradigm file (the fourth column); 3) use it as a
nuisance regressor. My question is what’s
the difference between the three methods?
In my situation, which one is the best choice in my situation?
I hope the question is clear. Thanks so much for your help.
Xiaomin
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