HI List experts,
I have a question in my mind, but I have never be such clear.
For the 3dDeconvolve step (of course, based on each subject), if I really do not collapse the regressors, I have about 70~80 regressors. Is that fine for a 3dDeconvolve? In detail,in my experiment, there are 5 runs, each run has 72 trials. The design is (6 SOAs x 6 Event conditions) x 10 repetitions/observations. As I have 6 SOA x 6 Event condition, so for the stimuli onset, I have 36 regressors. Then for the response stage, also 36 regressors. For them, totally 36+36=72 regressors. If I also include the error regressor, miss regressor, and then 6 motion regressors, then totally 80 regressors.
For each regressor, it has about 10 observations, i.e., each run has 2 observations for that event. For instance, the timeonsets for one regressor go below.
187.64 428.00
472.80 508.88
23.53 296.02
74.16 144.41
172.32 341.69
Is that fine that I run a 3dDeconvolve, with 80 regressors? How many is "TOO many"? Any good pointers?
Thanks so much,
Juan
