> Thanks for the response, Rick. I have 12 subjects, but I am looking
> at the distributions across voxels. 60,000 voxels should be plenty to
> get an even distribution that would allow 5% of the voxels to exceed
> the p < .05 threshold by random chance, would it not?

This is not quite correct. The t-distribution approaches the normal
distribution as the degrees of freedom approaches infinity (subjects
minus 1 in your case), but you have only 12 subjects. 60000 voxels is
multiple comparisons, but of the same non-normal test.

Keep in mind that these results depend on the variance of your data,
which comes not only from BOLD responses to your stimuli, but from how
the experiment was designed and how the data was processed.

---

To get a feel for the importance of the number of subjects, try this:

First, compute your test using 3dttest instead of 3dANOVA*, as it is
easier to manipulate for a single test. Just grab all the subject
volumes that went into the ANOVA and list them as '-set2' in a 3dttest
command. Run the 3dttest command. It should give the same results.

Now for comparison, input all of your subject datasets 4 times in the
otherwise same 3dttest command, so it is as if you had 4 times as many
subjects. Clearly the mean beta will be the same, but now the t-stats
should be basically doubled (as expected by the definition, the stat
will grow as sqrt(N)).

For a similar test, drop down to 3 subjects.

- rick