If you want a prediction equation expressing RT as a linear function of "amplitude of EEG signal", "speed of saccade", and "fMRI brain activity" and you've already collected the data, this is doable. Of course, whose to say the relationship with each of these variables is linear. But, that's another story (see dpb's comment).
The following code with fake data for 10 participants demonstrates the mechanics of building such a model. And it should get you thinking about your goals.
eeg = rand(10,1);
saccade = rand(10,1);
fmri = rand(10,1);
rt = rand(10,1);
data = [ones(size(eeg)) eeg saccade fmri];
[b, ~, ~, ~, stats] = regress(rt, data)
0.3729 1.1893 0.39018 0.12236
The prediction equation is
rt = 0.861 - 0.161 x eeg - 0.581 x saccade x 0.034 x fmri
with R^2 = 0.3729.
I suggest you read the documenation on the regress function and study the examples. Good luck.