Thanks so much for your both. I have a further and special question for Bob.

Bob, I agree with you - that is very clear thinking. Suppose in my experiment (this is only for our discussion), I have three events: positive, negative and neutral. I can do the 3dDeconvolve in two ways, if I want to know the effect of emotion (i.e., positive and negative ones) vs. neutral. I define emotion as "positive + negative" here.

3dDeconvolve –input run_1+orig run_2+orig -nfirst 0 –polort 2 \
-num_stimts 2 \
-stim_times 1 Emotion_onsets ‘GAM’ -stim_label 1 Emotion \
-stim_times 2 Neutral_onsets ‘GAM’ -stim_label 2 Neutral \
-num_glt 1 \
-gltsym "SYM: Emotion -Neutral" -glt_label 1 Emotion_vs_Neutral \
-fitts fit_ts –errts error_ts \
-xjpeg glm_matrix.jpg \
–tout –fout -bucket glm_out1


3dDeconvolve –input run_1+orig run_2+orig -nfirst 0 –polort 2 \
-num_stimts 3 \
-stim_times 1 Postive_onsets ‘GAM’ -stim_label 1 Postive \
-stim_times 2 Negative_onsets ‘GAM’ -stim_label 2 Negative \
-stim_times 3 Neutral_onsets ‘GAM’ -stim_label 3 Neutral \
-num_glt 3 \
-gltsym "SYM: Postive -Neutral" -glt_label 1 Postive_vs_Neutral \
-gltsym "SYM: Negative -Neutral" -glt_label 2 Negative_vs_Neutral \
-gltsym "SYM: 0.5*Postive + 0.5*Negative -Neutral" -glt_label 3 Emotion_vs_Neutral \
-fitts fit_ts –errts error_ts \
-xjpeg glm_matrix.jpg \
–tout –fout -bucket glm_out2

The 2nd 3dDeconvolve is used as I thought that the comparisons "Positive vs. Neutral", "Negative vs. Neutral" would be interesting. Now I find that the Emotion vs. Neutral is more helpful, however.

According to your suggestion, it seems that the results of "Emotion vs. Neutral" would be different from those two different 3dDeconvolve approaches. Then which one should be trusted and reported?

Thanks so much for your time,
Juan